scholarly journals Robustness Trade-offs in Social-Ecological Systems

2007 ◽  
Vol 1 (1) ◽  
pp. 43 ◽  
Author(s):  
Marco A. Janssen ◽  
John M Anderies
Keyword(s):  
Ecological Systems ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Trade Offs

scholarly journals Cross-Scale Value Trade-Offs in Managing Social-Ecological Systems: The Politics of Scale in Ruaha National Park, Tanzania

2011 ◽  
Vol 16 (4) ◽  
Author(s):  
Asim Zia ◽  
Paul Hirsch ◽  
Alexander Songorwa ◽  
David R. Mutekanga ◽  
Sheila O'Connor ◽  
...  
Keyword(s):  
National Park ◽  
Ecological Systems ◽  
Politics Of Scale ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Trade Offs ◽  
Ruaha National Park

scholarly journals Monitoring social–ecological networks for biodiversity and ecosystem services in human-dominated landscapes

FACETS ◽  
2021 ◽  
Vol 6 ◽  
pp. 1670-1692
Author(s):  
Carina Rauen Firkowski ◽  
Amanda M. Schwantes ◽  
Marie-Josée Fortin ◽  
Andrew Gonzalez
Keyword(s):  
Ecosystem Services ◽  
Ecosystem Service ◽  
Ecological Systems ◽  
Maple Syrup ◽  
Spatial And Temporal Scales ◽  
Causal Understanding ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Trade Offs ◽  
Analytical Tools

The demand the human population is placing on the environment has triggered accelerated rates of biodiversity change and created trade-offs among the ecosystem services we depend upon. Decisions designed to reverse these trends require the best possible information obtained by monitoring ecological and social dimensions of change. Here, we conceptualize a network framework to monitor change in social–ecological systems. We contextualize our framework within Ostrom’s social–ecological system framework and use it to discuss the challenges of monitoring biodiversity and ecosystem services across spatial and temporal scales. We propose that spatially explicit multilayer and multiscale monitoring can help estimate the range of variability seen in social–ecological systems with varying levels of human modification across the landscape. We illustrate our framework using a conceptual case study on the ecosystem service of maple syrup production. We argue for the use of analytical tools capable of integrating qualitative and quantitative knowledge of social–ecological systems to provide a causal understanding of change across a network. Altogether, our conceptual framework provides a foundation for establishing monitoring systems. Operationalizing our framework will allow for the detection of ecosystem service change and assessment of its drivers across several scales, informing the long-term sustainability of biodiversity and ecosystem services.

scholarly journals Linking resilience and robustness and uncovering their trade-offs in coupled infrastructure systems

2018 ◽  
Vol 9 (4) ◽  
pp. 1159-1168 ◽  
Author(s):  
Mehran Homayounfar ◽  
Rachata Muneepeerakul ◽  
John M. Anderies ◽  
Chitsomanus P. Muneepeerakul
Keyword(s):  
Coupled System ◽  
Analytical Framework ◽  
Ecological Systems ◽  
Internal Stresses ◽  
Public Infrastructure ◽  
Social Ecological Systems ◽  
Qualitative Approaches ◽  
Social Ecological ◽  
Trade Offs ◽  
Long Run

Abstract. Robustness and resilience are concepts in systems thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used conceptual framework for social-ecological systems. The model enables us to rigorously delineate the boundaries of conditions under which the coupled system can be sustained in a long run, define robustness and resilience related to these boundaries, and consequently investigate their connections. The results reveal the trade-offs between robustness and resilience. They also show how the nature of such trade-offs varies with the choice of certain policies (e.g., taxation and investment in public infrastructure), internal stresses, and uncertainty in social-ecological settings.

scholarly journals Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260159
Author(s):  
Elizabeth A. Law ◽  
John D. C. Linnell ◽  
Bram van Moorter ◽  
Erlend B. Nilsen
Keyword(s):  
Climatic Variability ◽  
Optimal Solution ◽  
Ecological Systems ◽  
Ecological Processes ◽  
Diverse Range ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Trade Offs ◽  
Optimal Harvest ◽  
Wildlife Harvest

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

scholarly journals How Robust is Your System Resilience?

