Integration of biophysical connectivity in the spatial optimization of coastal ecosystem services

Ecological connectivity in coastal oceanic waters is mediated by dispersion of the early life stages of marine organisms and conditions the structure of biological communities and the provision of ecosystem services. Integrated management strategies aimed at ensuring long-term service provision to society do not currently consider the importance of dispersal and larval connectivity. A spatial optimization model is introduced to maximise the potential provision of ecosystem services in coastal areas by accounting for the role of dispersal and larval connectivity. The approach combines a validated coastal circulation model that reproduces realistic patterns of larval transport along the coast, which ultimately conditions the biological connectivity and productivity of an area, with additional spatial layers describing potential ecosystem services. The spatial optimization exercise was tested along the coast of Central Chile, a highly productive area dominated by the Humboldt Current. Results show it is unnecessary to relocate existing management areas, as increasing no-take areas by 10% could maximise ecosystem service provision, while improving the spatial representativeness of protected areas and minimizing social conflicts. The location of protected areas was underrepresented in some sections of the study domain, principally due to the restriction of the model to rocky subtidal habitats. Future model developments should encompass the diversity of coastal ecosystems and human activities to inform integrative spatial management. Nevertheless, the spatial optimization model is innovative not only for its integrated ecosystem perspective, but also because it demonstrates that it is possible to incorporate time-varying biophysical connectivity within the optimization problem, thereby linking the dynamics of exploited populations produced by the spatial management regime.Comment: 30 pages, 5 figures, 2 tables; 1 graphical abstract. In this version: numbering of figures corrected, updated figure 2, typos corrected and references fixe

A mixed integer programming approach for multi-action planning for threat management

Planning for management actions that address threats to biodiversity is important for securing its long term persistence. However, systematic conservation planning (SCP) has traditionally overlooked this aspect and just focused on identiying priority areas without any recommendation on actions needed. This paper develops a mixed integer mathematical programming (MIP) approach for the multi-action management planning problem (MAMP), where the goal is to find an optimal combination of management actions that abate threats, in an efficent way while accounting for connectiivty. An extended version of the MAMP model (MAMP-E) is also proposed that adds an expression for minimizing fragmentation between different actions. To evaluate the efficiency of the two models, they were applied to a case study corresponding to a large area of the Mitchell River in Northern Asutralia, where 45 species of freshwater fish are exposed to the presence of four threats. The evaluation compares our exact MIP approach with the conservation planning software Marxan and the heuristic approach developed in Cattarino et al. (2015). The results obtained show that our MIP models have three advantages over their heuristic counterparts: shorter execution times, higher solutions quality, and a solution quality guarantee. Hence, the proposed MIP methodology provides a more effective framework for addressing the multi-action conservation problem.Peer ReviewedPostprint (published version

Global priority areas for ecosystem restoration

Extensive ecosystem restoration is increasingly seen as being central to conserving biodiversity1 and stabilizing the climate of the Earth2. Although ambitious national and global targets have been set, global priority areas that account for spatial variation in benefits and costs have yet to be identified. Here we develop and apply a multicriteria optimization approach that identifies priority areas for restoration across all terrestrial biomes, and estimates their benefits and costs. We find that restoring 15% of converted lands in priority areas could avoid 60% of expected extinctions while sequestering 299 gigatonnes of CO2—30% of the total CO2 increase in the atmosphere since the Industrial Revolution. The inclusion of several biomes is key to achieving multiple benefits. Cost effectiveness can increase up to 13-fold when spatial allocation is optimized using our multicriteria approach, which highlights the importance of spatial planning. Our results confirm the vast potential contributions of restoration to addressing global challenges, while underscoring the necessity of pursuing these goals synergistically.Fil: Strassburg, Bernardo B. N.. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal do Rio de Janeiro; BrasilFil: Iribarrem, Alvaro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Beyer, Hawthorne L.. The University of Queensland; Australia. University of Queensland; AustraliaFil: Cordeiro, Carlos Leandro. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Crouzeilles, Renato. Universidade Federal do Rio de Janeiro; Brasil. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Jakovac, Catarina C.. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Braga Junqueira, André. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Lacerda, Eduardo. Pontifícia Universidade Católica do Rio de Janeiro; Brasil. Universidade Federal Fluminense; BrasilFil: Latawiec, Agnieszka E.. University of East Anglia; Reino Unido. Pontifícia Universidade Católica do Rio de Janeiro; BrasilFil: Balmford, Andrew. University of Cambridge; Estados UnidosFil: Brooks, Thomas M.. University Of The Philippines Los Banos; Filipinas. Institute For Marine And Antarctic Studies; Australia. International Union For Conservation Of Nature And Natural Resources; SuizaFil: Butchart, Stuart H. M.. University of Cambridge; Estados UnidosFil: Chazdon, Robin L.. University Of The Sunshine Coast; Australia. University of Connecticut; Estados UnidosFil: Erb, Karl-Heinz. Universitat Fur Bodenkultur Wien; AustriaFil: Brancalion, Pedro. Universidade de Sao Paulo; BrasilFil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino UnidoFil: Cooper, David. Secretariat Of The Convention On Biological Diversity; CanadáFil: Díaz, Sandra Myrna. Universidad Nacional de Córdoba; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Donald, Paul F.. University of Cambridge; Estados UnidosFil: Kapos, Valerie. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Leclère, David. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Miles, Lera. United Nations Environment Programme World Conservation Monitoring Centre; Reino UnidoFil: Obersteiner, Michael. Oxford Social Sciences Division; Reino Unido. International Institute For Applied Systems Analysis, Laxenburg; AustriaFil: Plutzar, Christoph. Universitat Fur Bodenkultur Wien; Austria. Universidad de Viena; AustriaFil: de M. Scaramuzza, Carlos Alberto. International Institute For Sustainability; BrasilFil: Scarano, Fabio R.. Universidade Federal do Rio de Janeiro; BrasilFil: Visconti, Piero. International Institute For Applied Systems Analysis, Laxenburg; Austri

