Advancing Systematic Conservation Planning for Ecosystem Services
Bibliographic record
Abstract
We are at a critical time to ensure long-term prosperity for people and nature. This is reflected by international policy frameworks such as the United Nations Sustainable Development Goals. Systematic conservation planning (SCP) has been applied as a rigorous and transparent approach to inform solutions for biodiversity conservation by private and government conservation organizations globally. This approach has gained increased attention for safeguarding ecosystem services. Nevertheless, inappropriate incorporation of the social and biophysical components of ecosystem services could result in landscape plans that fail to generate the expected benefits for people. Taking inspiration from decision theory, we provide guidance on how to incorporate ecosystem service components into SCP to secure nature’s contributions to human well-being. Conservation and sustainable management activities are critical for enhancing ecosystem services. Systematic conservation planning (SCP) is a spatial decision support process used to identify the most cost-effective places for intervention and is increasingly incorporating ecosystem services thinking. Yet, there is no clear guidance on how to incorporate ecosystem service components (i.e., supply, demand, and flow) for multiple beneficiaries into the decision problem underpinning SCP. As such, conservation plans may fall short of maximizing benefits for both people and nature. We propose a benefit-based approach to integrate ecosystem service components into SCP that uses the principles of decision theory. Our approach will improve the likelihood that ecosystem service benefits are enhanced in spatial planning applications. Conservation and sustainable management activities are critical for enhancing ecosystem services. Systematic conservation planning (SCP) is a spatial decision support process used to identify the most cost-effective places for intervention and is increasingly incorporating ecosystem services thinking. Yet, there is no clear guidance on how to incorporate ecosystem service components (i.e., supply, demand, and flow) for multiple beneficiaries into the decision problem underpinning SCP. As such, conservation plans may fall short of maximizing benefits for both people and nature. We propose a benefit-based approach to integrate ecosystem service components into SCP that uses the principles of decision theory. Our approach will improve the likelihood that ecosystem service benefits are enhanced in spatial planning applications. iterative framework for learning-based decision-making that pursues the reduction of uncertainty through monitoring the outcomes of management interventions [46.Birge H. et al.Adaptive management for ecosystem services.J. Environ. Manag. 2016; 183: 343-352Crossref PubMed Scopus (46) Google Scholar,47.McCarthy M.A. Possingham H.P. Active adaptive management for conservation.Conserv. Biol. 2007; 21: 956-963Crossref PubMed Scopus (226) Google Scholar]. people whose well-being is influenced by ecosystem services [25.Daw T. et al.Applying the ecosystem services concept to poverty alleviation: the need to disaggregate human well-being.Environ. Conserv. 2011; 38: 370-379Crossref Scopus (422) Google Scholar,32.Keeler B.L. et al.Linking water quality and well-being for improved assessment and valuation of ecosystem services.Proc. Natl. Acad. Sci. U. S. A. 2012; 109: 18619-18624Crossref PubMed Scopus (303) Google Scholar]. direct or indirect gains that people receive from ecosystem services measured in aspects of human well-being [1.Millennium Ecosystem Assessment Ecosystems and Human Well-Being: Biodiversity Synthesis. World Resources Institute, Washington, DC2005Google Scholar,64.Díaz S. et al.The IPBES Conceptual Framework — connecting nature and people.Curr. Opin. Environ. Sustain. 2015; 14: 1-16Crossref Scopus (1178) Google Scholar]. disciplined protocol for problem solving based on decision theory, which attempts to achieve explicitly stated objectives while acknowledging the levels of uncertainty involved with the decision process (i.e., describe the problem, set objectives, define variables, list actions, identify constraints, and model the system) [23.Possingham H.P. et al.Making smart conservation decisions.in: Orians G. Soule M. Research Priorities for Conservation Biology. Island Press, 2001: 225-244Google Scholar]. extent to which an ecosystem service is currently or potentially used, needed, or preferred by people [65.Villamagna A.M. et al.Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery.Ecol. Complex. 2013; 15: 114-121Crossref Scopus (382) Google Scholar,66.Bagstad K.J. et al.Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services.Ecosyst. Serv. 2013; 4: 117-125Crossref Scopus (327) Google Scholar]. recognition of the variation in demand and potential to derive ecosystem service benefits among beneficiaries [25.Daw T. et al.Applying the ecosystem services concept to poverty alleviation: the need to disaggregate human well-being.Environ. Conserv. 2011; 38: 370-379Crossref Scopus (422) Google Scholar,58.Horcea-Milcu A. et al.Disaggregated contributions of ecosystem services to human well-being: a case study from Eastern Europe.Reg. Environ. Chang. 2016; 16: 1779-1791Crossref Scopus (38) Google Scholar]. biophysical and social conditions and processes by which people, directly or indirectly, obtain benefits from ecosystems that sustain and fulfil human well-being [1.Millennium Ecosystem Assessment Ecosystems and Human Well-Being: Biodiversity Synthesis. World Resources Institute, Washington, DC2005Google Scholar,64.Díaz S. et al.The IPBES Conceptual Framework — connecting nature and people.Curr. Opin. Environ. Sustain. 2015; 14: 1-16Crossref Scopus (1178) Google Scholar]. interactions and processes that connect supply and demand [65.Villamagna A.M. et al.Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery.Ecol. Complex. 2013; 15: 114-121Crossref Scopus (382) Google Scholar, 66.Bagstad K.J. et al.Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services.Ecosyst. Serv. 2013; 4: 117-125Crossref Scopus (327) Google Scholar, 67.Fisher B. et al.Defining and classifying ecosystem services for decision making.Ecol. Econom. 2009; 68: 643-653Crossref Scopus (1878) Google Scholar]. Broadly, it includes flow direction (spatial relationship that describes where the benefit is received) and flow type (classification of flow into biophysical, human capital-driven through transportation or infrastructure, or mediated by information transmission) [65.Villamagna A.M. et al.Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery.Ecol. Complex. 2013; 15: 114-121Crossref Scopus (382) Google Scholar, 66.Bagstad K.J. et al.Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services.Ecosyst. Serv. 2013; 4: 117-125Crossref Scopus (327) Google Scholar, 67.Fisher B. et al.Defining and classifying ecosystem services for decision making.Ecol. Econom. 2009; 68: 643-653Crossref Scopus (1878) Google Scholar]. the world’s stocks of natural assets including geology, soil, air, water, and all living things [1.Millennium Ecosystem Assessment Ecosystems and Human Well-Being: Biodiversity Synthesis. World Resources Institute, Washington, DC2005Google Scholar]. mathematical formulation describing the problem of finding the best solution from all feasible solutions [7.Moilanen A. et al.Spatial Conservation Prioritization. Quantitative Methods and Computational Tools. Oxford University Press, 2009Google Scholar]. ecosystem conditions and processes that contribute to the potential delivery of a particular ecosystem service [65.Villamagna A.M. et al.Capacity, pressure, demand, and flow: a conceptual framework for analyzing ecosystem service provision and delivery.Ecol. Complex. 2013; 15: 114-121Crossref Scopus (382) Google Scholar, 66.Bagstad K.J. et al.Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services.Ecosyst. Serv. 2013; 4: 117-125Crossref Scopus (327) Google Scholar, 67.Fisher B. et al.Defining and classifying ecosystem services for decision making.Ecol. Econom. 2009; 68: 643-653Crossref Scopus (1878) Google Scholar]. structured decision analysis approach with a series of stages that concern both the design and implementation of conservation actions to meet specific objectives, usually through the spatial prioritization of the most feasible places for conservation investment [7.Moilanen A. et al.Spatial Conservation Prioritization. Quantitative Methods and Computational Tools. Oxford University Press, 2009Google Scholar, 8.Pressey R. Bottrill M. Approaches to landscape- and seascape-scale conservation planning: convergence, contrasts and challenges.Oryx. 2009; 43: 464-475Crossref Scopus (196) Google Scholar, 9.Margules C.R. Pressey R.L. Systematic conservation planning.Nature. 2000; 405: 243-253Crossref PubMed Scopus (3929) Google Scholar].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".