Spatial Conservation Prioritization

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The utility of spatial conservation prioritization (SCP), could be limited by the biases produced by taxonomic uncertainty and by the lack of an accepted taxonomic checklist for a diverse group of species. Using information on the endemic cacti of the Atacama Desert and Mediterranean Chile, we assessed the implications for SCP of the existence of two contrasting taxonomies. Biological and socioeconomic criteria were combined to design conservation networks for two widely used taxonomic checklists of endemic Chilean cacti. We analyzed the spatial distribution of these conservation networks to assess the congruence of the taxonomic checklists and evaluated whether our models match the geographic distribution of the National System of Protected Areas. The conservation networks had low similarity. However, consensus scenarios revealed several coincident priority sites. Gap analyses indicated that one-third of the species were completely unprotected but that all species were satisfactorily protected in the consensus scenario. Consensus scenarios based on different checklists can improve SCP because this approach is less affected by taxonomic uncertainty. It is more conservative (without a priori taxonomic decisions) and robust (priority sites are supported by more than one scenario). Given the narrow distribution of cacti, effective conservation actions demand environmental actions in a geographically explicit framework.

Leading up to the Convention on Biological Diversity Conference of the Parties 15, there is momentum around setting bold conservation targets. Yet, it remains unclear how much of Earth's land area remains without significant human influence and where this land is located. We compare four recent global maps of human influences across Earth's land, Anthromes, Global Human Modification, Human Footprint and Low Impact Areas, to answer these questions. Despite using various methodologies and data, these different spatial assessments independently estimate similar percentages of the Earth's terrestrial surface as having very low (20%–34%) and low (48%–56%) human influence. Three out of four spatial assessments agree on 46% of the non‐permanent ice‐ or snow‐covered land as having low human influence. However, much of the very low and low influence portions of the planet are comprised of cold (e.g., boreal forests, montane grasslands and tundra) or arid (e.g., deserts) landscape...

In the light of the current changing global scenarios, green infrastructure is obtaining increasing relevance in planning policies, especially due to its ecological, environmental and social components which contribute to pursuing sustainable and resilient planning and designing of cities and territories. The issue of green infrastructure is framed within the conceptual contexts of sustainability and resilience, which are described through the analysis of their common aspects and differences with a particular focus on planning elements. In particular, the paper uses two distinct case studies of green infrastructure as representative: the green infrastructure of the Region Languedoc-Roussillon in France and the one of the Province of Turin in Italy. The analysis of two case studies focuses on the evaluation process carried on about the social-ecological system and describes the methodologies and the social-ecological indicators used to define the green infrastructure network. We related these indicators to their possible contribution to the measurement of sustainability and resilience. The analysis of this relationship led us to outline some conclusive considerations on the complex role of the design of green infrastructure with reference to sustainability and resilience.

Gaps in research exist for country-wide analyses to identify areas of particular importance for biodiversity and ecosystem services to help reach Aichi Target 11 in developing countries. Here we provide a spatial conservation prioritization approach that ranks landowners for maximizing the representation of biodiversity features and ecosystem services, while exploring the trade-offs with agricultural and commercial forestry production and land cost, using Uruguay as a case study. Specifically, we explored four policy scenarios, ranging from a business as usual scenario where only biodiversity and ecosystem services were included in the analysis to a potentially unsustainable scenario where expansion of alternative land uses and economic development would be given higher priority over biodiversity and ecosystem services. At the 17% land target proposed for conservation, the representation levels for biodiversity and ecosystem services were, on average, higher under the business as usual scenario. However, a small addition to the proposed target (from 17 to 20%) allowed to meet same representation levels for biodiversity and ecosystem services, while decreasing conflict with agricultural and commercial forestry production and opportunity costs to local landowners. Under the unsustainable scenario, a striking 41% addition to the conservation target (from 17 to 58%) was needed to meet same representation levels for threatened ecosystems and ecosystem services, which are crucial to sustain human well-being. Our results highlight that more realistic and potentially higher conservation targets, than politically set targets, can be achieved at the country level when sustainable development needs are also accounted for.

The utility of spatial conservation prioritization (SCP), could be limited by the biases produced by taxonomic uncertainty and by the lack of an accepted taxonomic checklist for a diverse group of species. Using information on the endemic cacti of the Atacama Desert and Mediterranean Chile, we assessed the implications for SCP of the existence of two contrasting taxonomies. Biological and socioeconomic criteria were combined to design conservation networks for two widely used taxonomic checklists of endemic Chilean cacti. We analyzed the spatial distribution of these conservation networks to assess the congruence of the taxonomic checklists and evaluated whether our models match the geographic distribution of the National System of Protected Areas. The conservation networks had low similarity. However, consensus scenarios revealed several coincident priority sites. Gap analyses indicated that one-third of the species were completely unprotected but that all species were satisfactorily protected in the consensus scenario. Consensus scenarios based on different checklists can improve SCP because this approach is less affected by taxonomic uncertainty. It is more conservative (without a priori taxonomic decisions) and robust (priority sites are supported by more than one scenario). Given the narrow distribution of cacti, effective conservation actions demand environmental actions in a geographically explicit framework.