2018 ◽  
Author(s):  
Mehran Homayounfar ◽  
Rachata Muneepeerakul ◽  
John M. Anderies
Keyword(s):  
Coupled System ◽  
Analytical Framework ◽  
Ecological Systems ◽  
Internal Stresses ◽  
Public Infrastructure ◽  
Social Ecological Systems ◽  
Qualitative Approaches ◽  
Social Ecological ◽  
Trade Offs ◽  
Long Run

Abstract. Robustness and resilience are concepts in systems thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used conceptual framework for social-ecological systems. The model enables us to rigorously delineate the boundaries of conditions under which the coupled system can be sustained in a long run, define robustness and resilience related to these boundaries, and consequently investigate their connections. The results reveal the tradeoffs between robustness and resilience. They also show how the nature of such tradeoffs varies with the choices of certain policies (e.g., taxation and investment in public infrastructure), internal stresses and external disturbances.

Sustainability of wildlife harvest in stochastic social-ecological systems

2020 ◽  
Author(s):  
Elizabeth Law ◽  
John D C Linnell ◽  
Bram Van Moorter ◽  
Erlend B. Nilsen
Keyword(s):  
Simulation Models ◽  
Ecological Systems ◽  
Multiple Objectives ◽  
Potential Conflict ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Trade Offs ◽  
Singular Optimum ◽  
Wildlife Harvest ◽  
Ethical Perspectives

1.Sustainable wildlife harvest is challenged by complex and uncertain social-ecological systems, and diverse stakeholder perspectives. Heuristics could provide one avenue to integrate scientific principles and understand potential conflict in data-poor harvest systems. Management Strategy Evaluation (MSE) can be a useful tool to explore harvest options and implications from diverse perspectives, and aid in heuristic development.2.We ran 176,910 stochastic simulation models to develop heuristics for sustainability in wildlife harvest systems. Environmental contexts included three simulated species distributed across the slow-fast life-history gradient (the great-unicorn, lesser-unicorn, and phoenix), two variability/uncertainty levels, and three starting population sizes. Optimal outcomes from four harvest strategies (constant, proportional, threshold-proportional, and threshold-increasing-proportional) were assessed under evaluation contexts reflecting multiple environmental, harvester, manager and societal sustainability objectives and ethical perspectives.3.The results reveal fundamental challenges in obtaining sustainable outcomes in harvest systems: few scenarios produced good scores across all evaluation metrics and ethical perspectives. Composite evaluation metric sets and ethical perspectives strongly influenced perceived outcomes. Rawlsian ethical perspectives (considering the minimum score of multiple objectives) often revealed severe trade-offs between individual metrics, even when Utilitarian ethical perspectives (averaging scores of multiple objectives) view the same scenarios positively. Simple composite metrics popular in the theoretical literature often diverged from the holistic metrics that better reflect applied contexts.4.Threshold and proportional systems performed better than constant harvest under Utilitarian ethics in 79-90% of cases, and 34-39% of cases with Rawlsian ethics. However, no strategy was optimal overall: each harvest system tested was near-optimal in at least one evaluation context in every environmental context.5.Synthesis and applications. Given a lack of a singular optimum strategy, we recommend harvest systems should be chosen with clear reference to contextually appropriate metrics and ethics of interest when optimizing harvest systems for sustainability. Importantly, management recommendations focused on maximizing harvest should be treated with skepticism if this is not explicitly identified as a key value for that socio-ecological system.

Systems theories

2018 ◽  
Author(s):  
Marc J. Stern
Keyword(s):  
Social Networks ◽  
Problem Solving ◽  
Natural Resources ◽  
Real World ◽  
Common Pool Resources ◽  
Ecological Systems ◽  
Effective Governance ◽  
Social Ecological Systems ◽  
Social Ecological ◽  
Real World Problem

This chapter covers systems theories relevant to understanding and working to enhance the resilience of social-ecological systems. Social-ecological systems contain natural resources, users of those resources, and the interactions between each. The theories in the chapter share lessons about how to build effective governance structures for common pool resources, how to facilitate the spread of worthwhile ideas across social networks, and how to promote collaboration for greater collective impacts than any one organization alone could achieve. Each theory is summarized succinctly and followed by guidance on how to apply it to real world problem solving.

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