The Evolution of the Nature Management System and Modern Trends in Its Development

  • Published: 08 December 2022
  • Volume 43 , pages 212–217, ( 2022 )

Cite this article

thesis nature management

  • B. I. Kochurov 1 ,
  • V. V. Chernaya 2 &
  • R. M. Voronin 2  

1276 Accesses

Explore all metrics

We have examined the evolution of nature management systems in a historical context. An analysis has been made of the crisis of existing nature management models, an aggravation of contradictions, and an increase in threats and risks at the beginning of the 21st century. Modern trends in the development of effective nature management have been discussed, namely, low-waste technologies, technoecopolises, agroecopolises, and green clusterization. We have generalized and suggested conceptual prospects in the realm of effective nature management: the concept of a New Ecological Policy and a new “ecopolicy of containment.” We have explored the possibility of introducing the culture of nature management contributing to reinforcing the necessary rules and regulations—the binding force of the system of restrictions and prohibitions for humans in nature management, with due regard for the sustainability of natural systems. Emphasis is placed on a crucial need for changes in mass-scale consumer stereotypes and for an increase in the number of green technologies and production and the furthering of ecological education and medical–ecological tourism, as well as the importance of reorientation of the attitudes of the population from ecological–consumer to social–spiritual values in accordance with the Code of the Culture of Nature Management. We have substantiated the need for integrating the economic determinism of nature management and the ecological–economic imperative of sustainable development based on a noospheric approach.

Similar content being viewed by others

thesis nature management

Making sense of nature conservation after the end of nature

thesis nature management

Landscape Ecology Culture and Some Principles of Sustainable Nature Use

thesis nature management

Against Environmental Protection? Ecological Modernization as “Technician Ecology”

Explore related subjects.

  • Artificial Intelligence

Avoid common mistakes on your manuscript.

INTRODUCTION

The development of life, the maintenance of species diversity, and even the emergence of new organisms is possible only if there are favorable environmental conditions. In the history of the Earth, due to changes in the natural environment, many organisms have disappeared without a trace and others suddenly appeared, more developed and adapted, with a unique body structure and exceptional abilities [ 1 – 6 ]. During the appearance of Homo sapiens, on the one hand, all possible ecological niches had already been filled, but, on the other hand, there were favorable natural conditions for its existence. Today the most important global duty for a person is to maintain the environment of their habitat at the proper level. The unwillingness to fulfill this function threatens humanity with various dangers and, ultimately, extinction. The COVID-19 pandemic clearly demonstrates that it is impossible to eliminate global risks only by the development of medicine and the healthcare system [ 7 , 8 ].

Man is an integral part of the single “living organism” of the Earth’s biosphere and must ensure the waste-free activity of all living things and maintain the most effective natural mechanism—the circulation of matter, energy, and information. According to the law of internal dynamic equilibrium, matter, energy, information and the dynamic qualities of individual natural systems in their hierarchy are interconnected so much that any change in one of these indicators causes concomitant functional–structural quantitative and qualitative changes that preserve the total amount of material–energetic, informational, and dynamic qualities of the system where these changes occur, or in their hierarchy.

Human economic activity has led to changes in biogeochemical cycles and the destruction of individual components of its “biological” link—many species of animals and plants—which makes this “living organism” sick and disturbs the human habitat, in some places completely destroying and degrading it.

Thus, in modern realities, the problem of effective nature management goes far beyond the scope of economic or social issues, but is directly related to the very existence of human civilization; that is, it refers to global, worldwide problems that require their solution in the foreseeable future.

EVOLUTION OF THE NATURE MANAGEMENT SYSTEM

One important question is, when did humans begin to engage in environmental management in the current sense of this term? From a modern point of view, environmental management is the science of the rational and balanced use of natural resources; it is the involvement of territorial complexes of the natural environment and their resources in the process of social production, culture, and recreation, as well as their rational and balanced use, protection, restoration, and transformation [ 9 ].

It is believed that the history of mankind began from 3400–3300 B.C. with the advent of writing [ 10 ]. However, this is not entirely accurate, since even before that time, human society actively interacted with the environment [ 1 – 3 ]. Thus, a number of researchers connect the beginning of the history of mankind with the appearance of behavioral signs similar to the characteristics of modern people. The time frame is quite difficult to establish and is the subject of a dispute between scientists, ranging from 200 000 to 40 000 B.C. [ 11 , 12 ].

The most correct, in our opinion, is the neurobiological approach [ 13 ], according to which representatives of the genus Homo became behaviorally modern people with the acquisition of prefrontal synthesis (PFS), which is a conscious purposeful process of synthesizing new mental images. This date is defined as 42 000 B.C., i.e., coincides with the time of the appearance of works of art—images of figures of people and animals [ 14 , 15 ] (see Fig. 1 ). This important event in the history of mankind provided the grounds for American researcher V.V. Torvich [ 1 – 3 ] to single out the first group of resources during this period of time (consisting of similar types of resources), “new mental images,” which are very important for the development of human society.

figure 1

Block diagram of a comprehensive assessment of the ecological and economic balance of the territory. NP, natural protection of the territory; NRP, natural resource potential; AL, anthropogenic load; EES, ecological and economic state of the territory; and EEB, ecological and economic balance of the territory.

According to V.V. Torvich, “resources are tools, things, qualities, and methods that can be used to achieve human goals” [ 2 , p. 48]. In total, in the history of mankind, the author identified 26 groups of resources: from new mental images to artificial intelligence (AI).

The largest amount of new resources was mastered by humans during the Holocene period (11 700 B.C.) (see Fig. 1 ), when climatic conditions became most favorable for the development of human activity [ 1 – 3 ]. The cold climate on Earth has changed to a warmer one. The most dramatic warming occurred around 9700 B.C. Since this period, mankind has been able to successfully domesticate many plant and animal species (see Fig. 1 ), which has created unprecedented opportunities for various types of economic activities. A rapid increase in population began. In 2019 A.D., 7.6 billion people lived on Earth, which is 1 million times more than in 1000 B.C. [ 16 , 17 ], primarily due to the high rate of technological breakthroughs. Traditional nature management is increasingly becoming a thing of the past. New types of nature management have appeared, on the basis of which the industrial period (stage) in the development of human society started several centuries ago, gradually giving way to the postindustrial one. These periods are characterized by the fact that the social systems created in them increasingly depend not on the effect of influences, but on the consequences of the development of the systems themselves [ 18 – 21 ].

In connection with the threat of an ecological catastrophe, to which human society as a result of its economic activity (especially over the past decades) has come close, there is a need to revise the old approach and develop new ones that can stop destruction and death and ensure the further development of mankind. How does one see the further development of human society? V.V. Torvich [ 1 – 3 ] believes that humanity is subject to the so-called directed process and is moving towards an increase in the number of “great” opportunities for its development. This is confirmed by the increase in the number of various resources for development, which cannot always contribute to it and often lead to the degradation and death of all living things. As for the statement about the controllability of the process of emergence of new resources, technologies, tools, methods, etc., there is no evidence for this. It is only obvious that new resources expand the possibilities of influencing the environment [ 1 , 3 , 18 , 20 ].

Human society must adequately respond to various threats and challenges, and this is the main and only condition for its development and preservation. The creativity of people who make new resources is what determines the development of human society today. However, creativity must be controlled, humane, and not provide conditions for self-destruction and the death of mankind. The ever-increasing insatiability of the modern consumer society, which negatively affects the natural environment, is manifested in the uncontrolled development of the market for biotechnologies, genetic engineering, and nanotechnologies, which in the future can cause irreversible consequences—mutations and the emergence of new viruses and diseases, which can lead to the extinction of humans on Earth. In this case, we are talking about irresponsible scientific activity in modern civilization.

The alternative is the development of low-waste technologies, technoecopolises, agroecopolises, and green clusters, which can minimize the impact of by-products of technogenesis; technogenic accidents and disasters should be reduced by decreasing the energy intensity of the economy and creating autotrophic natural–anthropogenic ecosystems [ 19 – 23 ].

There are a number of prerequisites for the development of this direction, first and foremost, the growth of our knowledge and ideas about the structure and patterns of functioning of the biosphere, geo-eco-sociosystems, and the rapid development of green technological innovations that make the goal quite feasible. Today, a number of countries are developing low-waste industries and closed life support systems for outer-space, underground, underwater, and arctic purposes and sustainable green technologies and concepts. Cities of the future, from the point of view of the principle of autotrophy, are considered practically closed geosystems with a predominance of the eco-urban structure [ 24 , 25 ].

According to experts [ 26 ], environmentally compatible technologies must correspond to the natural features and patterns of the Earth’s territory, cause no harm to nature, and be in harmony with it.

In recent years, as part of environmentally compatible technologies that are used on living organisms or in contact with them, nanotechnology products, hybrid and bionic devices, and biorobotic systems [ 26 , 27 ] stand out; their environmental consequences are difficult to imagine or predict.

Environmentally compatible technologies include alternative energy—nontraditional ways of obtaining, transmitting, and using energy. Alternative energy sources are understood as renewable natural resources: water, sunlight, wind, biofuels, etc. However, the replacement of oil, gas, coal, and wood combustion technologies with alternative energy does not exclude its negative impact on the natural environment. This can be a serious reason for revising the prospects for its further development.

MODERN DIRECTIONS OF THE DEVELOPMENT OF EFFICIENT NATURE MANAGEMENT

Modern environmental management is determined by three main indicators [ 1 , 2 , 5 ]: (1) the balance between the production (profit-generating) and environmental (green) sectors of the economy, (2) the creative activity of the population in two directions: national (to work for the state) and individual (to ensure their livelihoods), and (3) the balance between real and monetary efficiency of production.

As was shown by our calculations [ 20 ], for the regions of Russia and the world, a balanced and harmonious ratio of the main indicators of nature management is created when their ratio is 1.0–1.5:

1 < (PGS/GES) < 1.5, where POS is a profit-generating sector and GES is a green economic sector;

1 < (NCAP/ICAP) < 1.5, where NCAP is the nationwide creative activity of the population and ICAP is the individual creative activity of the population;

1 < (REP/MEP) < 1.5, where REP is the real efficiency of production and MEP is the monetary efficiency of production.

For example, the profit received from production activities provides a balance between the sphere of production and services, as well as the quality of the natural environment with its constant improvement [ 5 ].

If the values in the considered ratios exceed 1.5, then this indicates economic and environmental problems (a decline in production, a rapid depreciation of assets, pollution and degradation of the natural environment, etc.), which manifests itself in the form of economic, financial, and other crises that are cyclical. Thus, an increase in environmental safety and sustainability of development is seen only in a balanced approach and harmony between competing interests.

Increasing the efficiency of nature management, both from an economic and environmental point of view, is likely an insufficient measure, but it postpones the onset of a global environmental catastrophe for a certain period [ 18 – 21 ]. Therefore, effective environmental management can be considered with full confidence as a new “resource package” for the development of mankind, when the value of the results of this social and production activity exceeds the value of the natural resources consumed in this case.

The current crisis in the models of nature management is also due to problems in the environmental policy of Russia and other countries. The concept of the New Environmental Policy (NEP) of environmental expert A.I. Kalachev [ 28 ] deserves close attention, placing the following emphasis:

(i) The state is the main beneficiary of solving the problems of environmental protection and nature management.

(ii) Human-centeredness: the state is a partner for business and citizens in solving problems, and the main customer of environmental services.

(iii) There is a guideline for solving environmental problems that reasonably depend on the existing shortcomings of nature management models.

Understanding the threats looming over society (environmental disasters, pandemics, and economic crises) is a global challenge for fundamental science—the need to develop a new containment methodology (noospheric convergence) and create modern production, management, social, educational and other technologies on its basis [ 19 ].

It is urgent to achieve an ecological and economic balance on Earth based on the noospheric concept, efficient nature management, and the principles of sustainable development (see Fig. 1 ). The world, according to the capitalist model of society and based on Adam Smith’s idea of economic growth, gradually ceases to be attractive and loses its relevance [ 18 – 21 ].

The noospheric approach is the basis of the modern development of human society. It is a global concept aimed at a gradual transition to autotrophy, strategic initiatives and planning, a new environmental policy, the development of local communities (civil society), and the maximum conservation of natural landscapes and ecosystems. It can be viewed as a kind of convergence at the intersection of technological innovations, as well as economics, ecology, education, which will bring human society to a fundamentally new level of development [ 19 ].

Undoubtedly, the creation of the noosphere as an area of interaction between nature and society is associated with the emergence and formation in the biosphere of the Earth of the bearer of consciousness (mind)—humanity. Hence, consciousness is the basis of the noosphere. Its state completely depends on the adequacy of the reflection by the consciousness of humanity of the relationship between it and nature [ 25 – 27 ].

In modern realities, consciousness and its manifestations are, to a large extent, spontaneous and destructive for the biosphere and the geographical sphere as a whole. Obviously, this situation will continue until our consciousness is freed from the idea of anthropocentrism and humanity learns to adhere to objective natural laws and subordinate its needs to them.

The level of responsible consumption of natural resources in the sphere of production, aimed at meeting human needs, is determined by the culture of nature management [ 18 , 19 ]. As a scientific direction, it studies the principles of rational use of natural resources, including the factors of anthropogenic and technogenic impacts on nature and their consequences for the population. The culture of nature management not only contributes to the consolidation of the necessary rules and norms, but also acts as a binding force for a system of restrictions and prohibitions for humans in the processes of nature management and the regulation of economic activity taking into account the sustainability of natural systems.

The culture of nature management is a membrane through which human interaction with nature takes place. Its most important direction, as we noted above, is the development of the mental qualities of the individual, primarily spirituality and harmony.

To balance the processes of nature management, it is extremely necessary to change consumer stereotypes; increase the number of green technologies and industries; develop environmental education, medical and environmental tourism, i.e.; reorient people from environmental–consumerism to social–spiritual in accordance with the Code of the Culture of Nature Management [ 18 , 19 ], which consists of two sections that have specific postulates.

The first section considers the limits of human adaptation to nature, namely the following postulates:

(i) Nature is the natural source of human vitality; we cannot be allowed to deplete it or needlessly waste it.

(ii) Man-made quasi-natural developments may conceal unknown, untested dangers; therefore, before offering innovations, constantly confirmed boundaries for their safe use should be indicated.

(iii) We cannot change natural conditions without taking into account even the smallest negative consequences, because they can cause unpredictable natural and man-made disasters.

(iv) Nature must be constantly taken care of by restoring its potential, and this restoration requires the same efforts and costs as are necessary for the extraction and consumption of natural resources.

(v) Humans are children of nature, and their increasing power should not be directed to its oppression, but to ensuring the creation of mutually beneficial and mutually enriching technologies for nature management.

The second section discusses the limits of nature’s adaptation to man, expressed in certain rules and prohibitions:

(i) One must not destroy nature; mankind has become powerful and capable of causing irreparable harm.

(ii) It is necessary to limit and control the level of scientific and technical progress in terms of possible damage to nature.

(iii) Natural resources cannot be used for excessive personal enrichment; they should be distributed in proportion to ability and labor.

(iv) One cannot build a relationship with nature built on half-truths: introducing even a small lie hidden underneath a grain of truth into the technologies of nature management will destroy nature over time and bring great misfortune.

(v) One cannot use natural wealth for excesses, praise, and out of envy for others, and the acquisition of the gifts of nature should be conditioned by the need for their consumption.

The culture of nature management, according to the Code of the Culture of Nature Management, is becoming the most important mechanism for achieving effective nature management, and we have to admit that other mechanisms are secondary and, without taking into account its requirements, lead to the destruction of the natural environment.

CONCLUSIONS

The development of human society and related nature management during the Holocene period (11 700 years) is characterized by an ever-expanding use of natural resources and the rapid emergence of new resources (genetic engineering and nanotechnologies), which has led to unprecedented pressure on the natural environment and put the world on the brink of ecological disaster.

It should be noted that the current environmental crisis is perhaps the deepest in the periods of modern and recent history, and it is global in nature. Today, there is no single scientifically based approach to overcoming the ecological crisis, and there is no universal trajectory for the development of human society. Existing standards, regulations, and calls for the formation of a green economy and green technologies and cities for the environmental protection of the economy and regulations only temporarily postpone the onset of regional crises and a global environmental catastrophe [ 27 , 29 – 31 ].

Obviously, in the 2000s, ecology, the rational use of natural resources, and environmental protection are becoming the leading force in the development of society. Nondecreasing emissions of ecopollutants, pseudoscientific concepts of energy supply, and gray technologies lead to local and regional environmental and economic crises and regional and global drops in the GDP. The scenarios of A. Peccei and A. King [ 32 ], according to which the global economic growth was supposed to stop in 2020, was justified to some extent, given the coronavirus pandemic.

The existing system of global consumer nature management leads to the fact that the main goal of society is stagnation and survival, rather than development and coevolution with nature. Understanding the threat of the COVID-19 pandemic looming over human society, global climate change poses a challenge to science, primarily geoecology and nature management, environmental resource science, etc., of enormous socioeconomic significance, as well as the further development of new concepts and models: the Ecopolitics of Containment and the New Environmental Policy. It is necessary to integrate the economic determinism of nature management and the ecological and economic imperative of the sustainable development of countries and regions based on the noospheric approach in the territory–resources–population–economy–ecology system.

Torvich, V.V. Mankind as a system, Slozhnye Sist. , 2020, Pt. 1, no. 1 (34), pp. 72–88.

Torvich, V.V. Mankind as a system, Slozhnye Sist. , 2020, Pt. 2, no. 2 (35), pp. 48–70.

Torvich, V.V. Mankind as a system, Slozhnye Sist. , 2020, Pt. 3, no. 3 (36), pp. 74–93.

Kayser, J., Schreck, C.F., Yu, Q.Q., Gralka, M., and Hallatscek, O., Emergence of evolutionary driving forces in pattern-forming microbial populations, Philor. Trans. R. Lond. Biol. Sci. , 2018, no. 373 (1747), https://www.ncbi. nlm.nih.gov/pmc/articles/PMC5904294/. Cited July 30, 2020.

