Abstract The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.
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An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments
Abstract There is about to be an abrupt step-change in the use of coastal seas around the globe, specifically by the addition of large-scale offshore renewable energy (ORE) developments to combat climate change. Developing this sustainable energy supply will require trade-offs between both direct and indirect environmental effects, as well as spatial conflicts with marine uses like shipping, fishing, and recreation. However, the nexus between drivers, such as changes in the bio-physical environment from the introduction of structures and extraction of energy, and the consequent impacts on ecosystem services delivery and natural capital assets is poorly understood and rarely considered through a whole ecosystem perspective. Future marine planning needs to assess these changes as part of national policy level assessments but also to inform practitioners about the benefits and trade-offs between different uses of natural resources when making decisions to balance environmental and energy sustainability and socio-economic impacts. To address this shortfall, we propose an ecosystem-based natural capital evaluation framework that builds on a dynamic Bayesian modelling approach which accounts for the multiplicity of interactions between physical (e.g. bottom temperature), biological (e.g. net primary production) indicators and anthropogenic marine use (i.e. fishing) and their changes across space and over time. The proposed assessment framework measures ecosystem change, changes in ecosystem goods and services and changes in socio-economic value in response to ORE deployment scenarios as well as climate change, to provide objective information for decision processes seeking to integrate new uses into our marine ecosystems. Such a framework has the potential of exploring the likely outcomes in the same metrics (both ecological and socio-economic) from alternative management and climate scenarios, such that objective judgements and decisions can be made, as to how to balance the benefits and trade-offs between a range of marine uses to deliver long-term environmental sustainability, economic benefits, and social welfare.
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- Award ID(s):
- 2137701
- NSF-PAR ID:
- 10357324
- Date Published:
- Journal Name:
- Progress in Energy
- Volume:
- 4
- Issue:
- 3
- ISSN:
- 2516-1083
- Page Range / eLocation ID:
- 032005
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The security, resilience, and sustainability of urban water supply systems (UWSS) are challenged by global change pressures, including climate and land use changes, rapid urbanization, and population growth. Building on prior work on UWSS security and resilience, we quantify the sustainability of UWSS based on the performance of local sustainable governance and the size of global water and ecological footprints. We develop a new framework that integrates security, resilience, and sustainability to investigate trade-offs between these three distinct and inter-related dimensions. Security refers to the level of services, resilience is the system’s ability to respond to and recover from shocks, and sustainability refers to local and global impacts, and to the long-term viability of system services. Security and resilience are both relevant at local scale (city and surroundings), while for sustainability cross-scale and -sectoral feedbacks are important. We apply the new framework to seven cities selected from diverse hydro-climatic and socio-economic settings on four continents. We find that UWSS security, resilience, and local sustainability coevolve, while global sustainability correlates negatively with security. Approaching these interdependent goals requires governance strategies that balance the three dimensions within desirable and viable operating spaces. Cities outside these boundaries risk system failure in the short-term, due to lack of security and resilience, or face long-term consequences of unsustainable governance strategies. We discuss these risks in the context of poverty and rigidity traps. Our findings have strong implications for policy-making, strategic management, and for designing systems to operate sustainably at local and global scales.
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Sustainable development requires jointly achieving economic development to raise standards of living and environmental sustainability to secure these gains for the long run. Here, we develop a local-to-global, and global-to-local, earth-economy model that integrates the Global Trade Analysis Project (GTAP)-computable general equilibrium model of the economy with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model of fine-scale, spatially explicit ecosystem services. The integrated model, GTAP–InVEST, jointly determines land use, environmental conditions, ecosystem services, market prices, supply and demand across economic sectors, trade across regions, and aggregate performance metrics like GDP. We use the integrated model to analyze the contribution of investing in nature for economic prosperity, accounting for the impact of four important ecosystem services (pollination, timber provision, marine fisheries, and carbon sequestration). We show that investments in nature result in large improvements relative to a business-as-usual path, accruing annual gains of $100 to $350 billion (2014 USD) with the largest percentage gains in the lowest-income countries. Our estimates include only a small subset of ecosystem services and could be far higher with inclusion of more ecosystem services, incorporation of ecological tipping points, and reduction in substitutability that limits economic adjustments to declines in natural capital. Our analysis highlights the need for improved environmental–economic modeling and the vital importance of integrating environmental information firmly into economic analysis and policy. The benefits of doing so are potentially very large, with the greatest percentage benefits accruing to inhabitants of the poorest countries.
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Abstract The ecosystem services provided by freshwater biodiversity are threatened by development and environmental and climate change in the Anthropocene.
Here, case studies are described to show that a focus on the shared dependence on freshwater ecosystem functioning can mutually benefit fisheries and conservation agendas in the Anthropocene.
Meeting the threat to fish biodiversity and fisher livelihood is pertinent in developing regions where there is often a convergence between high biodiversity, high dependency on aquatic biota and rapid economic development (see Kafue River, Logone floodplain, Tonle Sap, and Rio Negro case studies).
These case studies serve as evidence that biodiversity conservation goals can be achieved by emphasizing a sustainable fisheries agenda with partnerships, shared knowledge and innovation in fisheries management (see Kafue River and Kenai River case studies).
In all case studies, aquatic biodiversity conservation and fisheries agendas are better served if efforts focused on creating synergies between fishing activities with ecosystem functioning yield long‐term livelihood and food security narratives.
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Abstract Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade‐offs, but this method has not yet been used to study possible changes in optimal trade‐offs caused by climate change. We created a stochastic dynamic programming model capturing trade‐off decisions required by an individual adult female polar bear (
Ursus maritimus ) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best‐case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1088/2516-1083/ac702a
