Conservation Prioritization

We are currently facing the likelihood of severe climate change before the close of the century. In the face of such a global driver of species loss, we urgently need to identify refugia that will shelter species from the worst impacts of climate change. This will be a critical component of successful conservation and management of our biodiversity. Despite this, little is known about how best to identify refugia in the landscape, and the practical strategies needed to identify, protect and expand refugia are just beginning to be developed. Identifying refugia that will protect most species, or large numbers of species, remains a complex and daunting endeavour due to the large variations in climatic and biotic requirements of species. A first step to identifying refugia for biodiversity across Australia is to locate the areas which show the least change into the future (i.e. the most environmentally stable), particularly along axes of temperature and precipitation. The second and cr...

Most of the world's nations adopted the 20 Aichi global biodiversity targets to be met by 2020, including the protection of at least 10% of their coastal and marine areas (Target 11) and the avoidance of extinction of threatened species (Target 12). However, reconciling these biodiversity targets with socio-economic demands remains a great dilemma for implementing conservation policies.

In this paper, Aichi Targets 11 and 12 were  simultaneously addressed using Brazil's exclusive economic zone as an example. Priority areas for expanding the current system of marine protected areas within the country's eight marine ecoregions were identified with data on threatened vertebrates under different scenarios. Additionally, the potential effects of major socio-economic activities (small and large-scale fishing, seabed mining, and oil and gas exploration) on the representation of conservation features in proposed marine protected areas were explored.

Areas selected for expanding marine protected areas solely based on biodiversity data were different (spatial overlap from 62% to 93%) from areas prioritized when socio-economic features were incorporated into the analysis. The addition of socio-economic data in the prioritization process substantially decreased opportunity costs and potential conservation conflicts, at the cost of reducing significantly (up to 31%) the coverage of conservation features. Large and small-scale fisheries act in most of the exclusive economic zone and are the major constraints for protecting high-priority areas.

Nevertheless, there is some spatial mismatch between areas of special relevance for conservation and socio-economic activities, suggesting an opportunity for reconciling the achievement of biodiversity targets and development goals within the intricate Brazilian seascape by 2020 and beyond.

One of the biggest challenges in large-scale conservation is quantifying connectivity at broad geographic scales and for a large set of species. Because connectivity analyses can be computationally intensive, and the planning process quite complex when multiple taxa are involved, assessing connectivity at large spatial extents for many species turns to be often intractable. Such limitation results in that conducted assessments are often partial by focusing on a few key species only, or are generic by considering a range of dispersal distances and a fixed set of areas to connect that are not directly linked to the actual spatial distribution or mobility of particular species. By using a graph theory framework, here we propose an approach to reduce computational effort and effectively consider large assemblages of species in obtaining multi-species connectivity priorities. We demonstrate the potential of the approach by identifying defragmentation priorities in the Italian road network focusing on medium and large terrestrial mammals. We show that by combining probabilis-tic species graphs prior to conducting the network analysis (i) it is possible to analyse con-nectivity once for all species simultaneously, obtaining conservation or restoration priorities that apply for the entire species assemblage; and that (ii) those priorities are well aligned with the ones that would be obtained by aggregating the results of separate connectivity analysis for each of the individual species. This approach offers great opportunities to extend connectivity assessments to large assemblages of species and broad geographic scales.

Aim: As a step towards providing support for an ecological approach to strengthening marine protected areas (MPAs) and meeting international commitments, this study combines cumulative impact assessment and conservation planning approach to undertake a large-scale spatial prioritization. Location: Exclusive Economic Zone (EEZ) of Brazil, Southwest Atlantic Ocean.

Methods: We developed a prioritization approach to protecting different habitat types, threatened species ranges and ecological connectivity, while also mitigating
the impacts of multiple threats on biodiversity. When identifying priorities for conservation, we accounted for the co-occurrence of 24 human threats and the distribu-
tion of 161 marine habitats and 143 threatened species, as well as their associated vulnerabilities. Additionally, we compared our conservation priorities with MPAs  proposed by local stakeholders.