Live Science Staff, Forces of Evolution, Live science, 2007. https://www.livescience.com/1796-forces-evolution.html. Cited July 30, 2020.

Haliday, T.J.D. and Goswami, A., Eutherian morphological disparity across the end-cretaceous mass extinction, Biol. J. Linnean Soc. , 2016, vol. 118, no. 1, pp. 152–168.

Article   Google Scholar  

Kochurov, B.I., Ivashkina, I.V., Fomina, N.V., and Ermakova, Yu.I., Urban health approach to the study and development of large cities, Geogr. Nat. Resour. , 2020, vol. 41, pp. 203–210.

Kochurov, B.I., Ivashkina, I.V., Fomina, N.V., Ermakova, Yu.I., Peculiarities of urban development after the coronavirus pandemic, Ekol. Urbanizir. Territorii , 2020, no. 3, pp. 90–97.

Ivanov, E.S., Chernaya, V.V., Vinogradov, D.V., Poznyak, S.S., and Kochurov, B.I., Ekologicheskoe resursovedenie: Uchebnoe posobie (Ecological Resource Science: Textbook), Ryazan: Ryazan. Agrotekhnolog. Univ., 2018.

History.com. https://www.history.com/tohics/pre-history. Cited July 30, 2020.

Soressi, M., Late Mousterian Lithic Technology. Its Implication for the Pace of the Emergence of Behavioral Modernity and the Relationship between Behavioral Modernity and Biological Modernity , Johannesburg: Univ. of Witwatersrand Press, 2005, pp. 389–417.

Google Scholar  

Wilfond, J.N., When Humans Became Human. https://www.nytimes.com/2002/02/26/scince/when-humans-became-human.html. Cited July 30, 2020.

Vyshedskiy, A., Development of behavioral modernity by hominins around 70,000 years ago was associated with simultaneous acquisition of a novel component of imagi-nation, called prefrontal synthesis, and conversion of a preexisting rich-vocabulary non-recursive communication system to a fully recursive syntactic language. https://www.biorxiv.org/content/10.1101/ 166520v5. Cited July 30, 2020.

Aubert, M., Lebe, R., Oktaviana, A.A., Tang, M., Burhan Z., Hamrullah, Jusdi A., Abdullah, Hakim B., Zhao, J-X., Made Geria, I., Sulistyarto, P.H., Sardi, R., and Brumm, A., Earliest hunting scene in prehistoric art, Nature , 2019, no. 576 (7778), pp. 442–445

Charles, Q.C., Humanity’s Oldest Cave Art Shows Shape-Shifting Supernational Hunters. https://www.livescience.com/oldest-rock-art-supernatural-beings.html. Cited July 30, 2020.

Roser, M., Ritchie, H., and Ortiz-Ospine, E., World Population Growth revision in May, 2019. https://ourworldindata.org/world-population-growth. Cited July 30, 2020.

Total World Population – Census Bureau, Table 1331, Population Change by Development Status: 1950 to 2050, vs Census. https://books.google.ru/books?id= iDWMJjP1xJgC&pg. Cited August 31, 2020.

Kochurov, B.I., Lobkovskii, V.A., and Smirnov, A.Ya., Effektivnost’ i kul’tura prirodopol’zovaniya (Efficiency and Culture of Nature Management), Moscow: RUSLINE, 2020.

Kochurov, B.I., Smirnov, A.Ya., and Lobkovskii, V.A., The concept of Russia’s development: From excess to necessity, Geol., Geogr. Glob. Energ.: Nauchno-Tekhn. Zh. , 2008, no. 1 (28), pp. 38–47.

Kochurov, B.I., Ekodiagnostika i sbalansirovannoe razvitie (Ecodiagnostics and Balanced Development), Moscow: Izd. Dom Infra-M, 2016.

Kochurov, B.I., Ivashkina, I.V., Ermakova, Yu.I., and Fomina, N.V., Geoecological forecast and use of energy carriers, Ekol. Sist. Pribory , 2020, no. 4, pp. 39–50.

Korogodin, V.I. and Korogodina, V.L., Infrastruktura kak osnova zhizni (Infrastructure as the Basis of Life), Dubna: Izd. Tsentr Feniks, 2000.

Kondratenko, P.A., Creation of life in the model of the Universe with minimum initial entropy, J. Sci. Leon , 2020, no. 11, pp. 40–47.

Kochurov, B.I., Blinova, E.A., and Ivashkina, I.V., Development of Russian cities after the COVID-19 pandemic, Reg. Geosist. , 2021, vol. 45, no. 2, pp. 183–193.

Frolov, V.A., A systematic approach to the problem of interaction between the biosphere and space, in Sovremennyye problemy izucheniya i sokhraneniya biosfery (Modern Problems of Studying and Preserving the Biosphere), St. Petersburg: Gidrometeoizdat, 1992, Vol. 1, pp. 82–88.

Shumov, V.A., Development of nature-like technologies, Int. Independent Sci. J. , 2020, no. 21, pp. 46–50.

Baklanov, P.Ya., Territorial’nye struktury khozyaystva v regional’nom upravlenii (Territorial Structures of the Economy in Regional Management), Moscow: Nauka, 2007.

Kalachev, A.I., New environmental policy: ecology must become an economic category! https://Infragreen.ru/expetise/134900. Cited February 22, 2022.

Privalovskaya, G.A., Territorial combinations of resources and ecological situation, in Natsional’nyi doklad “Strategicheskie resursy Rossii”: Inform.-analit. materialy (National Report “Strategic Resources of Russia”: Inform.-Analit. Materials), Moscow: Nauka, 1996, pp. 74–77.

Vvedenie v geografiyu: Uchebnoe posobie (Introduction to Geography: Textbook), Kochurov, B.I., Ed., Moscow: KNORUS, 2020.

Mirzekhanova, Z.G., Some directions of regional environmental policy in the strategy of long-term development of the Khabarovsk Krai, Reg. Probl. , 2020, vol. 13, no. 1, pp. 115–119.

Kovalchuk, M.V. and Naraykin, O.S., Nature-like technologies – new opportunities and new threats, Indeks Bezopasnosti , 2018, vol. 22, no. 3–4, pp. 104–108.

Download references

Author information

Authors and affiliations.

Institute of Geography, Russian Academy of Sciences, 119017, Moscow, Russia

B. I. Kochurov

Pavlov State Medical University, 390026, Ryazan, Russia

V. V. Chernaya & R. M. Voronin

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to B. I. Kochurov , V. V. Chernaya or R. M. Voronin .

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by S. Avodkova

Rights and permissions

Reprints and permissions

About this article

Kochurov, B.I., Chernaya, V.V. & Voronin, R.M. The Evolution of the Nature Management System and Modern Trends in Its Development. Geogr. Nat. Resour. 43 , 212–217 (2022). https://doi.org/10.1134/S1875372822030064

Download citation

Received : 05 November 2021

Revised : 22 December 2021

Accepted : 29 March 2022

Published : 08 December 2022

Issue Date : September 2022

DOI : https://doi.org/10.1134/S1875372822030064

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • sustainable nature management
  • green technologies
  • nature-compatible technologies
  • new ecological policy
  • culture of nature management
  • Find a journal
  • Publish with us
  • Track your research

MSc in Nature Management

  • Nature Management
  • Programme Structure

Female students on the woods

Programme Structure

Compulsory thematic courses will give you the basic understanding of the core academic subject areas in the programme.

In addition, you choose courses from a pool of restricted elective courses, thereby strengthening your specific profile.

Finally, it is possible to personalise your degree and to create a profile that suits your personal academic interests by choosing between many elective courses: These could include biodiversity and conservation, ecology, nature perception, environmental economics, environmental chemistry, conflict management, etc.

The teaching varies between lectures, exercises, excursions, and project work. The thematic course and most of the elective and restricted elective courses include field work and excursions.

The MSc programme is concluded with a scientific project, the thesis, which takes 4 or 7 months and entitles graduates to the title Master of Science (MSc).

Do a Project in Practice or Study Abroad

You may choose to use some of your elective courses to do a project in practice in collaboration with a company or an institution. You can also study abroad for one or two semesters.

The programme can be structured in two different ways, depending on the size of your thesis:

Programme Overview, Thesis 30 ECTS

Compulsory courses: 15 ECTS Restricted elective courses: 45 ECTS Elective courses: 30 ECTS Master's thesis: 30 ECTS

Restricted elective course Restricted elective course Restricted elective course
Restricted elective course Restricted elective course
Elective course Elective course Thesis
Elective course Elective course

One block each year equals nine weeks of study and 15 ECTS.

Programme Overview, Thesis 45 ECTS

Compulsory courses: 15 ECTS Restricted elective courses: 45 ECTS Elective courses: 15 ECTS Master's thesis: 45 ECTS

Restricted elective course Restricted elective course Restricted elective course
Restricted elective course Restricted elective course
Elective course Thesis
Elective course

Restricted Elective Courses

Choose your restricted elective courses from the lists below. Click on each course for a detailed description.

You are required to choose one of the following courses:

  • Thematic Course II: Rural Landscape – Management and Planning (15 ECTS)
  • Thematic Course llB: Rural Landscape – Management and Planning (15 ECTS)

Furthermore, you must choose one of the following courses:

  • Environmental & Planning Law – Nature & Water (bachelor level; course language: Danish)
  • EU Law – Environment, Agriculture and Food (bachelor level)
  • Global Environmental Governance

Your remaining courses must be chosen from the list below:

  • Soil and Water Pollution, Concepts and Theory
  • Biodiversity in Urban Nature
  • Biodiversity in Managed Forests
  • Ethics, Environment and Society
  • Landscape and Restoration Ecology
  • Strategic Planning for Urban Nature
  • Rural Landscapes: Transformation and Governance
  • Nature Perception – Theories and Methods for Investigation
  • Conservation Biology
  • Conflict Management
  • Macro Ecology and Community Ecology
  • Ecosystem Services from Forests and Nature
  • Applied Statistics: From Data to Results
  • Applied Ecosystem Ecology
  • Motivation and Pro-Environmental Behaviour – Managing Change
  • Countryside Planning (course language: Danish)
  • Geographical Informations Systems (GIS)
  • Land Use and Environmental Modelling
  • People, Nature and Recreation
  • Climate Change Mechanisms and Tipping Points
  • International Nature Conservation
  • Introduction to Data Science (IDS)
  • Aerial and Near-Field Remote Sensing
  • Feltkursus i naturforvaltning

Are you already a student at Nature Management?

Find the programme structure that fits your year of admission on your Study Information.

Learn more about the programme in the Curriculum for MSc in Nature Management .

Shared section of the curriculum  for all programmes at the Faculty of SCIENCE.

UCPH has more than 300 courses on climate and sustainability. See how to get more green competences

The requested URL was rejected.

  • Norwegian Bokmål
  • Find employee
  • Find study plan

Bachelor's Thesis in Nature Management

The subject is reserved for students of the following study programmes:

  • Nature Management, Bachelor's Programme

After completing the course, the student will have achieved the following learning outcomes:

  • has knowledge of scientific work and the development of new knowledge
  • has knowledge about the connections between topic/issue, research question, methods, analysis and scientific writing
  • can develop a project and formulate issues/hypotheses
  • can apply scientific method
  • can analyse an issue applying literature, theory and/or empirical data
  • can make a written scientific report

General competence:

  • has the ability to reflect critically
  • has the ability to read and understand professional scientific literature

This is largely an independent piece of work where the students are supervised by an appointed teacher/lecturer.

The framework for the assignment and relevant themes will be introduced in the 4th semester. Students who plan to conduct their field work during the summer must have their assignment approved and a supervisor appointed during the 4th semester, the rest of the students will have this in their 5th semester. The teaching on project work (5th semester) consists of lectures with exercises as well as submission of a pilot project towards the end of the semester.

The bachelor's thesis may be written by one student alone or by two in cooperation. Cooperation may take place across different study programmes.

Compound Assessment

  • Compulsory work. Approved/ Not approved. Must be passed prior to submission of the bachelor´s Thesis.
  • Compulsory participation. Approved/ Not approved. Must be passed prior to submission of the bachelor´s Thesis.
  • Bachelor´s Thesis, comprises 100% of the grade, grading scale A-F.

Employee photo: Jan Eivind Østnes

Jan Eivind Østnes

thesis nature management

MSc thesis projects - Plant Ecology and Nature Conservation Group

Our research can roughly be divided into three themes. Below you will find general information on these themes, but first we would like to provide you with some guidelines on how to select the right thesis project.

How to choose a thesis project?

The MSc thesis projects are clustered in research themes that cover the fields of interest of our lecturers, post-docs and PhD students. They are listed as supervisors. Many subjects are also suitable for a BSc thesis. Length and content of a thesis project may be tailored to your wishes. An overview of available project can be found in the TIP-database http://tip.wur.nl . New projects will be added to this database throughout the year.

If you are interested in a particular thesis project you can contact the supervisor of the project directly. Alternatively, if you are interested in a theme but you cannot find a suitable project, you may consult the contact person of the theme. When you have difficulties choosing a theme, please contact Juul Limpens ( [email protected] ).

You can also do a thesis project at a research institute or a different university in the Netherlands or abroad, on the condition that the project and the supervision are of sufficient scientific quality (PhD supervisor) and a supervisor from PEN is involved.

Start in time with looking for a thesis project and contacting people: preferably 3 to 9 months before the start of your project. Preparations for projects abroad take a long time. Some projects may require following an additional course.

Information on procedures around theses and internships and instructions for doing a thesis project are presented in the ‘Guidelines for preparing an MSc-thesis’. A hard copy can be obtained at the secretary’s office after registration for a thesis. The Guidelines also give an overview of prerequisite and recommended courses for a thesis PEN.

Theme 1 Environment and ecosystem functioning

Contact person: Juul Limpens

Other supervisors: Monique Heijmans, José van Paassen, Rúna Magnússon

Background: This theme covers our research on large-scale human influences on ecosystem functioning. Increased greenhouse gas concentrations in the atmosphere, climate change and nitrogen deposition strongly affect nutrient- and water cycling within ecosystems, plant growth, and competitive relations between plant species. Such effects may change vegetation succession and biodiversity. Conversely, the resulting changes in the vegetation can have important consequences for ecosystem processes such as biomass production, carbon sequestration and emission, evapotranspiration, erosion, absorption and reflection of solar radiation.

Research: Peatlands equal forests as carbon (C) stores due to slow decomposition of the water-locked plant material. Large-scale draining of peatlands and extraction of peat have removed the lock on the stored carbon, turning them into sources for greenhouse gasses. At PEN we study functioning of intact, degraded and rewetted peatlands in the Netherlands and abroad to 1) understand how the ecosystem services change with environmental and human stressors and 2) how we can use these relationships to best manage and restore these ecosystems. (José van Paassen, Juul Limpens)

Northern ecosystems are facing rapid climate warming. In response, shrub vegetation is expanding. Good news, as shrubs can store carbon and protect permafrost soils from warming up in summer through shading. Bad news, as shrubs can warm up the soil in winter by capturing snow. Climate change, shrub expansion, permafrost degradation and vegetation succession - and their many interactions! - make for an exciting puzzle to work on in challenging environments. (Rúna Magnússon, Juul Limpens, Monique Heijmans)

Coastal ecosystems protect a large part of the world’s shores against flooding, harbour their own special species and often serve as recreation areas. One of the big questions is to what extent these ecosystems can keep on offering these services as the sea level keeps on rising: how resilient are salt marshes and dunes? (Juul Limpens)

Type of work: The research involves field observations, experimental work in field, garden or greenhouses, remote sensing, simulation studies on long-term dynamics of ecosystems and tree-ring studies on polar shrubs.

Theme 2 Biodiversity and ecosystem functioning

Contact person: Fons van der Plas

Other supervisors: Amanda Taylor, Coline Boonman, Philippine Vergeer

Background: The biodiversity within ecosystems is an important aspect of the conservation value of ecosystems, because species rich communities are rare and many endangered species occur mainly in species rich communities. After many years of research the regulation of biodiversity is still poorly understood. How can we explain that 40 or more plant species of higher plants per m2 coexist in some communities, while other communities contain only a few species? How do species manage to survive under the pressure of competition, stress and disturbance? What circumstances are favourable to species richness and how can we promote and maintain or destroy these circumstances? The role of biodiversity in ecosystem functioning is even more obscure. Species richness could have important impacts on other ecosystem properties and functions such as resource use, biomass production, and resistance to invasions.

Several projects are united under this theme.

A. The importance of biodiversity for ecosystem processes

The rapid loss of species has inspired ecologists to investigate the importance of biodiversity for the functioning of ecosystems. For some ecosystem processes, such as primary productivity in grasslands, several experiments have shown loss of plant species is detrimental. This negative effect has been ascribed to a loss of beneficial interactions among species. However, we still do not fully understand which interactions and, more importantly, how they work. In addition, the importance of biodiversity for many other ecosystem processes, in different ecosystems, is unclear. For example, some experiments have shown biodiversity effects for decomposition of dead organic material, a crucial process driving C and N cycles and ultimately productivity, but other studies found no effect or even negative effects! So far, we cannot explain these conflicting results. New clever experiments are strongly needed.

B. Regulation of plant species richness

In nature conservation it is important to know which circumstances are important for the development of species rich communities and how can we restore species rich communities. The relation between species richness and nutrient availability is especially important, since nutrient availability is influenced unintentionally by environmental problems, like eutrophication, and agricultural practices, like drainage. It can also be manipulated deliberately by conservation management practices (like grazing, mowing, sod cutting, hydrological measures, and fertilisation). The highest species richness is usually found at intermediate levels of biomass production, as set by the availability of the most limiting nutrient. We investigate how species richness depends on biomass production, above-ground structure of the vegetation, identity and number of (co-)limiting nutrients. To determine which factors limit the various coexisting species we measure biomass nutrient concentrations and  responses to fertilisation with separate nutrients in the field. To understand differences in response we investigate nutrient uptake efficiency and nutrient use efficiency in pot and water culture experiments in the greenhouse.

