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A climatic stability approach to prioritizing global conservation investments.

ABSTRACT: Climate change is impacting species and ecosystems globally. Many existing templates to identify the most important areas to conserve terrestrial biodiversity at the global scale neglect the future impacts of climate change. Unstable climatic conditions are predicted to undermine conservation investments in the future. This paper presents an approach to developing a resource allocation algorithm for conservation investment that incorporates the ecological stability of ecoregions under climate change. We discover that allocating funds in this way changes the optimal schedule of global investments both spatially and temporally. This allocation reduces the biodiversity loss of terrestrial endemic species from protected areas due to climate change by 22% for the period of 2002-2052, when compared to allocations that do not consider climate change. To maximize the resilience of global biodiversity to climate change we recommend that funding be increased in ecoregions located in the tropics and/or mid-elevation habitats, where climatic conditions are predicted to remain relatively stable. Accounting for the ecological stability of ecoregions provides a realistic approach to incorporating climate change into global conservation planning, with potential to save more species from extinction in the long term.

SUBMITTER: Iwamura T

PROVIDER: S-EPMC2994894 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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A climatic stability approach to prioritizing global conservation investments.

Iwamura Takuya T Wilson Kerrie A KA Venter Oscar O Possingham Hugh P HP

PloS one 20101130 11

Climate change is impacting species and ecosystems globally. Many existing templates to identify the most important areas to conserve terrestrial biodiversity at the global scale neglect the future impacts of climate change. Unstable climatic conditions are predicted to undermine conservation investments in the future. This paper presents an approach to developing a resource allocation algorithm for conservation investment that incorporates the ecological stability of ecoregions under climate ch ...[more]

PMID: 21152095

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Project description:BackgroundMillions of dollars are invested annually under the umbrella of national health systems strengthening. Global health initiatives provide funding for low- and middle-income countries through disease-oriented programmes while maintaining that the interventions simultaneously strengthen systems. However, it is as yet unclear which, and to what extent, system-level interventions are being funded by these initiatives, nor is it clear how much funding they allocate to disease-specific activities - through conventional 'vertical-programming' approach. Such funding can be channelled to one or more of the health system building blocks while targeting disease(s) or explicitly to system-wide activities.MethodsWe operationalized the World Health Organization health system framework of the six building blocks to conduct a detailed assessment of Global Fund health system investments. Our application of this framework framework provides a comprehensive quantification of system-level interventions. We applied this systematically to a random subset of 52 of the 139 grants funded in Round 8 of the Global Fund to Fight AIDS, Tuberculosis and Malaria (totalling approximately US$1 billion).ResultsAccording to the analysis, 37% (US$ 362 million) of the Global Fund Round 8 funding was allocated to health systems strengthening. Of that, 38% (US$ 139 million) was for generic system-level interventions, rather than disease-specific system support. Around 82% of health systems strengthening funding (US$ 296 million) was allocated to service delivery, human resources, and medicines & technology, and within each of these to two to three interventions. Governance, financing, and information building blocks received relatively low funding.ConclusionsThis study shows that a substantial portion of Global Fund's Round 8 funds was devoted to health systems strengthening. Dramatic skewing among the health system building blocks suggests opportunities for more balanced investments with regard to governance, financing, and information system related interventions. There is also a need for agreement, by researchers, recipients, and donors, on keystone interventions that have the greatest system-level impacts for the cost-effective use of funds. Effective health system strengthening depends on inter-agency collaboration and country commitment along with concerted partnership among all the stakeholders working in the health system.

Project description:This study reports on the application of a Portfolio Decision Analysis (PDA) to support investment decisions of a non-profit funder of vaccine technology platform development for rapid response to emerging infections. A value framework was constructed via document reviews and stakeholder consultations. Probability of Success (PoS) data was obtained for 16 platform projects through expert assessments and stakeholder portfolio preferences via a Discrete Choice Experiment (DCE). The structure of preferences and the uncertainties in project PoS suggested a non-linear, stochastic value maximization problem. A simulation-optimization algorithm was employed, identifying optimal portfolios under different budget constraints. Stochastic dominance of the optimization solution was tested via mean-variance and mean-Gini statistics, and its robustness via rank probability analysis in a Monte Carlo simulation. Project PoS estimates were low and substantially overlapping. The DCE identified decreasing rates of return to investing in single platform types. Optimal portfolio solutions reflected this non-linearity of platform preferences along an efficiency frontier and diverged from a model simply ranking projects by PoS-to-Cost, despite significant revisions to project PoS estimates during the review process in relation to the conduct of the DCE. Large confidence intervals associated with optimization solutions suggested significant uncertainty in portfolio valuations. Mean-variance and Mean-Gini tests suggested optimal portfolios with higher expected values were also accompanied by higher risks of not achieving those values despite stochastic dominance of the optimal portfolio solution under the decision maker's budget constraint. This portfolio was also the highest ranked portfolio in the simulation; though having only a 54% probability of being preferred to the second-ranked portfolio. The analysis illustrates how optimization modelling can help health R&D decision makers identify optimal portfolios in the face of significant decision uncertainty involving portfolio trade-offs. However, in light of such extreme uncertainty, further due diligence and ongoing updating of performance is needed on highly risky projects as well as data on decision makers' portfolio risk attitude before PDA can conclude about optimal and robust solutions.

Dataset Information

A climatic stability approach to prioritizing global conservation investments.

Publications

A climatic stability approach to prioritizing global conservation investments.

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