Multi criteria decision support system for watershed management under uncertain conditions, A

2012 Summer.Includes bibliographical references.Nonpoint source (NPS) pollution is the primary cause of impaired water bodies in the United States and around the world. Elevated nutrient, sediment, and pesticide loads to waterways may negatively impact human health and aquatic ecosystems, increasing costs of pollutant mitigation and water treatment. Control of nonpoint source pollution is achievable through implementation of conservation practices, also known as Best Management Practices (BMPs). Watershed-scale NPS pollution control plans aim at minimizing the potential for water pollution and environmental degradation at minimum cost. Simulation models of the environment play a central role in successful implementation of watershed management programs by providing the means to assess the relative contribution of different sources to the impairment and water quality impact of conservation practices. While significant shifts in climatic patterns are evident worldwide, many natural processes, including precipitation and temperature, are affected. With projected changes in climatic conditions, significant changes in diffusive transport of nonpoint source pollutants, assimilative capacity of water bodies, and landscape positions of critical areas that should be targeted for implementation of conservation practices are also expected. The amount of investment on NPS pollution control programs makes it all but vital to assure the conservation benefits of practices will be sustained under the shifting climatic paradigms and challenges for adoption of the plans. Coupling of watershed models with regional climate projections can potentially provide answers to a variety of questions on the dynamic linkage between climate and ecologic health of water resources. The overarching goal of this dissertation is to develop a new analysis framework for the development of optimal NPS pollution control strategy at the regional scale under projected future climate conditions. Proposed frameworks were applied to a 24,800 ha watershed in the Eagle Creek Watershed in central Indiana. First, a computational framework was developed for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. This study highlighted the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management. Second, an integrated simulation-optimization approach for targeted implementation of agricultural conservation practices was presented. A multiobjective genetic algorithm (NSGA-II) with mixed discrete-continuous decision variables was used to identify optimal types and locations of conservation practices for nutrient and pesticide control. This study showed that mixed discrete-continuous optimization method identifies better solutions than commonly used binary optimization methods. Third, the conclusion from application of NSGA-II optimization followed by development of a multi criteria decision analysis framework to identify near-optimal NPS pollution control plan using a priori knowledge about the system. The results suggested that the multi criteria decision analysis framework can be an effective and efficient substitute for optimization frameworks. Fourth, the hydrologic and water quality simulations driven by an extensive ensemble of climate projections were analyzed for their respective changes in basin average temperature and precipitation. The results revealed that the water yield and pollutants transport are likely to change substantially under different climatic paradigms. And finally, impact of projected climate change on performance of conservation practice and shifts in their optimal types and locations were analyzed. The results showed that performance of NPS control plans under different climatic projections will alter substantially; however, the optimal types and locations of conservation practices remained relatively unchanged

An assessment of the state of conservation planning in Europe

Expanding and managing current habitat and species protection measures is at the heart of the European biodiversity strategy. A structured approach to gain insights into such issues is systematic conservation planning, which utilizes techniques from decision theory to identify places and actions that contribute most effectively to policy objectives given a set of constraints. Yet culturally and historically determined European landscapes make the implementation of any conservation plans challenging, requiring an analysis of synergies and trade-offs before implementation. In this work, we review the scientific literature for evidence of previous conservation planning approaches, highlighting recent advances and success stories. We find that the conceptual characteristics of European conservation planning studies likely reduced their potential in contributing to better-informed decisions. We outline pathways towards improving the uptake of decision theory and multi-criteria conservation planning at various scales, particularly highlighting the need for (a) open data and intuitive tools, (b) the integration of biodiversity-focused conservation planning with multiple objectives, (c) accounting of dynamic ecological processes and functions, and (d) better facilitation of entry-points and codesign practices of conservation planning scenarios with stakeholders. By adopting & improving these practices, European conservation planning might become more actionable and adaptable towards implementable policy outcomes

Towards systematic and evidence-based conservation planning for western chimpanzees

As animal populations continue to decline, frequently driven by large‐scale land‐use change, there is a critical need for improved environmental planning. While data‐driven spatial planning is widely applied in conservation, as of yet it is rarely used for primates. The western chimpanzee (Pan troglodytes verus) declined by 80% within 24 years and was uplisted to Critically Endangered by the IUCN Red List of Threatened Species in 2016. To support conservation planning for western chimpanzees, we systematically identified geographic areas important for this taxon. We based our analysis on a previously published data set of modeled density distribution and on several scenarios that accounted for different spatial scales and conservation targets. Across all scenarios, typically less than one‐third of areas we identified as important are currently designated as high‐level protected areas (i.e., national park or IUCN category I or II). For example, in the scenario for protecting 50% of all chimpanzees remaining in West Africa (i.e., approximately 26,500 chimpanzees), an area of approximately 60,000 km2 was selected (i.e., approximately 12% of the geographic range), only 24% of which is currently designated as protected areas. The derived maps can be used to inform the geographic prioritization of conservation interventions, including protected area expansion, “no‐go‐zones” for industry and infrastructure, and conservation sites outside the protected area network. Environmental guidelines by major institutions funding infrastructure and resource extraction projects explicitly require corporations to minimize the negative impact on great apes. Therefore, our results can inform avoidance and mitigation measures during the planning phases of such projects. This study was designed to inform future stakeholder consultation processes that could ultimately integrate the conservation of western chimpanzees with national land‐use priorities. Our approach may help in promoting similar work for other primate taxa to inform systematic conservation planning in times of growing threats