C. Ecological patterns in biodiversit y

Spatial patterns in biodiversity may determine the location of specific ecosystem services and may guide conservation efforts. ecological questions regarding a shift in spatial patterns or community adjustments due to disturbance (e.g. climate change, fire, management) can be answered at various scales, from local to global and from species to community levels. the research focus of pen lies within grasslands, urban environments, and global spatial scale patterns, where field studies and large database analyses are combined. applying the latest biodiversity models enables us to link patterns in biodiversity to environmental conditions and functional traits., theme 3 nature conservation in agricultural landscapes.

Contact person: Prof.Dr. David Kleijn. E-mail

Other supervisors: Jeroen Scheper, Thijs Fijen

Background: In Europe, some of the most species-rich ecosystems have developed as a result of prolonged and extensive use by mankind (e.g. calcareous grasslands, sub-alpine meadows). The diversity and species richness of these habitats is currently under threat, particularly in agricultural areas. Policy makers at the EU and member state level have recognised this and have started large-scale conservation initiatives. One of the initiatives to reverse the trend of progressive bio-diversity loss, ‘agri-environment schemes’ (financial compensations for farmers willing to enhance biodiversity on their land), aims to integrate nature conservation into farming. However, because agri-environment scheme fail to halt farmland biodiversity loss, there is an increasing number of grassroots, bottom-up conservation initiatives by municipalities, citizens and even scientists.

Research: The research within the theme ‘Nature conservation in agricultural landscapes’ focuses broadly on questions:

A. How can we optimize the effectiveness of nature conservation in agricultural landscapes?

Here we focus on gaining a better understanding of (the factors influencing) the effectiveness of conservation measures in agricultural landscapes. We study conservation, not only on farmland (e.g. wildflower strips, strip-cropping) but also in nearby public space (e.g. staggered mowing in road-side verges) and protected areas. The projects address a range of different questions. Does a landscape-scale approach where integrated conservation measures are being implemented by many different stakeholders work better than traditional conservation approaches? What are the ecological benefits of strip cropping for insect biodiversity and farmland birds? Do ambitious nature conservation strategies of municipalities result in significant biodiversity gain? Why are most farmers reluctant to integrate the management of biodiversity into their farm business? Is co-design of conservation measures with farmers more effective than science-led conservation? A range of species groups is included in these projects (plants, birds, bees and hover flies, invertebrates in general). Most project will take place in the Netherlands, but some projects offer opportunities for MSc theses and Internships in other European countries such as Latvia, Hungary and Spain.

B. What is the contribution of biodiversity to agricultural production?

A second line of attack under the theme ‘Nature conservation in agricultural landscapes‘ quantifies the contribution of biodiversity to agricultural production. Evidence for this can help convince farmers to support biodiversity on their farms. Research mainly focusses on pollination and pest control as key regulating services, although some projects include soil services such as carbon sequestration and nutrient cycling. The projects under this theme address research questions such as: What is the relationship of flower visitation rate by wild pollinators to yield of insect pollinated crops? Does extensification of grassland management result in significant ecosystem service benefits? Does nature-inclusive farming enhance pest control? Do the benefits of enhancing biodiversity on farms outweigh the opportunity costs to farmers? These questions are mainly being addressed by studying functionally important species groups such as bees, spiders and carabid beetles and mostly in research carried out in the Netherlands.

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

  • Advanced Search
  • Journal List
  • Springer Nature - PMC COVID-19 Collection

Logo of phenaturepg

The Evolution of the Nature Management System and Modern Trends in Its Development

B. i. kochurov.

1 Institute of Geography, Russian Academy of Sciences, 119017 Moscow, Russia

V. V. Chernaya

2 Pavlov State Medical University, 390026 Ryazan, Russia

R. M. Voronin

We have examined the evolution of nature management systems in a historical context. An analysis has been made of the crisis of existing nature management models, an aggravation of contradictions, and an increase in threats and risks at the beginning of the 21st century. Modern trends in the development of effective nature management have been discussed, namely, low-waste technologies, technoecopolises, agroecopolises, and green clusterization. We have generalized and suggested conceptual prospects in the realm of effective nature management: the concept of a New Ecological Policy and a new “ecopolicy of containment.” We have explored the possibility of introducing the culture of nature management contributing to reinforcing the necessary rules and regulations—the binding force of the system of restrictions and prohibitions for humans in nature management, with due regard for the sustainability of natural systems. Emphasis is placed on a crucial need for changes in mass-scale consumer stereotypes and for an increase in the number of green technologies and production and the furthering of ecological education and medical–ecological tourism, as well as the importance of reorientation of the attitudes of the population from ecological–consumer to social–spiritual values in accordance with the Code of the Culture of Nature Management. We have substantiated the need for integrating the economic determinism of nature management and the ecological–economic imperative of sustainable development based on a noospheric approach.

INTRODUCTION

The development of life, the maintenance of species diversity, and even the emergence of new organisms is possible only if there are favorable environmental conditions. In the history of the Earth, due to changes in the natural environment, many organisms have disappeared without a trace and others suddenly appeared, more developed and adapted, with a unique body structure and exceptional abilities [ 1 – 6 ]. During the appearance of Homo sapiens, on the one hand, all possible ecological niches had already been filled, but, on the other hand, there were favorable natural conditions for its existence. Today the most important global duty for a person is to maintain the environment of their habitat at the proper level. The unwillingness to fulfill this function threatens humanity with various dangers and, ultimately, extinction. The COVID-19 pandemic clearly demonstrates that it is impossible to eliminate global risks only by the development of medicine and the healthcare system [ 7 , 8 ].

Man is an integral part of the single “living organism” of the Earth’s biosphere and must ensure the waste-free activity of all living things and maintain the most effective natural mechanism—the circulation of matter, energy, and information. According to the law of internal dynamic equilibrium, matter, energy, information and the dynamic qualities of individual natural systems in their hierarchy are interconnected so much that any change in one of these indicators causes concomitant functional–structural quantitative and qualitative changes that preserve the total amount of material–energetic, informational, and dynamic qualities of the system where these changes occur, or in their hierarchy.

Human economic activity has led to changes in biogeochemical cycles and the destruction of individual components of its “biological” link—many species of animals and plants—which makes this “living organism” sick and disturbs the human habitat, in some places completely destroying and degrading it.

Thus, in modern realities, the problem of effective nature management goes far beyond the scope of economic or social issues, but is directly related to the very existence of human civilization; that is, it refers to global, worldwide problems that require their solution in the foreseeable future.

EVOLUTION OF THE NATURE MANAGEMENT SYSTEM

One important question is, when did humans begin to engage in environmental management in the current sense of this term? From a modern point of view, environmental management is the science of the rational and balanced use of natural resources; it is the involvement of territorial complexes of the natural environment and their resources in the process of social production, culture, and recreation, as well as their rational and balanced use, protection, restoration, and transformation [ 9 ].

It is believed that the history of mankind began from 3400–3300 B.C. with the advent of writing [ 10 ]. However, this is not entirely accurate, since even before that time, human society actively interacted with the environment [ 1 – 3 ]. Thus, a number of researchers connect the beginning of the history of mankind with the appearance of behavioral signs similar to the characteristics of modern people. The time frame is quite difficult to establish and is the subject of a dispute between scientists, ranging from 200 000 to 40 000 B.C. [ 11 , 12 ].

The most correct, in our opinion, is the neurobiological approach [ 13 ], according to which representatives of the genus Homo became behaviorally modern people with the acquisition of prefrontal synthesis (PFS), which is a conscious purposeful process of synthesizing new mental images. This date is defined as 42 000 B.C., i.e., coincides with the time of the appearance of works of art—images of figures of people and animals [ 14 , 15 ] (see Fig. 1 ). This important event in the history of mankind provided the grounds for American researcher V.V. Torvich [ 1 – 3 ] to single out the first group of resources during this period of time (consisting of similar types of resources), “new mental images,” which are very important for the development of human society.

An external file that holds a picture, illustration, etc.
Object name is 13541_2022_1110_Fig1_HTML.jpg

Block diagram of a comprehensive assessment of the ecological and economic balance of the territory. NP, natural protection of the territory; NRP, natural resource potential; AL, anthropogenic load; EES, ecological and economic state of the territory; and EEB, ecological and economic balance of the territory.

According to V.V. Torvich, “resources are tools, things, qualities, and methods that can be used to achieve human goals” [ 2 , p. 48]. In total, in the history of mankind, the author identified 26 groups of resources: from new mental images to artificial intelligence (AI).

The largest amount of new resources was mastered by humans during the Holocene period (11 700 B.C.) (see Fig. 1 ), when climatic conditions became most favorable for the development of human activity [ 1 – 3 ]. The cold climate on Earth has changed to a warmer one. The most dramatic warming occurred around 9700 B.C. Since this period, mankind has been able to successfully domesticate many plant and animal species (see Fig. 1 ), which has created unprecedented opportunities for various types of economic activities. A rapid increase in population began. In 2019 A.D., 7.6 billion people lived on Earth, which is 1 million times more than in 1000 B.C. [ 16 , 17 ], primarily due to the high rate of technological breakthroughs. Traditional nature management is increasingly becoming a thing of the past. New types of nature management have appeared, on the basis of which the industrial period (stage) in the development of human society started several centuries ago, gradually giving way to the postindustrial one. These periods are characterized by the fact that the social systems created in them increasingly depend not on the effect of influences, but on the consequences of the development of the systems themselves [ 18 – 21 ].

In connection with the threat of an ecological catastrophe, to which human society as a result of its economic activity (especially over the past decades) has come close, there is a need to revise the old approach and develop new ones that can stop destruction and death and ensure the further development of mankind. How does one see the further development of human society? V.V. Torvich [ 1 – 3 ] believes that humanity is subject to the so-called directed process and is moving towards an increase in the number of “great” opportunities for its development. This is confirmed by the increase in the number of various resources for development, which cannot always contribute to it and often lead to the degradation and death of all living things. As for the statement about the controllability of the process of emergence of new resources, technologies, tools, methods, etc., there is no evidence for this. It is only obvious that new resources expand the possibilities of influencing the environment [ 1 , 3 , 18 , 20 ].

Human society must adequately respond to various threats and challenges, and this is the main and only condition for its development and preservation. The creativity of people who make new resources is what determines the development of human society today. However, creativity must be controlled, humane, and not provide conditions for self-destruction and the death of mankind. The ever-increasing insatiability of the modern consumer society, which negatively affects the natural environment, is manifested in the uncontrolled development of the market for biotechnologies, genetic engineering, and nanotechnologies, which in the future can cause irreversible consequences—mutations and the emergence of new viruses and diseases, which can lead to the extinction of humans on Earth. In this case, we are talking about irresponsible scientific activity in modern civilization.

The alternative is the development of low-waste technologies, technoecopolises, agroecopolises, and green clusters, which can minimize the impact of by-products of technogenesis; technogenic accidents and disasters should be reduced by decreasing the energy intensity of the economy and creating autotrophic natural–anthropogenic ecosystems [ 19 – 23 ].

There are a number of prerequisites for the development of this direction, first and foremost, the growth of our knowledge and ideas about the structure and patterns of functioning of the biosphere, geo-eco-sociosystems, and the rapid development of green technological innovations that make the goal quite feasible. Today, a number of countries are developing low-waste industries and closed life support systems for outer-space, underground, underwater, and arctic purposes and sustainable green technologies and concepts. Cities of the future, from the point of view of the principle of autotrophy, are considered practically closed geosystems with a predominance of the eco-urban structure [ 24 , 25 ].

According to experts [ 26 ], environmentally compatible technologies must correspond to the natural features and patterns of the Earth’s territory, cause no harm to nature, and be in harmony with it.

In recent years, as part of environmentally compatible technologies that are used on living organisms or in contact with them, nanotechnology products, hybrid and bionic devices, and biorobotic systems [ 26 , 27 ] stand out; their environmental consequences are difficult to imagine or predict.

Environmentally compatible technologies include alternative energy—nontraditional ways of obtaining, transmitting, and using energy. Alternative energy sources are understood as renewable natural resources: water, sunlight, wind, biofuels, etc. However, the replacement of oil, gas, coal, and wood combustion technologies with alternative energy does not exclude its negative impact on the natural environment. This can be a serious reason for revising the prospects for its further development.

MODERN DIRECTIONS OF THE DEVELOPMENT OF EFFICIENT NATURE MANAGEMENT

Modern environmental management is determined by three main indicators [ 1 , 2 , 5 ]: (1) the balance between the production (profit-generating) and environmental (green) sectors of the economy, (2) the creative activity of the population in two directions: national (to work for the state) and individual (to ensure their livelihoods), and (3) the balance between real and monetary efficiency of production.

As was shown by our calculations [ 20 ], for the regions of Russia and the world, a balanced and harmonious ratio of the main indicators of nature management is created when their ratio is 1.0–1.5:

1 < (PGS/GES) < 1.5, where POS is a profit-generating sector and GES is a green economic sector;

1 < (NCAP/ICAP) < 1.5, where NCAP is the nationwide creative activity of the population and ICAP is the individual creative activity of the population;

1 < (REP/MEP) < 1.5, where REP is the real efficiency of production and MEP is the monetary efficiency of production.

For example, the profit received from production activities provides a balance between the sphere of production and services, as well as the quality of the natural environment with its constant improvement [ 5 ].

If the values in the considered ratios exceed 1.5, then this indicates economic and environmental problems (a decline in production, a rapid depreciation of assets, pollution and degradation of the natural environment, etc.), which manifests itself in the form of economic, financial, and other crises that are cyclical. Thus, an increase in environmental safety and sustainability of development is seen only in a balanced approach and harmony between competing interests.

Increasing the efficiency of nature management, both from an economic and environmental point of view, is likely an insufficient measure, but it postpones the onset of a global environmental catastrophe for a certain period [ 18 – 21 ]. Therefore, effective environmental management can be considered with full confidence as a new “resource package” for the development of mankind, when the value of the results of this social and production activity exceeds the value of the natural resources consumed in this case.

The current crisis in the models of nature management is also due to problems in the environmental policy of Russia and other countries. The concept of the New Environmental Policy (NEP) of environmental expert A.I. Kalachev [ 28 ] deserves close attention, placing the following emphasis:

(i) The state is the main beneficiary of solving the problems of environmental protection and nature management.

(ii) Human-centeredness: the state is a partner for business and citizens in solving problems, and the main customer of environmental services.

(iii) There is a guideline for solving environmental problems that reasonably depend on the existing shortcomings of nature management models.

Understanding the threats looming over society (environmental disasters, pandemics, and economic crises) is a global challenge for fundamental science—the need to develop a new containment methodology (noospheric convergence) and create modern production, management, social, educational and other technologies on its basis [ 19 ].

It is urgent to achieve an ecological and economic balance on Earth based on the noospheric concept, efficient nature management, and the principles of sustainable development (see Fig. 1 ). The world, according to the capitalist model of society and based on Adam Smith’s idea of economic growth, gradually ceases to be attractive and loses its relevance [ 18 – 21 ].

The noospheric approach is the basis of the modern development of human society. It is a global concept aimed at a gradual transition to autotrophy, strategic initiatives and planning, a new environmental policy, the development of local communities (civil society), and the maximum conservation of natural landscapes and ecosystems. It can be viewed as a kind of convergence at the intersection of technological innovations, as well as economics, ecology, education, which will bring human society to a fundamentally new level of development [ 19 ].

Undoubtedly, the creation of the noosphere as an area of interaction between nature and society is associated with the emergence and formation in the biosphere of the Earth of the bearer of consciousness (mind)—humanity. Hence, consciousness is the basis of the noosphere. Its state completely depends on the adequacy of the reflection by the consciousness of humanity of the relationship between it and nature [ 25 – 27 ].

In modern realities, consciousness and its manifestations are, to a large extent, spontaneous and destructive for the biosphere and the geographical sphere as a whole. Obviously, this situation will continue until our consciousness is freed from the idea of anthropocentrism and humanity learns to adhere to objective natural laws and subordinate its needs to them.

The level of responsible consumption of natural resources in the sphere of production, aimed at meeting human needs, is determined by the culture of nature management [ 18 , 19 ]. As a scientific direction, it studies the principles of rational use of natural resources, including the factors of anthropogenic and technogenic impacts on nature and their consequences for the population. The culture of nature management not only contributes to the consolidation of the necessary rules and norms, but also acts as a binding force for a system of restrictions and prohibitions for humans in the processes of nature management and the regulation of economic activity taking into account the sustainability of natural systems.

The culture of nature management is a membrane through which human interaction with nature takes place. Its most important direction, as we noted above, is the development of the mental qualities of the individual, primarily spirituality and harmony.

To balance the processes of nature management, it is extremely necessary to change consumer stereotypes; increase the number of green technologies and industries; develop environmental education, medical and environmental tourism, i.e.; reorient people from environmental–consumerism to social–spiritual in accordance with the Code of the Culture of Nature Management [ 18 , 19 ], which consists of two sections that have specific postulates.

The first section considers the limits of human adaptation to nature, namely the following postulates:

(i) Nature is the natural source of human vitality; we cannot be allowed to deplete it or needlessly waste it.

(ii) Man-made quasi-natural developments may conceal unknown, untested dangers; therefore, before offering innovations, constantly confirmed boundaries for their safe use should be indicated.

(iii) We cannot change natural conditions without taking into account even the smallest negative consequences, because they can cause unpredictable natural and man-made disasters.

(iv) Nature must be constantly taken care of by restoring its potential, and this restoration requires the same efforts and costs as are necessary for the extraction and consumption of natural resources.

(v) Humans are children of nature, and their increasing power should not be directed to its oppression, but to ensuring the creation of mutually beneficial and mutually enriching technologies for nature management.

The second section discusses the limits of nature’s adaptation to man, expressed in certain rules and prohibitions:

(i) One must not destroy nature; mankind has become powerful and capable of causing irreparable harm.

(ii) It is necessary to limit and control the level of scientific and technical progress in terms of possible damage to nature.