Results: We show that impacts to habitats and species are widespread and identify hot spots of cumulative impacts on inshore and offshore areas. Industrial fisheries, climate change and land-based activities were the most severe threats to biodiversity. The highest priorities were mostly found towards the coast due to the high cumulative impacts found in nearshore areas. As expected, our systematic approach showed a better performance on selecting priority sites when compared to the MPAs proposed by local stakeholders without a typical conservation planning exercise, increasing the existing coverage of MPAs by only 7.9%. However, we found that proposed MPAs still provide some opportunities to protect areas facing high levels of threats.

Main conclusions: The study presents a blueprint of how to embrace a comprehensive ecological approach when identifying strategic priorities for conservation. We advocate protecting these crucial areas from degradation in emerging conservation efforts is key to maintain their biodiversity value.

We propose a landscape-scale prioritization procedure for tropical forest landscape as the following; defining the conservation tasks, identifying components and subcomponents, and assessing the parameters. Defining tasks in forest conservation, either for preservation or rehabilitation, depends on the purposes of the forest management and/or established the criteria and indicator for sustainable forest management. Identification of component within each conservation task must cover both value/ importance and threat/urgency. Component is then narrowed down into the subcomponents by considering forest landscape characteristics. Parameters which are considered as measurable biophysical conditions of the forest landscape are assessed in each sub-component. Since the landscape is the appropriate perspective for forest prioritization, therefore, parameter assessment must acknowledge scale, spatial and temporal patterns of the forest landscape. Recent zonation of forests, as the result of...

1A principal goal of protected-area networks is to maintain viable populations of as many species as possible, particularly those that are vulnerable to environmental change outside reserves. Ideally, one wants to be able to protect all biodiversity when selecting priority areas for conservation.2Using the area-prioritization algorithm ZONATION, we identified the locations where UK Biodiversity Action Plan (BAP) species of mammals, birds, herptiles, butterflies and plants occur in concentrated populations with high connectivity. Both these features are likely to be correlated with population persistence. The analyses were successful in maintaining a high proportion of the connectivity of narrow-range species, and large total amounts of the connectivity of wider-range species over 10% of the land surface of Great Britain.3Biodiversity Action Plan (BAP – high priority) species of one taxonomic group were not particularly good surrogates (indicators) for BAP species of other taxonomic groups. Hence, maintaining population concentrations of one taxonomic group did not guarantee doing likewise for other taxa.4Species with narrow geographic ranges were most effective at predicting conservation success for other species, probably because they represent the range of environmental conditions required by other species.5Synthesis and applications. This study identifies landscape-scale priority areas for conservation of priority species from several taxonomic groups, using the Zonation software. ‘Indicator groups’ were only partially successful as predictors of priority areas for other taxonomic groups, and therefore, the identification of priority areas for biodiversity conservation should include information from all taxonomic groups available. Larger areas should be protected to account for species not included in the analyses. Conservation solutions based on data for many different species, and particularly those species with narrowly defined ranges, appear to be most effective at protecting other rare taxa.A principal goal of protected-area networks is to maintain viable populations of as many species as possible, particularly those that are vulnerable to environmental change outside reserves. Ideally, one wants to be able to protect all biodiversity when selecting priority areas for conservation.Using the area-prioritization algorithm ZONATION, we identified the locations where UK Biodiversity Action Plan (BAP) species of mammals, birds, herptiles, butterflies and plants occur in concentrated populations with high connectivity. Both these features are likely to be correlated with population persistence. The analyses were successful in maintaining a high proportion of the connectivity of narrow-range species, and large total amounts of the connectivity of wider-range species over 10% of the land surface of Great Britain.Biodiversity Action Plan (BAP – high priority) species of one taxonomic group were not particularly good surrogates (indicators) for BAP species of other taxonomic groups. Hence, maintaining population concentrations of one taxonomic group did not guarantee doing likewise for other taxa.Species with narrow geographic ranges were most effective at predicting conservation success for other species, probably because they represent the range of environmental conditions required by other species.Synthesis and applications. This study identifies landscape-scale priority areas for conservation of priority species from several taxonomic groups, using the Zonation software. ‘Indicator groups’ were only partially successful as predictors of priority areas for other taxonomic groups, and therefore, the identification of priority areas for biodiversity conservation should include information from all taxonomic groups available. Larger areas should be protected to account for species not included in the analyses. Conservation solutions based on data for many different species, and particularly those species with narrowly defined ranges, appear to be most effective at protecting other rare taxa.