(iii) Natural resources cannot be used for excessive personal enrichment; they should be distributed in proportion to ability and labor.

(iv) One cannot build a relationship with nature built on half-truths: introducing even a small lie hidden underneath a grain of truth into the technologies of nature management will destroy nature over time and bring great misfortune.

(v) One cannot use natural wealth for excesses, praise, and out of envy for others, and the acquisition of the gifts of nature should be conditioned by the need for their consumption.

The culture of nature management, according to the Code of the Culture of Nature Management, is becoming the most important mechanism for achieving effective nature management, and we have to admit that other mechanisms are secondary and, without taking into account its requirements, lead to the destruction of the natural environment.

CONCLUSIONS

The development of human society and related nature management during the Holocene period (11 700 years) is characterized by an ever-expanding use of natural resources and the rapid emergence of new resources (genetic engineering and nanotechnologies), which has led to unprecedented pressure on the natural environment and put the world on the brink of ecological disaster.

It should be noted that the current environmental crisis is perhaps the deepest in the periods of modern and recent history, and it is global in nature. Today, there is no single scientifically based approach to overcoming the ecological crisis, and there is no universal trajectory for the development of human society. Existing standards, regulations, and calls for the formation of a green economy and green technologies and cities for the environmental protection of the economy and regulations only temporarily postpone the onset of regional crises and a global environmental catastrophe [ 27 , 29 – 31 ].

Obviously, in the 2000s, ecology, the rational use of natural resources, and environmental protection are becoming the leading force in the development of society. Nondecreasing emissions of ecopollutants, pseudoscientific concepts of energy supply, and gray technologies lead to local and regional environmental and economic crises and regional and global drops in the GDP. The scenarios of A. Peccei and A. King [ 32 ], according to which the global economic growth was supposed to stop in 2020, was justified to some extent, given the coronavirus pandemic.

The existing system of global consumer nature management leads to the fact that the main goal of society is stagnation and survival, rather than development and coevolution with nature. Understanding the threat of the COVID-19 pandemic looming over human society, global climate change poses a challenge to science, primarily geoecology and nature management, environmental resource science, etc., of enormous socioeconomic significance, as well as the further development of new concepts and models: the Ecopolitics of Containment and the New Environmental Policy. It is necessary to integrate the economic determinism of nature management and the ecological and economic imperative of the sustainable development of countries and regions based on the noospheric approach in the territory–resources–population–economy–ecology system.

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest.

Translated by S. Avodkova

Contributor Information

B. I. Kochurov, Email: ur.liam@nizagamnotremac .

V. V. Chernaya, Email: moc.liamg@11912791ynomrah .

R. M. Voronin, Email: ur.liam@ninorovmr .

  • Bibliography
  • More Referencing guides Blog Automated transliteration Relevant bibliographies by topics
  • Automated transliteration
  • Relevant bibliographies by topics
  • Referencing guides

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

  • Knowledge Base
  • How to Write a Thesis Statement | 4 Steps & Examples

How to Write a Thesis Statement | 4 Steps & Examples

Published on January 11, 2019 by Shona McCombes . Revised on August 15, 2023 by Eoghan Ryan.

A thesis statement is a sentence that sums up the central point of your paper or essay . It usually comes near the end of your introduction .

Your thesis will look a bit different depending on the type of essay you’re writing. But the thesis statement should always clearly state the main idea you want to get across. Everything else in your essay should relate back to this idea.

You can write your thesis statement by following four simple steps:

  • Start with a question
  • Write your initial answer
  • Develop your answer
  • Refine your thesis statement

Instantly correct all language mistakes in your text

Upload your document to correct all your mistakes in minutes

upload-your-document-ai-proofreader

Table of contents

What is a thesis statement, placement of the thesis statement, step 1: start with a question, step 2: write your initial answer, step 3: develop your answer, step 4: refine your thesis statement, types of thesis statements, other interesting articles, frequently asked questions about thesis statements.

A thesis statement summarizes the central points of your essay. It is a signpost telling the reader what the essay will argue and why.

The best thesis statements are:

  • Concise: A good thesis statement is short and sweet—don’t use more words than necessary. State your point clearly and directly in one or two sentences.
  • Contentious: Your thesis shouldn’t be a simple statement of fact that everyone already knows. A good thesis statement is a claim that requires further evidence or analysis to back it up.
  • Coherent: Everything mentioned in your thesis statement must be supported and explained in the rest of your paper.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

The thesis statement generally appears at the end of your essay introduction or research paper introduction .

The spread of the internet has had a world-changing effect, not least on the world of education. The use of the internet in academic contexts and among young people more generally is hotly debated. For many who did not grow up with this technology, its effects seem alarming and potentially harmful. This concern, while understandable, is misguided. The negatives of internet use are outweighed by its many benefits for education: the internet facilitates easier access to information, exposure to different perspectives, and a flexible learning environment for both students and teachers.

You should come up with an initial thesis, sometimes called a working thesis , early in the writing process . As soon as you’ve decided on your essay topic , you need to work out what you want to say about it—a clear thesis will give your essay direction and structure.

You might already have a question in your assignment, but if not, try to come up with your own. What would you like to find out or decide about your topic?

For example, you might ask:

After some initial research, you can formulate a tentative answer to this question. At this stage it can be simple, and it should guide the research process and writing process .

Now you need to consider why this is your answer and how you will convince your reader to agree with you. As you read more about your topic and begin writing, your answer should get more detailed.

In your essay about the internet and education, the thesis states your position and sketches out the key arguments you’ll use to support it.

The negatives of internet use are outweighed by its many benefits for education because it facilitates easier access to information.

In your essay about braille, the thesis statement summarizes the key historical development that you’ll explain.

The invention of braille in the 19th century transformed the lives of blind people, allowing them to participate more actively in public life.

A strong thesis statement should tell the reader:

  • Why you hold this position
  • What they’ll learn from your essay
  • The key points of your argument or narrative

The final thesis statement doesn’t just state your position, but summarizes your overall argument or the entire topic you’re going to explain. To strengthen a weak thesis statement, it can help to consider the broader context of your topic.

These examples are more specific and show that you’ll explore your topic in depth.

Your thesis statement should match the goals of your essay, which vary depending on the type of essay you’re writing:

  • In an argumentative essay , your thesis statement should take a strong position. Your aim in the essay is to convince your reader of this thesis based on evidence and logical reasoning.
  • In an expository essay , you’ll aim to explain the facts of a topic or process. Your thesis statement doesn’t have to include a strong opinion in this case, but it should clearly state the central point you want to make, and mention the key elements you’ll explain.

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

  • Ad hominem fallacy
  • Post hoc fallacy
  • Appeal to authority fallacy
  • False cause fallacy
  • Sunk cost fallacy

College essays

  • Choosing Essay Topic
  • Write a College Essay
  • Write a Diversity Essay
  • College Essay Format & Structure
  • Comparing and Contrasting in an Essay

 (AI) Tools

  • Grammar Checker
  • Paraphrasing Tool
  • Text Summarizer
  • AI Detector
  • Plagiarism Checker
  • Citation Generator

A thesis statement is a sentence that sums up the central point of your paper or essay . Everything else you write should relate to this key idea.

The thesis statement is essential in any academic essay or research paper for two main reasons:

  • It gives your writing direction and focus.
  • It gives the reader a concise summary of your main point.

Without a clear thesis statement, an essay can end up rambling and unfocused, leaving your reader unsure of exactly what you want to say.

Follow these four steps to come up with a thesis statement :

  • Ask a question about your topic .
  • Write your initial answer.
  • Develop your answer by including reasons.
  • Refine your answer, adding more detail and nuance.

The thesis statement should be placed at the end of your essay introduction .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, August 15). How to Write a Thesis Statement | 4 Steps & Examples. Scribbr. Retrieved August 26, 2024, from https://www.scribbr.com/academic-essay/thesis-statement/

Is this article helpful?

Shona McCombes

Shona McCombes

Other students also liked, how to write an essay introduction | 4 steps & examples, how to write topic sentences | 4 steps, examples & purpose, academic paragraph structure | step-by-step guide & examples, what is your plagiarism score.

An aerial view of University of Idaho's Moscow campus.

Virtual Tour

Experience University of Idaho with a virtual tour. Explore now

  • Discover a Career
  • Find a Major
  • Experience U of I Life

More Resources

  • Admitted Students
  • International Students

Take Action

  • Find Financial Aid
  • View Deadlines
  • Find Your Rep

Two students ride down Greek Row in the fall, amid changing leaves.

Helping to ensure U of I is a safe and engaging place for students to learn and be successful. Read about Title IX.

Get Involved

  • Clubs & Volunteer Opportunities
  • Recreation and Wellbeing
  • Student Government
  • Student Sustainability Cooperative
  • Academic Assistance
  • Safety & Security
  • Career Services
  • Health & Wellness Services
  • Register for Classes
  • Dates & Deadlines
  • Financial Aid
  • Sustainable Solutions
  • U of I Library

A mother and son stand on the practice field of the P1FCU-Kibbie Activity Center.

  • Upcoming Events

Review the events calendar.

Stay Connected

  • Vandal Family Newsletter
  • Here We Have Idaho Magazine
  • Living on Campus
  • Campus Safety
  • About Moscow

The homecoming fireworks

The largest Vandal Family reunion of the year. Check dates.

Benefits and Services

  • Vandal Voyagers Program
  • Vandal License Plate
  • Submit Class Notes
  • Make a Gift
  • View Events
  • Alumni Chapters
  • University Magazine
  • Alumni Newsletter

A student works at a computer

SlateConnect

U of I's web-based retention and advising tool provides an efficient way to guide and support students on their road to graduation. Login to SlateConnect.

Common Tools

  • Administrative Procedures Manual (APM)
  • Class Schedule
  • OIT Tech Support
  • Academic Dates & Deadlines
  • U of I Retirees Association
  • Faculty Senate
  • Staff Council

College of Natural Resources

CNR | Graduate Studies Office

Physical Address: 975 W. 6th Street Moscow, Idaho

Mailing Address: 875 Perimeter Drive MS 1142 Moscow, ID 83844-1142

Phone: 208-885-1505

Email: [email protected]

Final Project

Guidelines for ENVS 500 Research

For a thesis research project, please consult with your major professor on what deliverables are expected. In general, a thesis is a scholarly report involving primary data collection and analysis and is typically written for publication in a peer-reviewed scientific journal. A maximum of 10 credits of Research and Thesis (ENVS 500) can be counted toward the 30-credit requirement.

Guidelines for ENVS 599 Non-Thesis Research

Link to ENVS Project Opportunities Page

The non-thesis M.S. in Environmental Science requires a minimum of three credits of ENVS 599 Non-thesis Research. This is equivalent to 120 hours of work effort over 1-2 semesters. The Non-thesis Research project is intended to be a capstone experience where information and skills built during the student’s time at the University of Idaho are brought together in a synthesizing experience.

The Non-thesis experience can take two different forms. The first is a basic research paper where the student selects a topic to research, conducts a search of the literature, and obtains research materials to read and analyze. The student may, but is not required to, carry out laboratory, field work, or interviews to develop new data and information. The final deliverable is a research paper with all information properly cited. This type of capstone experience is appropriate when the student has a topic they would like to pursue in greater detail than their coursework allowed, where the student plans to continue on to graduate school or to a Ph.D., or when building research and writing skills is a priority. The second type of capstone experience is carrying out a hands-on project in the community. This type of thesis involves selecting a project, obtaining the required permissions, developing a budget and a funding source if needed, carrying out the project, documenting the steps in the project, and putting together a portfolio that shows the steps and the progress that was made.

Sometimes the entire paper/project can be carried out in a semester, and sometimes the project is a part of a larger, more long-term plan. In most cases, it is recommended that you complete your non-thesis capstone in the final two semesters of the program. During the first semester, you will work with your advisor to identify an appropriate major professor based on your paper/project topic. The two of you will work together to develop goals and objectives for your project, along with a timeline for completion. Write up your project plan in a brief proposal that includes context – why there is a need for the paper/project – and desired outcomes, and submit it to the Environmental Science Program. The second semester will be spent carrying out the steps of your project plan – e.g., research, data collection and review - and developing your final report.

Topic and Scope

The topic you choose should help you build skills related to your career goals. If you are a working professional in a related field, one option is to align your project with activities at work. Another option is to choose a topic you learned about in a class or through personal experience and would like to explore further.

ENVS projects vary widely, incorporating quantitative, qualitative, or mixed methods approaches. For example, one student may conduct a feasibility study for the implementation and management of a recycling program, while another may be out in the field collecting soil samples for testing in a lab. The time and techniques required will depend on the individual nature of each project. You will need to work closely with your major professor to determine the scope of your particular project.

In both cases, the student is responsible for the following deliverables, each of which is shared with the major professor:

  • Developing a topic for approval by the major professor
  • Creating a timeline for progress and deliverables
  • A paper/project proposal developed in consultation with the major professor
  • An early deliverable should be an outline including research materials consulted to date
  • (if a research paper is selected) or a progress report (if a project is selected)
  • At least one draft of the final deliverable whether paper or portfolio (feedback will be given by the supervising faculty member on drafts)
  • A final version of the final deliverable

It is the student’s responsibility to both develop the timeline and to share information and gather feedback from the major professor. Part of the experience involves managing the project; time management, including getting deliverables in on time, is the responsibility of the student.

For research papers, the evaluation includes the quantity and quality of the research materials consulted, the depth of the analysis carried out, and the style demonstrated by the quality of the written paper. Good graduate papers are generally around 30-40 pages with at least 15-25 references cited, including more than webpages. Good reference materials include books and articles from the scholarly literature along with materials found on the web and in magazines. For projects, evaluation includes the appropriateness of the project to a degree in environmental science, the scope of the project, time spent carrying out the project, the success of the project and impact on the community, and the quality of the portfolio.

  • ENVS 599 Guidelines pdf
  • Arndt: Defining and Implementing a Socially Sustainable Tourism Certification System in Costa Rica pdf
  • Turner: An Analysis of Four Common Stream Restoration Techniques within the Chesapeake Bay Watershed pdf
  • Show search

The Nature Conservancy Provides Heartlands Update to Community

TNC is continuing to lay groundwork for local management and governance of the Heartlands.

August 21, 2024 | Copper Harbor, MI

Aerial view of a lake surrounded by dense forest. The leaves display fall colors of red, orange and gold.

Media Contacts

Ryan Hermes TNC Phone: 517-999-7745 Email: [email protected]

On Wednesday, Aug. 21, The Nature Conservancy in Michigan (TNC) held a Keweenaw Heartlands Project update to bring the public up to speed on the latest with the project. TNC was joined by representatives from the Michigan Department of Natural Resources (MDNR) at the meeting.

“I appreciate everyone who came out to hear the latest update on the Keweenaw Heartlands project and for your thoughtful and candid questions,” said Julia Petersen, Keweenaw Heartlands project manager for The Nature Conservancy in Michigan. “We have been working closely with the community since our last update to lay the foundation for local management and governance of the Heartlands and we look forward to continuing that work into 2025.”

TNC provided updates on the development of a local governance entity while MDNR provided an update on its plans to purchase just over 10,000 acres of the Heartlands.

“We’re looking forward to meeting with the public and sharing information about the general management plan process for the portion of the Keweenaw Heartlands the DNR will eventually be purchasing,” said Tori Irving, Upper Peninsula Field Analyst for the Michigan Department of Natural Resources. “Your input on our plans is a critical next step in this process and we look forward to connecting with the community to learn and hear their thoughts.”

The land the DNR plans on purchasing is adjacent to the Fort Wilkins Historic State Park and will allow the State of Michigan to expand on a host of outdoor recreation offerings at the tip of the Keweenaw.

The public update meeting was the first in a series of Heart the Heartlands events offered as summer turns to fall. The update is followed by a hike, open to the public, on Thursday, Aug. 22, from 3-6 p.m. The hike will take attendees up to the Helmut & Candis Stern Preserve at Mt. Baldy . The hike up Mt. Baldy, co-hosted by the Keweenaw Hiking Trails Association. A second hike, Saturday, Aug. 24, from 10:00 a.m. to 1:00 p.m. will take hikers from forest to the rocky shoreline of TNC’s Mary MacDonald Preserve at Horseshoe Harbor .

The Nature Conservancy (TNC) purchased the Keweenaw Heartlands, which includes more than 32,000 acres of land, in two separate sales, one closing in late October 2022 and the second just before Christmas 2022. 

While in TNC ownership, the land remains open to the public under the Michigan Commercial Forest Program and on community tax rolls. TNC, as the temporary owner before these lands are in public ownership, is working closely with the region’s communities to plan for the future of the Heartlands and ensure long-term protection of this forest wildlife and people.

You can find more information about our “Heart the Heartlands” series and view upcoming events on our event poster , or learn more about the Keweenaw Heartlands project .

The Nature Conservancy is a global conservation organization dedicated to conserving the lands and waters on which all life depends. Guided by science, we create innovative, on-the-ground solutions to our world’s toughest challenges so that nature and people can thrive together. We are tackling climate change, conserving lands, waters and oceans at an unprecedented scale, providing food and water sustainably and helping make cities more sustainable. The Nature Conservancy is working to make a lasting difference around the world in 77 countries and territories (41 by direct conservation impact and 36 through partners) through a collaborative approach that engages local communities, governments, the private sector, and other partners. To learn more, visit nature.org or follow @nature_press on X.

  • News, Stories & Speeches
  • Get Involved
  • Structure and leadership
  • Committee of Permanent Representatives
  • UN Environment Assembly
  • Funding and partnerships
  • Policies and strategies
  • Evaluation Office
  • Secretariats and Conventions
  • Asia and the Pacific
  • Latin America and the Caribbean
  • New York Office
  • North America
  • Climate action
  • Nature action
  • Chemicals and pollution action
  • Digital Transformations
  • Disasters and conflicts
  • Environment under review
  • Environmental law and governance
  • Extractives
  • Fresh Water
  • Green economy
  • Ocean, seas and coasts
  • Resource efficiency
  • Sustainable Development Goals
  • Youth, education and environment
  • Publications & data

thesis nature management

Mid-term Status on SDG 6 Indicators: 6.3.2, 6.5.1, & 6.6.1 (2024)

SDG 6 Indicator Report Cover

Water is vital to human and planetary health and the internationally agreed goals that back it, including the 2030 Agenda for Sustainable Development, the Kunming-Montreal Global Biodiversity Framework, the Sendai Framework and the Paris Agreement. Yet the triple planetary crisis – the crisis of climate change, nature and biodiversity loss and pollution and waste – is affecting the availability, distribution, quality and quantity of water.

Despite water being essential for human health, food security, energy supplies, sustaining cities, and ecosystems and on the front lines of the triple planetary crisis of climate change, biodiversity loss, and pollution, SDG 6 is alarmingly off-track. For most of the SDG 6 Indicators, the current rate of progress is not fast enough to close the gap before 2030. In some cases, progress is even relapsing. The new mid-term status reports for SDG 6 indicators: 6.3.2, 6.5.1, and 6.6.1 found that if the priorities under SDG 6 are to be achieved by 2030, action on these indicators needs to be accelerated four times faster. These priorities can be ensured if adequate investments are made towards institutions, infrastructure, information, and innovation, where concerted action and institutional coherence is required, and new ideas, tools, and solutions are developed that draw from existing knowledge and indigenous practices.

Working with partners within the framework of the UN-Water led  Integrated Monitoring Initiative for SDG 6 , UNEP officially launched reports, in August 2021, on the three SDG 6 indicators for which it is custodian. These indicator reports are:

  • SDG 6.3.2 – Progress on Ambient Water Quality with a special focus on Health
  • SDG 6.5.1 – Progress on the Implementation of Integrated Water Resources Management with special focus on Climate Change
  • SDG 6.6.1 – Progress on Water-related Ecosystems with a special focus on Biodiversity

A key underlying message from these reports is that existing efforts to protect and restore water-related ecosystems must be urgently scaled up and accelerated.

Progress Reports can also be found on UN-Water's SDG 6 Progress Reports page

  • Fresh water

thesis nature management

© 2024 UNEP Terms of Use Privacy   Report Project Concern Report Scam Contact Us

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • View all journals
  • Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • Open access
  • Published: 27 August 2024

Impact of pesticide use on wild bee distributions across the United States

  • Laura Melissa Guzman   ORCID: orcid.org/0000-0003-2198-9738 1 , 2 ,
  • Elizabeth Elle   ORCID: orcid.org/0000-0002-0371-600X 2 ,
  • Lora A. Morandin 3 ,
  • Neil S. Cobb 4 ,
  • Paige R. Chesshire 4 , 5 ,
  • Lindsie M. McCabe 6 ,
  • Alice Hughes   ORCID: orcid.org/0000-0002-0675-7552 7 ,
  • Michael Orr   ORCID: orcid.org/0000-0002-9096-3008 8 &
  • Leithen K. M’Gonigle   ORCID: orcid.org/0000-0002-6015-9748 2  

Nature Sustainability ( 2024 ) Cite this article

Metrics details

  • Agroecology
  • Macroecology

The decline of many wild bee species has major consequences for pollination in natural and agro-ecosystems. One hypothesized cause of the declines is pesticide use; neonicotinoids and pyrethroids in particular have been shown to have pernicious effects in laboratory and field experiments, and have been linked to population declines in a few focal species. We used aggregated museum records, ecological surveys and community science data from across the contiguous United States, including 178,589 unique observations from 1,081 bee species (33% of species with records in the United States) across six families, to model species occupancy from 1995 to 2015 with linked land use data. While there are numerous causes of bee declines, we discovered that the negative effects of pesticides are widespread; the increase in neonicotinoid and pyrethroid use is a major driver of changes in occupancy across hundreds of wild bee species. In some groups, high pesticide use contributes to a 43.3% decrease in the probability that a species occurs at a site. These results suggest that mechanisms that reduce pesticide use (such as integrative pest management) can potentially facilitate pollination conservation.

There are widespread reports of bee declines in Europe and North America, but the status of most species is poorly known 1 , 2 , 3 , 4 , 5 , 6 . Insect pollination, largely from wild and managed bees, benefits ~75% of crop species worldwide and 88% of flowering plant species 1 . Further, the majority of crop pollination is provided by wild pollinators worldwide, and wild pollinators can enhance yields regardless of managed bee abundances 7 , 8 . Overall, this suggests that the decline of wild pollinators will have strong detrimental effects on pollination services, with both economic and ecological consequences.

The major drivers of wild bee declines include climate change 5 , land use change and habitat loss 9 , disease and pathogens 10 , dietary stress, and pesticide use 9 , 11 . Many of these factors are primarily associated with agricultural intensification (Extended Data Fig. 1) 12 . First, agricultural intensification generally reduces the diversity of floral and nesting resources available 13 . This is particularly the case in crop monocultures that do not provide resources to pollinators, such as grain monocultures 14 . Second, agricultural intensification can increase the exposure of wild bees to combinations of pesticides 15 . Among these pesticides, two notable classes are neonicotinoids and pyrethroids. The usage of these compounds is widespread across the United States, with neonicotinoid usage having rapidly increased since their introduction in the mid-1990s (Supplementary Figs. 1–3) , while the usage of other classes of insecticides declined over the same time period (Extended Data Fig. 2) 16 . Evidence from both laboratory and field experiments has demonstrated that both types of pesticide are harmful to individual bees; thus, exposure to the high quantities typically used in agriculture could potentially cause population declines 17 , 18 , 19 . Neonicotinoids are a class of neuro-active insecticides that target the central nervous system 20 . They are either sprayed or applied as soil drenches or seed treatments. When used as a seed treatment, they are systemic, expressed throughout plant tissues including pollen and nectar. The effects of neonicotinoids are typically sublethal and chronic, and therefore difficult to detect under typical regulatory studies 21 . Because of their chronic and sublethal effects, the European Union banned neonicotinoids in 2018 (with a moratorium since 2013) 22 . Pyrethroids are synthetic, modified versions of pyrethrins and target the closure of voltage-gated sodium channels in axonal membranes of insects 23 . Lastly, many farmers, especially those with large acreages of crops that rely or benefit from animal pollination, use managed honeybees ( Apis mellifera ) for crop pollination. There is evidence that managed honeybees can negatively impact wild bees through competition for floral resources and disease transmission 24 .

While there are multiple avenues by which agricultural intensification might harm wild bee populations, identifying mechanistic pathways has been difficult. This is partly owing to large data gaps 25 , 26 , even in relatively well-sampled areas such as the United States. Similarly, lack of available data on historical application of different pesticides (both spatial and temporal) has hindered our ability to evaluate their full effects on communities. Indeed, most of the evidence that links pesticide use to bee declines comes from experimental or small-scale observational studies which may not reflect large-scale (for example, continent-wide) patterns. The majority of these studies were performed on a handful of species 27 (most notably the western honeybee Apis mellifera ) and therefore may not be representative of the many other wild bee species. However, recent studies from the United Kingdom have demonstrated that population-level extinction rates at a country level are associated with the use of neonicotinoid seed treatment 11 . Developing effective policies to protect wild bees requires understanding the causes of decline, and many of the purported causal factors are interlinked. Understanding the impacts of pesticides in relation to other potential drivers of decline is critical to sustainable management of ecosystems and food systems, and has important ecological and economic implications worldwide.

Here we address these challenges using one of the largest databases of bee records for the contiguous United States ever compiled; these were aggregated from museum specimens, surveys and community science observations 25 . The United States has the largest number of described bee species on the planet with 3,594 species (including Hawaii and Alaska) 26 , 17% of known species, and a large proportion of agriculture is intensive agriculture with recent land use change, making it an ideal place to understand the impacts of intensive agriculture on bee diversity. Our analysis included occurrence records for 1,081 bee species across the following families: 220 species from Andrenidae, 284 from Apidae (excluding Apis mellifera ), 69 from Colletidae, 221 from Halictidae, 278 from Megachilidae and 9 from Melittidae (Fig. 1d ). We combined multispecies occupancy models with tools of causal inference to estimate the effect of (1) pesticide use, (2) animal-pollinated agriculture (that is, agriculture that benefits from animal pollination) and (3) honeybee colonies on wild bee distributions across the contiguous United States. We did this via three types of multispecies occupancy model, each run independently on each bee family. We focused our analysis on crops that benefit from animal pollination because farms growing these may import honeybee colonies which may change their impacts on wild bees (Supplementary Fig. 4a vs b) . Further, we expect that crops that benefit from animal pollination can provide additional resources known to attract wild bees. Finally, our analysis focuses specifically on the effects of neonicotinoids and pyrethroids because these classes of insecticides are thought to be linked to declines of wild pollinators 1 , and increasing use of these compounds has increased risk to bees 16 .

figure 1

a , The distributions of pesticide use (2013–2015), modified from ref. 65 . Pesticide use was calculated by dividing the kg of compound used by the LD 50 (for honeybees), averaged over a 3-year period, summed across compounds and standardized to county area. b , Animal-pollinated agriculture (2008), modified from ref. 33 . The percent of the county that is animal pollinated removes the following crops: corn, wheat, rice, soybean, sorghum, barley and oat. Here we include all crops that would present a high exposure to pesticides for wild bees. c , Honeybee colonies (2012), modified from ref. 51 . The number of honeybee colonies comes from the Census of Agriculture of farms that sell more than US$1,000. Values for a – c are log transformed and scaled. d , Expected wild bee species richness. Wild bee expected richness was compiled from ref. 25 and divided by area of the county and log transformed (raw expected richness is presented in Supplementary Fig. 8) .

We analyse individual species’ occupancy trends through space and time using a multispecies framework. In these models, individual species’ effects are drawn from distributions whose parameters are informed by data from all species. We analyse by family to reduce the computational burden. In addition, different families analysed separately provide semi-independent validation and, furthermore, bee species’ responses may be taxonomically grouped. We combined Melittidae and Colletidae (the two smallest families) because Melittidae had too few species to model on its own. In total, we ran 15 multispecies occupancy models (5 family groups × 3 effects). We modelled occupancy across all of the counties that fall within a species geographic range for 7 time periods, each lasting 3 years, from 1995 to 2015. We terminated in 2015 because the USGS Pesticide National Synthesis Project does not provide data on seed-coated neonicotinoids beyond 2015 28 . We treated each of the 3 years within each time period as an opportunity for a potential visit by someone collecting bees. For each of these potential visits, we inferred species absences for a particular species at a site if another species within the same genus was observed at that site in that year 4 , 29 , 30 . We obtained data on pesticide use application for every county and every year from the USGS Pesticide National Synthesis Project 31 (Fig. 1a ). Because the application of neonicotinoids and pyrethroids are correlated across space and time, we aggregated all active compounds (for both neonicotinoids and pyrethroids), controlling for their toxicity by weighting each by its median lethal dose (LD 50 ) as measured on honey bees (from the US Environmental Protection Agency (EPA) ECOTOX Database 32 ). In doing this, we are implicitly assuming that the relative LD 50 of different pesticides for honey bees is representative of the relative LD 50 of those same pesticides for native bees, but we recognize that LD 50 s probably vary among wild bee species. We obtained honeybee colony data (the number of colonies per county across multiple years) from the National Agricultural Statistics Service (NASS) Census of Agriculture (Fig. 1c ). While this census ignores small farm operations by only tracking farms that sell more than US$1,000 per year, it includes most large honeybee operations. Finally, we obtained agricultural distribution data from the Crop Data Layer 33 (Fig. 1b ) and climatological data from CHELSA 34 . Because we modelled occupancy across space and time, estimated effects can be driven by changes in predictors across both space and time.

To select predictors for the occupancy models, we relied on structural causal model analysis, which uses directed acyclic graphs (DAGs). DAGs are a visual representation of the presumed relationships between predictor variables and can help identify potential controlling variables in the context of multiple regression 35 . In a DAG analysis, we first construct a diagram that includes all potential relationships between all potential predictor variables. This is done using previous knowledge about the system. For example, the amount of pesticide applied in a county probably depends on the amount of agriculture in that county. Next, we compared candidate DAGs using methods that leverage the statistical correlations among our predictor variables to arrive at a best DAG (Extended Data Fig. 1) . Once we settle on a DAG that both represents potential relationships between variables and is consistent with the data, we identify the minimal set of variables needed to estimate the effect of our predictor(s) of interest. This analysis allows us to block confounding paths using the ‘backdoor criterion’. Namely, we identify which variables can confound the effect of the predictor(s) of interest. The main result is to avoid overcontrolling by including mediator or collider variables. While including many variables in an analysis can increase the predictive ability of a model, it may not allow for inference on effect sizes of the predictor of interest. Instead, by carefully considering potential confounders, colliders and mediators, we determine which minimal set of variables is needed to correctly estimate effect size(s) of the predictor(s) of interest. These steps are conducted before a regression analysis. Once a predictor set is chosen, we run the multispecies occupancy models. While a full overview of DAG analysis is beyond the scope of this paper, these steps have been summarized for ecological approaches in ref. 36 , have been identified as crucial for robust inferences in occupancy models in ref. 37 and are explained in ref. 35 .

We found that the mean effect of pesticide on species occupancy across all families was negative (Fig. 2a ). This effect was strongest (95% Bayesian credible intervals do not overlap zero) for Andrenidae and Apidae, and Colletidae/Melittidae, and negative (but 95% Bayesian credible intervals overlap zero) for Halictidae and Megachilidae. For the different families, this translates into the following declines in mean occupancy probability (for a corresponding increase in pesticide use from zero to the maximum observed value in our dataset): 43.3% decline in Apidae, 28.9% in Andrenidae, 23% in Colletidae and Melittidae, 19% in Halictidae and 0.4% in Megachilidae (Fig. 3 ). These findings were qualitatively unchanged under multiple possible classifications of animal-pollinated agriculture. Namely, it did not matter whether we considered animal-pollinated agriculture those crops that (1) need pollination, (2) attract pollinators or (3) use managed pollinators (Extended Data Fig. 3a,d) . Similarly, our findings were robust to our chosen duration of the occupancy interval (Supplementary Fig. 5) and whether we modelled the neonicotinoids or pyrethroids together or separately (Extended Data Fig. 4) . When we aggregated these species-level effects within each genus, we found that effects varied by genus (Fig. 4a , and Supplementary Figs. 6a and 7a) , with estimated effects of pesticide ranging from a 54% decline to a 62% increase (for a corresponding increase in pesticide use from zero to the maximum observed value in our dataset; Extended Data Fig. 5 ). We found that the mean effect of animal-pollinated agriculture was positive after controlling for climate (via temperature and precipitation) for Andrenidae, Colletidae and Melittidae, and Megachilidae (Fig. 2b ), and had no effect for other groups. This effect was only consistent for Andrenidae; when we used a broader definition of animal-pollinated agriculture, credible intervals overlapped with zero for all other families (Extended Data Fig. 3b,e) . This effect also varied by genus (Fig. 4b , and Supplementary Figs. 6b and 7b) , with the estimated effect of animal-pollinated agriculture ranging from a 23.5% decline to a 401% increase for a corresponding increase in the percent animal-pollinated agriculture from zero to the maximum observed value in our dataset (Extended Data Fig. 6) . Finally, to quantify potential effects of honey bees (Fig. 2c , Model 3), we controlled for the distribution of animal-pollinated agriculture. The mean effect of honeybee colonies on wild bee occupancy was not distinguishable from zero for all groups (Fig. 2c ).

figure 2

a , Model 1. The mean effect size for pesticide use is strongly negative across five families. b , Model 2. The mean effect size of animal-pollinated agriculture is largely positive. c , Model 3. The mean effect size of honey bees is mixed across families. Asterisks mean that the 95% credible interval does not overlap with zero and error bars represent 95% Bayesian credible intervals. Sample sizes vary for each family but are the same for each model (Extended Data Table 1 ). Photos obtained from iNaturalist taken by Sam Droege under a CC-0 license. In order: Megachile fortis , Agapostemon angelicus , Colletes willistoni , Bombus griseocollis , Andrena polemonii . The family Apidae excludes Apis mellifera .

figure 3

The black lines represent the mean occupancy, the shaded grey lines are the 95% credible intervals. Occupancy probability was estimated using the posterior distribution of the mean intercept and mean slope effect estimated for pesticide use while keeping all other predictors at the mean value. Pesticide use was varied from the minimum to the maximum ever observed. Pesticide use is the combined sum of kg weighted by LD 50 and area, log transformed and scaled. Sample sizes vary for each family (Extended Data Table 1 ).

figure 4

a , Model 1. The mean effect of pesticide use is strongly negative across most genera. b , Model 2. The mean effect of animal-pollinated agriculture is largely positive. c , Model 3. The mean effect of honey bees is mixed across genera. Points denote mean effects and bars 95% Bayesian credible intervals. Points and bars are coloured grey if the credible intervals overlap zero, blue if they do not overlap zero and the mean effect is positive, and orange if they do not overlap zero and the mean effect is negative. We present coefficients for all genera of bees in Supplementary Fig. 6 . Sample sizes vary for each family but are the same for each model (Extended Data Table 1 ).

Across the contiguous United States, we found that higher pesticide use resulted in lower occupancy of wild bees. Here, pesticides were aggregated across neonicotinoid and pyrethroid compounds, hence we interpret the pesticide use effect as a measure of pesticide intensity by county. The negative effect of pesticide use was consistent across all five families of bees and for three families, the credible intervals did not contain zero. We also found negative effects of pesticides for important crop pollinator groups. For example, we found that bumble bees (genus Bombus ) are negatively affected by pesticide use. Bumble bees are important pollinators of tomatoes, eggplants, peppers and melons, among other crops 38 . Similarly, the genus Andrena was negatively impacted by pesticide use, and bees in this group are important pollinators of apples and a wide variety of native plants.

Laboratory and field studies have demonstrated that realistic levels of exposure to some types of pesticide have negative effects on bees. These negative effects include impairment of navigation, reduced foraging success, reduced longevity and reductions in reproductive health, among others 1 . Some of these studies have been conducted across multiple countries 18 , 39 and provide a foundation for larger-scale future experiments. At country-wide scales, observational studies have demonstrated that these negative effects of pesticides do scale up to population-level trends 11 . Our study adds additional such evidence by documenting decreasing species occupancy across hundreds of species, a finding that is consistent with experimental studies that have evaluated landscape-level pesticide risk for bumble bees 39 . Further, we identify that certain groups, such as bumble bees, may be sensitive to pesticides, which could be driving stronger declines in those groups. This finding for bumble bees, in particular, is consistent with laboratory studies that have shown that they are particularly sensitive to some neonicotinoids such as acetamiprid and imidacloprid, and combinations of compounds such as clothianidin and propiconazole 27 , 40 , 41 .

Pesticide use had a greater impact on native bees than the presence of honeybee colonies or the type of agriculture (animal pollinated), where the effect of animal-pollinated agriculture was largely positive and the effect of honeybee colonies was indistinguishable from zero. However, we note that the honeybee data that we used in this study (the Census of Agriculture for honey-producing colonies) were coarse both spatially and temporally, and do not account for the transient nature of honeybee hives that results from their transportation around the continent during the growing season. Further, our quantification of honeybee colonies at a county level may be too coarse a spatial scale to enable detection of their full effects. The positive (but not significant) association between honey bees and some wild bees may be a consequence of beekeepers targeting areas that are also good for wild bees such as those with ample floral resources. We also note that we did not explicitly quantify the effects of habitat conversion. Land cover and pesticide intensity in our model vary across space and through time, and we do not differentiate between those types of variation, hence our estimate should not be interpreted as necessarily indicative of temporal trends only. While conversion of natural and semi-natural areas into urban or industrial areas also affects wild bees 42 , we found that such habitat conversion was only weakly correlated with pesticide use and the fraction of animal-pollinated agriculture. Despite the lack of data, we want to highlight that this study was only possible due to the collection, curation and release of pesticide use data by the USGS, as well as the large-scale mobilization of bee occurrence data. Extension of this approach to other parts of the world requires both spatially explicit pesticide application records, honeybee colony location data, crop usage data and new bee inventories, particularly in undersurveyed areas.

While the use of occupancy models on presence-only data is becoming more commonplace 2 , 3 , 5 , 6 , 29 , 43 , 44 , 45 , doing so requires making assumptions about how the data have been collected. In our case, we assumed that detection of some species provides information about the detection probability, and thus potential presence of other species (namely, those in the same genus). While this assumption may not always be valid (particularly when observers are only collecting a single species), recent studies have found that occupancy models are fairly robust to the inclusion of incomplete checklists 46 and yield unbiased results as long as a minimum of ~50% of the collection events target multiple species 30 . Model caveats aside, there are no obvious mechanisms that would cause our use of presence-only data to generate statistical correlations between bee occupancy and pesticide application. Throughout the text, we have used the word ‘driver’ to link pesticides to changes in bee occupancy. We have used the strongest methods available to justify the use of such a term. However, the results of our models depend on the causal assumptions we made using the DAGs and, while our data were consistent with our DAGs, other hypotheses that include additional variables and/or links between variables might generate different outcomes.

Declining wild bee population health is troubling, particularly because wild bees are important pollinators of many crops and are essential to maintaining stability of our ecosystems in the United States. Our findings suggest that pesticide use may lower wild bee occupancy. These trends do not necessarily reflect population-level trends, particularly because changes in occupancy do not necessarily capture changes in abundance. Nevertheless, changes in occupancy only occur when a particular species either colonizes a previously vacant site or is extirpated at a site. Thus, declines in occupancy should cause concern, as the underlying patterns in abundance required to generate changes in occupancy are probably even more concerning. Analysing abundance patterns (not possible with available data) may reveal more troubling or wider-spread declines. Due to their high importance in agricultural settings and in pollinating native plants, identifying strategies that protect wild bees is necessary to ensure that these populations in the United States survive into the future. Techniques that enhance integrated pest and pollinator management (IPPM) 47 , which aims to co-manage both pests and pollinators, can help minimize trade-offs of pest control and pollination services. For example, increasing habitat via hedgerows has been shown to be a cost-effective method to increase pest control and pollination services 48 .

Bee records

We acquired North American occurrence records comprising six bee families (Andrenidae, Apidae, Colletidae, Halictidae, Megachilidae and Melittidae) from ref. 25 . In ref. 25 , records were downloaded from the Global Biodiversity Information Facility and Symbiota Collections of Arthropods Network, and were cleaned to ensure that (1) taxonomic names are correct and (2) erroneous records are removed. Further, ref. 25 removed records for the western honeybee ( Apis mellifera ) and restricted records to only those within the contiguous United States. Ref. 25 presented a total number of 1,923,814 occurrence records for 3,158 bee species from 1700 to 2021 (Supplementary Fig. 8) . Of these, many are multiple observations of the same species on the same date at the same geographic location. Because the raw specimen data we used are presence-only records and because there is no measure of effort, the number of observations at a site is not a direct measure of abundance, hence treating it as such may not be appropriate. Further, because occupancy analyses use presence/absence data, rather than abundance, we reduced abundance measures to binary 0/1 (absence/presence). This resulted in a total of 634,597 unique species × date × location presence combinations (times and locations are explained below). Because our emphasis is on post-1990s pesticide application, we removed any observation from before 1994 or after 2016. Further, we removed any species that had less than 10 unique observations (unique dates and locations). We also removed species that were present in less than 3 years or 3 counties. We also removed all A. angelicus records and kept only A. texanus records because females cannot be morphologically differentiated between the two. Finally, our models only included genera for which we had data for at least three species, which resulted in a total of 1,081 bee species across the following families: Andrenidae 220 species, Apidae 284 species, Colletidae 69 species, Halictidae 221 species, Megachilidae 278 species and Melittidae 9 species.

Species ranges

For each species, we constructed plausible species ranges by identifying all counties that intersected a convex hull drawn around all observations of that species. This resulted in the plausible set of sites where that species may be found. While this may include counties where a species would probably not be found, subsetting to an approximate species range reduces the bias that might occur if one instead modelled every species at every site 4 , 30 .

Agriculture and land use change

We obtained land cover data from the National Land Cover Database (NLCD), which provides nationwide data on land cover at a 30 m 2 resolution for every 2–3 years from 2001 to 2016. The NLDC provides data for 16 land use categories. Of relevance to us is the category of ‘Cultivated crops’ (hereafter agriculture), which contains areas used for the production of annual crops such as corn, soybeans and vegetables, perennial woody crops (such as orchards and vineyards), and land actively tilled 49 . For each county, we calculated the proportion of the county covered in agriculture. While this database does not cover every year in our study, we interpolate the data within years. This is appropriate given that the amount of agricultural cover generally did not change appreciably within counties between 1995 and 2015.

With the NLCD, we also evaluated whether the loss of natural habitat was correlated with pesticide use or animal-pollinated agriculture. We defined as ‘Natural or semi-natural area’ the following land cover categories: Deciduous forest, Evergreen forest, Mixed forest, Woody wetlands, Emergent herbaceous wetlands, Shrub/Scrub, Grassland/Herbaceous, Sedge/Herbaceous and Pasture/Hay. We tested whether changes in natural or semi-natural areas were associated with the amount of pesticide use or agricultural cover. We found low correlations between the loss of natural areas and the amount of pesticide applied (between −0.157 and −0.206). Therefore, we do not consider further the effect of land use change as it relates to the effect of pesticide use or animal-pollinated agriculture.

Type of agriculture

We obtained crop cover data from the Crop Data Layer (CDL), which provides nationwide agricultural land cover data at a 30 m 2 resolution. Because the amount of agricultural cover did not change appreciably through time, we only used agricultural cover data from 2008 (the first year to cover all states) to quantify crop types for all years of the analyses. The CDL provides information on 137 types of cover 33 . For each crop category, we also divided crops into ‘Non-animal-pollinated agriculture (NAPA)’ and ‘Animal-pollinated agriculture (APA)’. We considered three ways to categorize animal and non-animal-pollinated agriculture. First, we divided crops depending on whether they require pollination (presented in the main text); second, we divided crops on the basis of whether they use managed pollinators; and third, we divided crops depending on whether they attract pollinators (even if they do not require pollinators). For crops that do not require pollination, we included the following crops: corn, wheat, rice, soybean, sorghum, barley and oat. All of the other types of crop were considered in the APA category. Second, we used the USDA ‘Attractiveness of Agricultural Crops to Pollinating Bees for the Collection of Nectar and/or Pollen, 2017’. Here we separated crops on the basis of whether they used managed pollinators. This is because even though a crop may require animal pollination, it may not be supplemented by managed pollinators. The crops included in the category of not using managed pollinators were: barley, dry beans, chickpeas, corn, cotton, eggplants, garlic, grapes, hops, lentils, lettuce, oats, olives, oranges, peas, pistachios, potatoes, rice, rye, sorghum, soybeans, sugarbeets, sugarcane, sweet potatoes, tobacco, triticale, vetch, walnuts, winter wheat, durum wheat, spring wheat, turnips, celery, mustard, citrus, pecans, millet and flaxseed. All other crops were considered to supplement pollination via managed pollinators (Extended Data Fig. 7c) . We also selected crops that do not necessarily require pollination but may attract pollinators and, therefore, expose wild bees to pesticides. In the ‘Non-attractive to pollinators agriculture’ category we included: barley, grapes, hops, lentils, oats, onions, pistachios, rice, rye, sugarcane, triticale, walnuts, winter wheat, durum wheat, spring wheat, pecans and millet. All other crops were considered to attract pollinators (Extended Data Fig. 7d) . These additional categorizations of ‘animal-pollinated agriculture’ did not result in substantially different model estimates (Extended Data Fig. 3) . For each county, we calculated the proportion of the county that is APA. Proportions were scaled and log transformed to ensure normality.

Pesticide use

We obtained pesticide use data from the USGS Pesticide National Synthesis Project, which provides national data on pesticide use for each county for every year from 1992 to 2021. The pesticide use data are provided as kg of active ingredient used in each county for 448 active ingredient types 31 . From these active ingredients, we considered neonicotinoids and pyrethroids because (1) they are known to be highly toxic to honey bees (via LD 50 measurements), (2) the usage of neonicotinoids increased during the study period, and the usage of pyrethroids remained constant, while the amount of kg used of other classes of insecticides decreased (Extended Data Fig. 2) and (3) because neonicotinoids and pyrethroids have been previously identified as problematic due to their increased toxicity when combined with fungicides 1 . Specifically, we included in our analyses the following neonicotinoids: acetamiprid, clothianidin, dinotefuran, imidacloprid, thiamethoxam and thiacloprid; and the following pyrethroids: cyfluthrin, cypermethrin, permethrin, tefluthrin, tralomethrin, fenvalerate, deltamethrin, cyhalothrin-gamma, resmethrin and fluvalinate-tau. Because pesticides vary by orders of magnitude in toxicity, we weight each chemical by its contact LD 50 , as measured on honey bees (following the procedure in ref. 50 ), before we sum chemicals together. While LD 50 measurements collected on honey bees may differ from LD 50 s for wild bees, such measurements for native bees generally do not exist. Further, we expect that LD 50 measured on honey bees should broadly reflect toxicity of different active ingredients for native bees. We acquired LD 50 estimates from the EPA ECOTOX Database 32 . For all results, we standardized the mean response to be in units of ng per bee, and we removed any LD 50 estimate that could not be standardized in this way. We only used LD 50 from studies that estimated acute toxicity (studies whose duration was less than 4 days) because they characterized most studies. We removed any study that did not report the duration. For each compound and using only contact exposure, we calculated the mean LD 50 across studies for each compound (Supplementary Table 1 ). We only used contact LD 50 because this was the most commonly tested across compounds. We set to zero each county × year × compound combination that did not have any pesticide application data. To calculate the total pesticide use, we summed the kg of pesticides used per year per county across LD 50 weighted compounds. We then divided the total amount of pesticide use by the area of the county to normalize for county size. Because we estimated occupancy at 3-year intervals (see below), we averaged 3 years of pesticide use for every county. To ensure the data were normally distributed, we log transformed the weighted sums and converted values into standard normal deviance to facilitate comparisons between different predictors. Because the application amounts of pyrethroids and neonicotinoids are highly correlated (correlation per year varies from between 0.30 when neonicotinoids were rarely applied in 1996 to 0.94 in 2008), we ran models where pesticides of both classes were combined or separated. Animal-pollinated agriculture was not highly correlated with pesticide use across all of the counties modelled (Supplementary Fig. 9)

Honeybee hives

The NASS produces surveys and reports in their Bee and Honey Program 51 . Since 2002, NASS has conducted the Census of Agriculture, which surveys any farm that reports revenue in excess of US$1,000. In this census, NASS collects information on the number of colonies, the number of farms, the amount of honey produced and the total sale of honey products. Thes data are available for the years 2002, 2007, 2012 and 2017. We divided the total number of colonies used by the area of the county to normalize for county size and then log transformed and scaled the data. Because these data lack seasonal information, they do not allow us to incorporate information about when the hives were actually present in farms.

Temperature and precipitation

We obtained climatic variables (both temperature and precipitation) from the CHELSA high-resolution climate data 34 . Through the CHELSA time series, we were able to obtain monthly precipitation and maximum temperature at 30 arc-seconds resolution (~1 km). To calculate the yearly maximum temperature for every county, we extracted the maximum temperatures for the entire year and averaged the values within each county. Of these, we selected the maximum value per year. To calculate total precipitation, we extracted the precipitation for every month of the year, and averaged it within each county and across every year. We averaged both maximum temperature and mean precipitation across the number of time visits in a time interval to ensure consistency in the sensitivity analysis. We then scaled temperature and precipitation across all counties and years.

Data processing

Because pesticide use data are reported at county level, we calculated every other environmental predictor at county level and report each county as a ‘site’. We applied occupancy-detection models to historical data using the approach of ref. 30 . This approach requires specifying time intervals over which to estimate occupancy, and sub-intervals over which to estimate detection. We used 3 years as the time interval to estimate occupancy, and 1 year as the time interval to estimate detection. As a result, we did not model seasonal and within-year variation in occupancy. Recent studies have shown that trends inferred by occupancy models are robust to the choice of closure period (that is, the time period at which occupancy is estimated) 45 and spatial grain 5 , 45 . We conducted a sensitivity analysis where we considered occupancy intervals from 2 to 5 years; results were qualitatively unchanged from those in the main text that use a 3-year interval (Supplementary Figs. 5 , 10 and 11) . We inferred that a visit to a site that might have detected a given species (for example, a potential of 0 or 1) occurred only when at least one other species in the same genus as that species was observed in the same year and county, and we only did this for sites that fall within that species’ range. Because of this, we excluded any species where there are fewer than three species in a genus. The application of occupancy models to presence-only data is a growing field 2 , 3 , 5 , 6 , 29 , 43 , 44 , 45 . These studies have successfully leveraged the assumption that the presence of another species can inform non-detections for related species. Occupancy models can be robust to the breaking of this assumption, depending on the underlying data. For example, ref. 46 showed that inferences from occupancy models are robust to the combination of complete and incomplete checklist data. Further, ref. 30 found that using occupancy models that inferred non-detections on the basis of other species’ presences performed relatively well when applied to datasets comprising as much as 50% of sampling events where a collector was only seeking a single species.

However, it remains to be shown how sensitive these methods are to the taxonomic scope over which inferences about non-detections are extrapolated. We inferred non-detections across species at the genus, subfamily or family level. When inferring non-detections at the family level, we found that genera that are harder to identify tended to show declining trends (results not shown); however, when we inferred non-detections at the genus level, trends were consistent with those reported by experts. Our approach implicitly assumes that search effort, collection, identification and digitization of a species are comparable for different species within the same genus. While this may not be the case individually across all species, our analysis does allow for some genera to be under-identified or underdigitized compared with other genera via the non-detection imputation. We modelled each bee family separately, except for Colletidae and Melittidae, which we modelled together due to their containing a lower number of species.

Because not all families were observed in every county, we only modelled county × time interval combinations that had the presence of a species from a given family. Consequently, we modelled Andrenidae in 626 counties, Apidae in 1,763 counties, Halictidae in 1,046 counties, Megachilidae in 970, and Colletidae and Melittidae in 500 counties (Extended Data Fig. 8) .

We matched the temporal scale of the occurrence data and all of the predictors. For pesticide use, temperature and precipitation, this process was fairly simple because all of these datasets were reported yearly. Therefore, we averaged them over the period over which we estimated occupancy (3 years in the main results and 2–5 years in the sensitivity analysis). For the number of honeybee colonies, we had to rely on the NASS census of agriculture data which are only available for the census years 2002, 2007, 2012 and 2017. Therefore, for the other periods, we interpolated values from the census year to any previous year for a given time period. For example, using 3-year time intervals, we had seven time periods (1995–1997, 1998–2000, 2001–2003, 2004–2006, 2007–2009, 2010–2012 and 2013–2015); the first 4 time intervals would use honeybee data from 2002, while interval 5 would use those from 2007, 6 would use those from 2012, and 7 would use those from 2017. We followed a similar process for the agricultural data from NLDC which is available from 2001 to 2016 at varying time intervals. The only predictor that we did not vary over time was animal-pollinated agriculture because this relied on the Crop Data Layer that was only available from 2008 onwards. Therefore, we treated this as a time-independent variable.

Causal analysis

To infer the causal effect of pesticide use, animal-pollinated agriculture and honeybee usage, we used DAGs to find the minimal set of adjustment variables, given each exposure set. First, we generated the DAG (Extended Data Fig. 1a) . We used the following logic when building the DAG: we assumed that (1) conversion to agriculture has decreased the amount of floral and nesting resources available to wild bees 52 , (2) the expansion of agricultural landscapes has led to an increase in insecticide use 53 , (3) animal-pollinated crops also require the supplementation of honey bees for pollination 54 , (4) the presence of honey bees can affect the amount of pesticide used because one of the mitigation strategies proposed by the EPA to reduce the risk of pesticide to honey bees is to encourage the reduction of pesticide use via Managed Pollinator Protection Plans 55 . Furthermore, the location of agriculture in the contiguous United States is largely informed by both climate and topographical and soil characteristics. Climate (both temperature and precipitation) also affects the availability of floral resources for bees. These relationships represent the initial DAGs we created (Supplementary Fig. 4a , b) .

Methods that help build a DAG use the statistical correlations among predictors to support inclusion or exclusion of potential links between variables. For example, in our data, we observed that climate variables are correlated with honeybee colony abundance, suggesting that a link should connect these two predictors. This correlation might arise because climate variables directly impact honeybee colonies or, alternatively, it could be a consequence of a third variable that mediates this effect (for example, climate might impact the types of crop that are grown, which could subsequently impact whether or not honey bees are imported). Indeed, we found that including animal-pollinated agriculture as a mediator between climate and honeybee colony abundance is supported. Construction of our DAG proceeded by using this type of logic to determine which connections should be drawn between all of our variables (Supplementary Fig. 4) . We then used our final DAG to identify the combinations of predictors needed to test our various hypotheses in our occupancy models. These models differed depending on which ‘exposure’ variable we were interested in (for example, pesticide vs animal-pollinated agriculture vs honeybee colonies). While we would ideally use DAG E in Supplementary Fig. 4 , we were not able to obtain floral resource data that are independent from agriculture (for example, ref. 5 estimated floral resources on the basis of the Crop Data Layer), hence we used DAG D. Fortunately, for the exposure variables we were interested in here, the final model for each remained the same whether we used DAG C, D or E.

We used the R packages dagitty 56 and ggdag 57 to evaluate the minimum adjustment variables to estimate the causal effect of (1) pesticide use, (2) animal-pollinated agriculture and (3) honey bees, on wild bee occupancy (Extended Data Fig. 1) . To estimate the effect of pesticide use, we included both animal-pollinated agriculture and honeybee surveys (Model 1: Extended Data Fig. 1b) ; for animal-pollinated agriculture, we only included climate in the model (Model 2: Extended Data Fig. 1c) ; and for honeybee usage, we only included animal-pollinated agriculture (Model 3: Extended Data Fig. 1d) .

Occupancy models

Occupancy models aim to estimate the occupancy, denoted ψ , of a given species i on a site j in an era k by accounting for imperfect detection. They do this by incorporating multiple visits to the same sites. We developed three multispecies occupancy models for bee occurrence records in the contiguous United States that estimate the effect of pesticides, animal pollinated agriculture or honey bees on species occupancy.

For all occupancy models developed here, the probability that a species i is detected at site j in era k is drawn from a Bernoulli distribution with probability p i j k z i j k ,

where p i j k is the detection probability and z i j k is the true (but unknown) occupancy state. If a site is occupied, then z i j k  = 1, and z i j k  = 0 otherwise. The true occupancy state is also drawn from a Bernoulli distribution with success probability ψ i j k .

Both occupancy probability, ψ , and detection probability, p , can be formulated as functions of covariates, and we did this in three different ways for ψ .

Specifically, we used the following models:

where the expit function is defined as:

Here, β 0 denotes mean occupancy, β species [ i ] denotes a species-specific random intercept, β area denotes a fixed effect of area on occupancy, to account for the fact that some counties are larger than others. β apa [ i ], β temp [ i ], β prec [ i ], β honeybee [ i ] and β pesticide [ i ] denote species-specific linear effects of animal-pollinated agricultural cover (apa), temperature, precipitation, honeybee colonies, and pesticide use. β temp2 [ i ] denotes a species-specific quadratic effect of temperature.

We assumed that species-specific slopes and intercepts are normally distributed about some mean. Specifically,

where μ β apa , μ β temp , μ β temp2 , μ β prec , μ β honeybee and μ β pesticide denote the mean effect of each corresponding predictor across species, and σ terms denote the variances about these means.

In all of the above models, we modelled detection probability as

where α 0 denotes the mean detection probability, α era denotes a slope of detection through time, α species denotes a species-specific random intercept of detection, and α site,era [ j , k ] denotes a site-specific random effect that is era specific. This latter term allows detection to vary relatively independently across sites and between eras. Specifically, we assumed

We fitted 15 occupancy models, each of the types of model presented above (1, 2 and 3) for all five families of bees.

We ran models in JAGS 58 and assessed model convergence both by visually inspecting chains and checking the Gelman–Rubin statistic (we ensured that \(\hat{R}\) was <1.1 for all parameters). We used flat, uninformative priors for all parameters and ran models for 100,000 iterations, with a burn-in of 1,000 iterations and thinning every 100 iterations across 3 chains, resulting in a total of 300 posterior samples. For all analyses, we used R (v.4.3.2) 59 . For spatial manipulations, we used the package sf (v.1.0-15) 60 ; for data manipulation and visualization, we used tidyverse (v.2.0.0) 61 and data.table (v.1.15.0) 62 ; and for running models, we used runjags (v.2.2.2-4) 63 .

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

North American occurrence records were acquired from ref. 25 . Land cover data were obtained from the National Land Cover Database (NLCD) 49 for all years from 2001 to 2016 ( https://www.mrlc.gov/data/nlcd-land-cover-conus-all-years ). Crop cover data were obtained from the Crop Data Layer (CDL) for 2008 ( https://www.nass.usda.gov/Research_and_Science/Cropland/Release/index.php ). Attractiveness of agricultural crops was obtained from the USDA ‘Attractiveness of Agricultural Crops to Pollinating Bees for the Collection of Nectar and/or Pollen, 2017’ report ( https://www.usda.gov/sites/default/files/documents/Attractiveness-of-Agriculture-Crops-to-Pollinating-Bees-Report-FINAL-Web-Version-Jan-3-2018.pdf ). Pesticide use data were obtained from USGS Pesticide National Synthesis Project ( https://water.usgs.gov/nawqa/pnsp/usage/maps/county-level/ ) for all years from 1995 to 2015. LD 50 estimates were acquired from the EPA ECOTOX Database 32 ( https://cfpub.epa.gov/ecotox/search.cfm ). Honeybee colony counts were obtained from The National Agricultural Statistics Service (NASS) honey colony census 51 for years 2002 to 2017 ( https://quickstats.nass.usda.gov ). Temperature and precipitation data were obtained from the CHELSA high-resolution climate data 34 ( https://chelsa-climate.org/timeseries/ ).

Code availability

All code needed to re-create figures and analysis can be found in GitHub at https://github.com/lmguzman/bee_occupancy.git , and is published in Zenodo at https://zenodo.org/doi/10.5281/zenodo.12668534 (ref. 64 ).

Goulson, D., Nicholls, E., Botías, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347 , 1255957 (2015).

Article   Google Scholar  

Powney, G. D. et al. Widespread losses of pollinating insects in Britain. Nat. Commun. 10 , 1018 (2019).

Graves, T. A. et al. Western bumble bee: declines in the continental United States and range-wide information gaps. Ecosphere 11 , e03141 (2020).

Guzman, L. M., Johnson, S. A., Mooers, A. O. & M’Gonigle, L. K. Using historical data to estimate bumble bee occurrence: variable trends across species provide little support for community-level declines. Biol. Conserv. 257 , 109141 (2021).

Jackson, H. M. et al. Climate change winners and losers among North American bumblebees. Biol. Lett. 18 , 20210551 (2022).

Janousek, W. M. et al. Recent and future declines of a historically widespread pollinator linked to climate, land cover, and pesticides. Proc. Natl Acad. Sci. USA 120 , e2211223120 (2023).

Article   CAS   Google Scholar  

Burkle, L. A., Marlin, J. C. & Knight, T. M. Plant–pollinator interactions over 120 years: loss of species, co-occurrence, and function. Science 339 , 1611–1615 (2013).

Garibaldi, L. A. et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339 , 1608–1611 (2013).

Winfree, R., Aguilar, R., Vázquez, D. P., LeBuhn, G. & Aizen, M. A. A meta-analysis of bees’ responses to anthropogenic disturbance. Ecology 90 , 2068–2076 (2009).

Cameron, S. A. et al. Patterns of widespread decline in North American bumble bees. Proc. Natl Acad. Sci. USA 108 , 662–667 (2011).

Woodcock, B. A. et al. Impacts of neonicotinoid use on long-term population changes in wild bees in England. Nat. Commun. 7 , 12459 (2016).

Connelly, H., Poveda, K. & Loeb, G. Landscape simplification decreases wild bee pollination services to strawberry. Agric. Ecosyst. Environ. 211 , 51–56 (2015).

Langlois, A., Jacquemart, A.-L. & Piqueray, J. Contribution of extensive farming practices to the supply of floral resources for pollinators. Insects 11 , 818 (2020).

Scheper, J. et al. Environmental factors driving the effectiveness of European agri-environmental measures in mitigating pollinator loss—a meta-analysis. Ecol. Lett. 16 , 912–920 (2013).

Krupke, C. H., Hunt, G. J., Eitzer, B. D., Andino, G. & Given, K. Multiple routes of pesticide exposure for honey bees living near agricultural fields. PLoS ONE 7 , e29268 (2012).

DiBartolomeis, M., Kegley, S., Mineau, P., Radford, R. & Klein, K. An assessment of acute insecticide toxicity loading (AITL) of chemical pesticides used on agricultural land in the United States. PLoS ONE 14 , e0220029 (2019).

Rundlöf, M. et al. Seed coating with a neonicotinoid insecticide negatively affects wild bees. Nature 521 , 77–80 (2015).

Woodcock, B. A. et al. Country-specific effects of neonicotinoid pesticides on honey bees and wild bees. Science 356 , 1393–1395 (2017).

Stuligross, C. & Williams, N. M. Past insecticide exposure reduces bee reproduction and population growth rate. Proc. Natl Acad. Sci. USA 118 , e2109909118 (2021).

Tomizawa, M. & Casida, J. E. Neonicotinoid insecticide toxicology: mechanisms of selective action. Annu. Rev. Pharmacol. Toxicol. 45 , 247–268 (2005).

Lu, C., Hung, Y.-T. & Cheng, Q. A review of sub-lethal neonicotinoid insecticides exposure and effects on pollinators. Curr. Pollut. Rep. 6 , 137–151 (2020).

Bee Health: EU Takes Additional Measures on Pesticides to Better Protect Europe’s Bees (European Commission, 2013).

Soderlund, D. M. in Hayes’ Handbook of Pesticide Toxicology 1665–1686 (Elsevier, 2010).

Wojcik, V. A., Morandin, L. A., Davies Adams, L. & Rourke, K. E. Floral resource competition between honey bees and wild bees: is there clear evidence and can we guide management and conservation? Environ. Entomol. 47 , 822–833 (2018).

Chesshire, P. R. et al. Completeness analysis for over 3000 United States bee species identifies persistent data gap. Ecography 2023 , e06584 (2023).

Orr, M. C. et al. Global patterns and drivers of bee distribution. Curr. Biol. 31 , 451–458 (2021).

Shahmohamadloo, R. S., Tissier, M. L. & Guzman, L. M. Risk assessments underestimate threat of pesticides to wild bees. Conserv. Lett . https://doi.org/10.1111/conl.13022 (2024).

Hitaj, C. et al. Sowing uncertainty: what we do and don’t know about the planting of pesticide-treated seed. BioScience 70 , 390–403 (2020).

Outhwaite, C. L. et al. Annual estimates of occupancy for bryophytes, lichens and invertebrates in the UK, 1970–2015. Sci. Data 6 , 259 (2019).

Shirey, V., Khelifa, R., M’Gonigle, L. K. & Guzman, L. M. Occupancy-detection models with museum specimen data: promise and pitfalls. Methods Ecol. Evol. 14 , 402–414 (2023).

Baker, N. T. & Stone, W. W. Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12 Technical report (US Geological Survey, 2015).

Olker, J. H. et al. The ECOTOXicology Knowledgebase: a curated database of ecologically relevant toxicity tests to support environmental research and risk assessment. Environ. Toxicol. Chem. 41 , 1520–1539 (2022).

Cropland Data Layer (USDA National Agricultural Statistics Service, 2008).

Karger, D. N. et al. Climatologies at high resolution for the earth’s land surface areas. Sci. Data 4 , 170122 (2017).

McElreath, R. Statistical Rethinking: A Bayesian Course with Examples in R and Stan 2nd edn (Chapman and Hall/CRC, 2018).

Arif, S. & MacNeil, M. A. Applying the structural causal model framework for observational causal inference in ecology. Ecol. Monogr. 93 , e1554 (2023).

Stewart, P. S., Stephens, P. A., Hill, R. A., Whittingham, M. J. & Dawson, W. Model selection in occupancy models: inference versus prediction. Ecology 104 , e3942 (2023).

Mader, E. et al. Managing Alternative Pollinators: A Handbook for Beekeepers, Growers, and Conservationist SARE Handbook 11, NRAES-186 (SARE, 2010).

Nicholson, C. C. et al. Pesticide use negatively affects bumble bees across European landscapes. Nature 628 , 355–358 (2024).

Cresswell, J. E. et al. Differential sensitivity of honey bees and bumble bees to a dietary insecticide (imidacloprid). Zoology 115 , 365–371 (2012).

Robinson, A. et al. Comparing bee species responses to chemical mixtures: common response patterns? PLoS ONE 12 , e0176289 (2017).

Prendergast, K. S., Dixon, K. W. & Bateman, P. W. A global review of determinants of native bee assemblages in urbanised landscapes. Insect Conserv. Divers. 15 , 385–405 (2022).

Kamp, J., Oppel, S., Heldbjerg, H., Nyegaard, T. & Donald, P. F. Unstructured citizen science data fail to detect long-term population declines of common birds in Denmark. Divers. Distrib. 22 , 1024–1035 (2016).

van Strien, A. J., van Swaay, C. A., van Strien-van Liempt, W. T., Poot, M. J. & WallisDeVries, M. F. Over a century of data reveal more than 80% decline in butterflies in the Netherlands. Biol. Conserv. 234 , 116–122 (2019).

Jönsson, G. M., Broad, G. R., Sumner, S. & Isaac, N. J. A century of social wasp occupancy trends from natural history collections: spatiotemporal resolutions have little effect on model performance. Insect Conserv. Divers. 14 , 543–555 (2021).

Johnston, A. et al. Analytical guidelines to increase the value of community science data: an example using eBird data to estimate species distributions. Divers. Distrib. 27 , 1265–1277 (2021).

Lundin, O., Rundlöf, M., Jonsson, M., Bommarco, R. & Williams, N. M. Integrated pest and pollinator management—expanding the concept. Front. Ecol. Environ. 19 , 283–291 (2021).

Morandin, L., Long, R. & Kremen, C. Pest control and pollination cost–benefit analysis of hedgerow restoration in a simplified agricultural landscape. J. Econ. Entomol. 109 , 1020–1027 (2016).

Homer, C. et al. Conterminous United States land cover change patterns 2001–2016 from the 2016 national land cover database. ISPRS J. Photogramm. Remote Sens. 162 , 184–199 (2020).

Li, Y., Miao, R. & Khanna, M. Neonicotinoids and decline in bird biodiversity in the United States. Nat. Sustain. 3 , 1027–1035 (2020).

Census of Agriculture (USDA National Agricultural Statistics Service, 2017).

Kline, O. & Joshi, N. K. Mitigating the effects of habitat loss on solitary bees in agricultural ecosystems. Agriculture 10 , 115 (2020).

Meehan, T. D., Werling, B. P., Landis, D. A. & Gratton, C. Agricultural landscape simplification and insecticide use in the Midwestern United States. Proc. Natl Acad. Sci. USA 108 , 11500–11505 (2011).

Reilly, J. et al. Crop production in the USA is frequently limited by a lack of pollinators. Proc. R. Soc. B 287 , 20200922 (2020).

Environmental Protection Agency’s Policy to Mitigate the Acute Risk to Bees from Pesticide Products (US Environmental Protection Agency Office of Pesticide Programs, 2017).

Textor, J., van der Zander, B., Gilthorpe, M. S., Liśkiewicz, M. & Ellison, G. T. Robust causal inference using directed acyclic graphs: the R package ’dagitty’. Int. J. Epidemiol. 45 , 1887–1894 (2016).

Google Scholar  

Barrett, M. ggdag: Analyze and Create Elegant Directed Acyclic Graphs. R package version 0.2.8 https://CRAN.R-project.org/package=ggdag (2023).

Plummer, M. JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. In Proc. 3rd International Workshop on Distributed Statistical Computing 1–10 (DSC, 2003).

R Core Team. R: A Language and Environment for Statistical Computing . https://www.R-project.org/ (R Foundation for Statistical Computing, 2021).

Bivand, R. S., Pebesma, E. & Gomez-Rubio, V. Applied Spatial Data Analysis with R 2nd edn (Springer, 2013).

Wickham, H. et al. Welcome to the tidyverse. J. Open Source Softw. 4 , 1686 (2019).

Dowle, M. & Srinivasan, A. data.table: Extension of ’data.frame’. R package version 1.14.0 https://CRAN.R-project.org/package=data.table (2021).

Denwood, M. J. runjags: an R package providing interface utilities, model templates, parallel computing methods and additional distributions for MCMC models in JAGS. J. Stat. Softw 71 , 1–25 (2016).

Guzman, L. M. Code for Guzman et al. 2024 Impact of pesticide use on wild bee distributions across the United States. Zenodo https://doi.org/10.5281/zenodo.12668534 (2024).

Wieben, C. M. Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2013–17 (ver. 2.0, May 2020) (US Geological Survey, 2020).

Download references

Acknowledgements

We thank M. Pennell for all the useful discussions throughout the development of this work; T. Griswold and K.-L. J. Hung for advice on the current trends of native bees, and L. Richardson for feedback on the pesticide use data; K. Parys and N. Steinhauer for information about honeybee data; all the data collectors, taxonomists and other contributors that made this study possible. This study required an enormous amount of data. We also thank the USGS Pesticide Use project, the NASS Agricultural Census project, and the USDA Crop Data Layer project, without whom we could not have had sufficient data on predictor variables. We acknowledge funding from Simon Fraser University and the Natural Sciences and Engineering Research Council of Canada (NSERC) (Discovery Grants to L.K.M. and E.E.), the Liber Ero Fellowship Program and the University of Southern California (L.M.G.), and the National Science Foundation DBI-2216927 (iDigBees).

Author information

Authors and affiliations.

Marine and Environmental Biology section at the Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA

Laura Melissa Guzman

Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada

Laura Melissa Guzman, Elizabeth Elle & Leithen K. M’Gonigle

Pollinator Partnership, San Francisco, CA, USA

Lora A. Morandin

Biodiversity Outreach Network, Flagstaff, AZ, USA

Neil S. Cobb & Paige R. Chesshire

Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA

Paige R. Chesshire

USDA-ARS Pollinating Insects Research Unit, Logan, UT, USA

Lindsie M. McCabe

School of Biological Sciences, University of Hong Kong, Hong Kong, Hong Kong

Alice Hughes

Entomologie, Staatliches Museum für Naturkunde Stuttgart, Stuttgart, Germany

Michael Orr

You can also search for this author in PubMed   Google Scholar

Contributions

L.M.G., L.K.M., E.E. and L.A.M. designed the study. N.S.C., P.R.C., L.M.M., A.H. and M.O. provided the cleaned bee occurrence data. L.M.G. completed all of the analyses with support from L.K.M. and feedback from all authors. L.M.G. wrote the initial draft of the paper and all others edited and provided feedback.

Corresponding author

Correspondence to Laura Melissa Guzman .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Sustainability thanks Ben Woodcock and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended data fig. 1 directed acyclic graphs..

Directed Acyclic Graphs (DAGS) allow us to determine the minimal set of covariates in order to estimate the effect of a given variable. DAGS provide a visual representation of cause-and-effects relationships of the processes that generate the data. Specifically, The arrows indicate causal relationships assumed to be occurring. DAGs allow us to determine which variables are needed in a model by identifying possible colliding variables (that is, those we do not want to include), and the minimal set of covariates that are needed to eliminate confounding. This allows to reduce over-controlling. First we define the DAG for all the variables of interest ( A .). Then for three variables (Pesticide use, Animal pollinated agriculture, and Honey Bees), we evaluate which variables allow us to estimate each effect. To estimate the effect of Pesticide Use ( B .) we need to include Animal pollinated agriculture and Honey Bees in the model. To estimate the effect of Animal Pollinated Agriculture on wild bee occupancy ( C .) we need to include climate in the model. Finally, To estimate the effect of Honey Bees ( D .) we need to include Animal pollinated agriculture in the model. “Including” a variable here means adding a covariate for that variable to the equation for occupancy in our statistical models.

Extended Data Fig. 2 Pesticide use from 1994 to 2015.

From 1994 to 2015 the usage of organophosphates and carbamates decreased, while the usage of neonicotinoids increased rapidly, and the usage of pyrethroids remained constant. The total kg of pesticide use was summed by year and type of insecticide, where A . shows the raw sum, while B . shows the sum log-transformed. The compounds aggregated were the following: Neonicotinoids: Acetamiprid, Clothianidin, Dinotefuran, Imidacloprid, thiametoxam, Thiacloprid; Pyrethoids: Cyfluthrin, Cyhalothrin-Gamma, Cypermethrin, Deltamethrin, Fenvalerate, Fluvalinate, Fluvalinate Tau, Permethrin, Resmethrin, Tefluthrin, Tralomethrin; Carbamates: Carbaryl, Carbofuran, Methomyl, Oxamyl, Thiodicarb; Organophosphates: Azamethiphos, Azinphos-Methyl, Chlorpyrifos, Diazinon, Dichlorvos, Fenitrothion, Malathion, Methyl Parathion, Parathion, Phosmet, Tetrachlorvinphos; Other: Abamectin, Acephate, Chlorethoxyfos, Diazinon, Dimethoate, Fipronil, Pyridaben, Sulfoxaflor. Modified from data by 31 , 64 .

Extended Data Fig. 3 Sensitivity analysis to the definition of animal pollinated agriculture.

Family-level mean effect sizes on occupancy. The mean effect size for pesticide use ( A., D. Model 1) is strongly negative across all families, the mean effect size of animal pollinated agriculture ( B., E. , Model 2) is largely zero, and the mean effect size of honey bees ( C., F. , Model 3) is mixed across families. Asterisks mean that the 95% credible interval does not overlap with zero, and error bars represent 95% Bayesian credible intervals. Sample sizes vary for each family but are the same for each model (Extended Data Table 1). Panels A-C represent animal pollinated agriculture that uses managed pollinators. The crops that do not use managed pollinators are: Barley, Dry Beans, Chick Peas, Corn, Cotton, Eggplants, Garlic, Grapes, Hops, Lentils, Lettuce, Oats, Olives, Oranges, Peas, Pistachios, Potatoes, Rice, Rye, Sorghum, Soybeans, Sugarbeets, Sugarcane, Sweet Potatoes, Tobacco, Triticale, Vetch, Walnuts, Winter Wheat, Durum Wheat, Spring Wheat, Turnips, Celery, Mustard, Citrus, Pecans, Millet, Flaxseed. All other crops were considered to supplement pollination via managed pollinators. Panels D-E represent animal pollinated agriculture that is defined by crops that even though do not necessarily require pollination, they may attract pollinators and therefore expose wild bees to pesticides. In the “Non-attractive to pollinators agriculture” category we included: Barley, Grapes, Hops, Lentils, Oats, Onions, Pistachios, Rice, Rye, Sugarcane, Triticale, Walnuts, Winter Wheat, Durum Wheat, Spring Wheat, Pecans, Millet. All other crops were considered to attract pollinators.

Extended Data Fig. 4 Differential effect of neonicotinoids vs. pyrethroids on family-level mean occupancy.

Family-level mean effect sizes of neonicotinoids or pyrethroids alone on occupancy. The mean effect size for neonicotinoids is strongly negative for A n d r e n i d a e and A p i d a e , while the mean effect size for pyrethroids is strongly negative A p i d a e , C o l l e t i d a e a n d M e l i t t i d a e , and H a l i c t i d a e . Asterisks mean that the 95% credible interval does not overlap with zero, and error bars represent 95% Bayesian credible intervals. Sample sizes vary for each family but are the same for each model (Extended Data Table 1).

Extended Data Fig. 5 Effect of pesticide use on occupancy for each genera.

Mean expected county-level occupancy aggregated for every genera, decreases as neonicotinoid and pyrethroid use increases across bee families. The black line represented the mean occupancy while the shaded grey lines are the 95% credible intervals. Occupancy probability was estimated using the posterior distribution of each species intercept and each species slope effect estimated for pesticide use while keeping all other predictors at the mean value. Predicted posterior occupancy probability was then averaged across each genus. Pesticide use was varied from the minimum to the maximum ever observed. Pesticide use is the combined sum of Kg weighted by LD50 and area, log-transformed and scaled. Sample sizes vary for each family (Extended Data Table 1).

Extended Data Fig. 6 Effect of animal pollinated agriculture on occupancy for each genera.

Mean expected county-level occupancy aggregated for every genera, generally increases as the proportion of animal pollinated agriculture in a county increases. The black line represented the mean occupancy while the shaded grey lines are the 95% credible intervals. Occupancy probability was estimated using the posterior distribution of each species intercept and each species slope effect estimated for percent of animal pollinated agriculture while keeping all other predictors at the mean value. Predicted posterior occupancy probability was then averaged across each genus. The percent of agriculture that is animal pollinated in a county was log-transformed and scaled. Sample sizes vary for each family (Extended Data Table 1).

Extended Data Fig. 7 Animal pollinated agriculture by definition.

While the percent of the county that is agriculture is highly concentrated in the Midwest (2007) ( A .), Animal pollinated agriculture is more evenly distributed across the country (2008) (B. - D.). B . The percent of the county that is animal pollinated excludes the following crops: corn, wheat, rice, soybean, sorghum, barley, and oat. C . The percent of the county that uses managed pollinators excludes the following crops: Barley, Dry Beans, Chick Peas, Corn, Cotton, Eggplants, Garlic, Grapes, Hops, Lentils, Lettuce, Oats, Olives, Oranges, Peas, Pistachios, Potatoes, Rice, Rye, Sorghum, Soybeans, Sugarbeets, Sugarcane, Sweet Potatoes, Tobacco, Triticale, Vetch, Walnuts, Winter Wheat, Durum Wheat, Spring Wheat, Turnips, Celery, Mustard, Citrus, Pecans, Millet, Flaxseed. All other crops were considered to supplement pollination via managed pollinators. D . The percent of the county that is agriculture that attracts bumble bees and solitary bees excludes the following crops: : Barley, Grapes, Hops, Lentils, Oats, Onions, Pistachios, Rice, Rye, Sugarcane, Triticale, Walnuts, Winter Wheat, Durum Wheat, Spring Wheat, Pecans, Millet. All other crops were considered to attract pollinators. Modified from 33 .

Extended Data Fig. 8 Number of counties modelled for each family.

We modelled A n d r e n i d a e across 626 counties, Apidae across 1763, H a l i c t i d a e across 1046, M e g a c h i l i d a e across 970, and Colletidae and M e l i t t i d a e across 500. For each family we only included the counties where species of that family have been observed during the time period.

Supplementary information

Supplementary information.

Supplementary Figs. 1–11 and Table 1.

Reporting Summary

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Guzman, L.M., Elle, E., Morandin, L.A. et al. Impact of pesticide use on wild bee distributions across the United States. Nat Sustain (2024). https://doi.org/10.1038/s41893-024-01413-8

Download citation

Received : 25 August 2023

Accepted : 17 July 2024

Published : 27 August 2024

DOI : https://doi.org/10.1038/s41893-024-01413-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

  • Explore articles by subject
  • Guide to authors
  • Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

thesis nature management

IMAGES

  1. (PDF) Ensuring a rational nature management in the transition of land

    thesis nature management

  2. FREE 42+Thesis Templates in PDF

    thesis nature management

  3. Ch- 1Nature and significance of management. pdf

    thesis nature management

  4. PPT

    thesis nature management

  5. (PDF) The use of a mobile unit for separating coniferous trees for

    thesis nature management

  6. Nature

    thesis nature management

COMMENTS

  1. Master of Science (MSc) in Nature Management

    The MSc programme in Nature Management is about management and sustainable development of nature and landscapes based on knowledge of biology, ecology, human needs, and legislation related to nature and the environment. The programme is offered in English.

  2. The Evolution of the Nature Management System and Modern ...

    Abstract We have examined the evolution of nature management systems in a historical context. An analysis has been made of the crisis of existing nature management models, an aggravation of contradictions, and an increase in threats and risks at the beginning of the 21st century. Modern trends in the development of effective nature management have been discussed, namely, low-waste technologies ...

  3. MSc in Nature Management

    The teaching varies between lectures, exercises, excursions, and project work. The thematic course and most of the elective and restricted elective courses include field work and excursions. The MSc programme is concluded with a scientific project, the thesis, which takes 4 or 7 months and entitles graduates to the title Master of Science (MSc).

  4. PDF Curriculum for the MSc Programme in Nature Management

    6.1.5 Thesis. The MSc Programme in Nature Management (Landscape, Biodiversity and Planning) includes a thesis corresponding to 30 or 45 ECTS as described in Appendix 2 to the shared curriculum. The thesis must be written full time and the topic of the thesis must be within the academic scope of the programme.

  5. PDF Thesis topics Forest & Nature conservation Policy Group

    to the business models of forest and nature managing organizations, from small to big, in the Netherlands or in other countries. Possible thesis topics include: - Business models in forest and nature organizations - Forest and nature organizations and the social enterprise - Organizational culture in forest and nature management

  6. PDF Ph.D. in Natural Resources and Environmental Management Thesis Process

    The Natural Resources Institute (NRI) at the University of Manitoba offers Master's and Ph.D. degrees in resource and environmental management. It was established in 1968 as a degree-granting, interdisciplinary unit with a threefold purpose, namely: (a) to teach management skills leading to a graduate degree of Master of Natural Resources ...

  7. PDF Nature Based Solutions for Carbon Sequestration and Biodiversity

    NCS for forests and grassy biomes, natural regeneration, fire management, grazing management and agroforestry report positive impacts on at least two of the aspects climate change mitigation, biodiversity conservation and sustainable livelihoods. Preface This thesis was written as part of the Master programme Sustainable Development, which I

  8. Bachelor's Thesis in Nature Management

    The whole thesis may be written in English if the student so prefers. During the fourth semester (spring semester 2 nd study year) information about potential assignments is provided. During the fifth semester, project work is taught and students have to submit a pilot project for their own bachelor's thesis.

  9. PDF NATURE IN NATURE-BASED SOLUTIONS

    Faculty of Management and Business Master's Thesis November 2021 . Abstract Raysa França: Nature in nature-based solutions: understanding the discourses of nature in the UNaLab ... This thesis focuses on nature-based solutions through one specific project, the UNaLab (Urban nature lab), an urban living lab that implemented NbS in the city of ...

  10. The past, present and future of the PhD thesis

    According to one of those often-quoted statistics that should be true but probably isn't, the average number of people who read a PhD thesis all the way through is 1.6. And that includes the ...

  11. School of Natural Resources and Environment

    Ph.D. Dissertation: A Path to Nature Conservation: The Role of Mega Trails in Connecting Hikers, Communities, and Landscapes Chair/Faculty Advisor: Taylor Stein, Forest Resources and Conservation ... M.S. Thesis: The Ecology and Management of West Indian Marsh Grass (Hymenachne amplexicaulis) in Florida Wetlands Advisor: Stephen Enloe, Agronomy ...

  12. Online Master of Natural Resources (M.N.R.)

    The fundamental objective of the MNR graduate program is to integrate and scale various perspectives — ecology and management; planning, policy and society; and tools and technology — into a systems view of natural resources. ... 30 semester credits, non-thesis program designed for working professionals. Students may complete the degree in ...

  13. Dissertations / Theses: 'Nature management'

    List of dissertations / theses on the topic 'Nature management'. Scholarly publications with full text pdf download. Related research topic ideas.

  14. What's the point of the PhD thesis?

    Passing the test. Academics agree about one thing regarding the PhD assessment — its aim. The traditional goal is to demonstrate the candidate's ability to conduct independent research on a ...

  15. MSc thesis projects

    The MSc thesis projects are clustered in research themes that cover the fields of interest of our lecturers, post-docs and PhD students. They are listed as supervisors. Many subjects are also suitable for a BSc thesis. Length and content of a thesis project may be tailored to your wishes. An overview of available project can be found in the TIP ...

  16. The Evolution of the Nature Management System and Modern Trends in Its

    Abstract. We have examined the evolution of nature management systems in a historical context. An analysis has been made of the crisis of existing nature management models, an aggravation of contradictions, and an increase in threats and risks at the beginning of the 21st century. Modern trends in the development of effective nature management ...

  17. Bring PhD assessment into the twenty-first century

    And yet, most PhDs are still assessed after the production of a final dissertation, according to a format that, at its core, has not changed for at least half a century, as speakers and delegates ...

  18. PDF Community Participation in Mangrove Forest Management in the

    A thesis submitted In partial fulfillment of the requirements For the degree of Master of Science Natural Resources and Environment University of Michigan April 2016 . ... management such as household size, proximity to forests, membership to forest user groups, partnership between management authorities and local communities, among others ...

  19. Original Research: How Will the TNFD Impact the Health Sector's Nature

    3.1. Framework. The TNFD framework aims to be a risk management and disclosure tool for financial and non-financial entities to identify and disclose nature-related risks and opportunities. The current version is the second beta of an anticipated total of four, to be released later this year and next.

  20. Dissertations / Theses on the topic 'Nature conservation

    List of dissertations / theses on the topic 'Nature conservation ; Nature conservation - Research ; Nature conservation - Management'. Scholarly publications with full text pdf download. Related research topic ideas.

  21. How to Write a Thesis Statement

    Step 2: Write your initial answer. After some initial research, you can formulate a tentative answer to this question. At this stage it can be simple, and it should guide the research process and writing process. The internet has had more of a positive than a negative effect on education.

  22. Online M.S. in Environmental Science

    Overview. The non-thesis M.S. in Environmental Science requires a minimum of three credits of ENVS 599 Non-thesis Research. This is equivalent to 120 hours of work effort over 1-2 semesters. The Non-thesis Research project is intended to be a capstone experience where information and skills built during the student's time at the University of ...

  23. Streamline your writing

    Streamline your writing — and collaborations — with these reference managers. A suite of tools can help researchers to manage citations for grants and papers, and share those references with ...

  24. The Nature Conservancy provides Heartlands Update to community

    The Nature Conservancy is working to make a lasting difference around the world in 77 countries and territories (41 by direct conservation impact and 36 through partners) through a collaborative approach that engages local communities, governments, the private sector, and other partners. To learn more, visit nature.org or follow @nature_press on X.

  25. Mid-term Status on SDG 6 Indicators: 6.3.2, 6.5.1, & 6.6.1 (2024 ...

    Water is vital to human and planetary health and the internationally agreed goals that back it, including the 2030 Agenda for Sustainable Development, the Kunming-Montreal Global Biodiversity Framework, the Sendai Framework and the Paris Agreement. Yet the triple planetary crisis - the crisis of climate change, nature and biodiversity loss and pollution and waste - is affecting the ...

  26. Nanoparticle-specific transformations dictate nanoparticle ...

    Based on knowledge related to the management of NP transformations and their long-term effects, we propose feasible design suggestions to attain nano-enabled efficient and sustainable agricultural ...

  27. Impact of pesticide use on wild bee distributions across the ...

    There are widespread reports of bee declines in Europe and North America, but the status of most species is poorly known 1,2,3,4,5,6.Insect pollination, largely from wild and managed bees ...