Urban green infrastructure (UGI) has a key role in improving human and environmental health in cities and contributes to several services related to climate adaptation. Accurate localization and quantification of pervious surfaces and canopy cover are envisaged to implement UGI, address sustainable spatial planning, and include adaptation and mitigation strategies in urban planning practices. This study aims to propose a simple and replicable process to map pervious surfaces and canopy cover and to investigate the reliability and the potential planning uses of UGI maps. The proposed method combines the normalized difference vegetation index (NDVI), extracted from high-resolution airborne imagery (0.20 m), with digital elevation models to map pervious surfaces and canopy cover. The approach is tested in the Municipality of Trento, Italy, and, according to a random sampling validation, has an accuracy exceeding 80%. The paper provides a detailed map of green spaces in the urban areas,...

Social networks play an important role in facilitating effective and sustained connections between people responsible for regional conservation plans and those responsible for local conservation actions. Yet, few studies have utilized social network analysis in systematic conservation planning initiatives; this, in spite of social network analysis being developed as a structural and relational approach to describe and analyze the characteristics of patterns of relationships that make collaborative efforts more or less effective at solving natural resource management problems. Systematic conservation planning provides a framework for allocating actions in time and space to promote the conservation of biodiversity. Our study discusses three potential contributions of social network analysis to systematic conservation planning: identifying stakeholders and their roles in social networks, and characterizing relationships between them; designing and facilitating strategic networking to strengthen linkages between local and regional conservation initiatives; and prioritizing conservation actions using measures of social connectivity alongside ecological data. We propose that social network analysis has the potential to be a valuable tool to support decision making in conservation planning. We identify challenges and future research questions to be addressed to allow the integration of social network analysis into conservation planning processes.

International and national initiatives aim to conserve at least 30% of lands and waters by 2030. To safeguard biodiversity, conservation actions must be distributed in places that represent ecosystem and species diversity. Various methods of prioritizing sites for conservation have been used in local and global assessments. However, the performance and consequences of alternative methods are usually unknown. Such comparisons are needed to confidently implement national and international conservation initiatives. Here, we compared four widely-used methods of prioritizing sites in the contiguous United States for conserving species of mammals, birds, amphibians, and reptiles. Specifically, we calculated and mapped species richness, rarity-weighted richness, and two complementarity-based prioritizations (additive benefit function [ABF] and core area zonation [CAZ] in the software Zonation). We compared maps derived from these alternatives with respect to spatial locations and overlap, patch size distributions of the top-30% priorities, and existing ownership and protected-area status. We used species-accumulation curves across ranked priorities to evaluate performance of methods and compared results at 30% total area. Mapped locations and patch sizes of the highest priorities varied by taxonomic class and method of prioritization. Complementarity-based methods (ABF and CAZ) more efficiently represented species than methods based on richness or rarity-weighted richness, especially for taxa with higher beta diversity (amphibians). ABF and CAZ methods also resulted in greater conservation opportunity for the top 30% of priorities compared to maps of richness. Area-based conservation targets, such as the "30 by 30" initiative, must distribute limited resources in ways that safeguard all species. Our results show that spatial locations and configuration, performance, and conservation opportunity vary among prioritization methods and taxonomic classes.

Increasing food production without compromising biodiversity is one of the great challenges for humanity. The aims of my thesis were to define spatial priorities for biodiversity conservation and to evaluate conservation conflicts considering agricultural expansion in the 21 st century. I also tested the effect of globalizing conservation efforts on both food production and biodiversity conservation. I found spatial conflicts between biodiversity conservation and agricultural expansion. However, incorporating agricultural expansion data into the spatial prioritization process can significantly alleviate conservation conflicts, by reducing spatial correlation between the areas under high impact of agriculture and the priority areas for conservation. Moreover, developing conservation blueprints at the global scale, instead of the usual approach based on national boundaries, can benefit both food production and biodiversity. Based on these findings I conclude that the incorporation of agricultural expansion as a key component for defining global conservation strategies should be added to the list of solutions for our cultivated planet.

The concept of green infrastructure (GI) seeks to identify and prioritize areas of high ecological value for wildlife and people, to improve the integration of natural values in landscape planning decisions. In 2018, the canton of Geneva, Switzerland, established a roadmap for biodiversity conservation, which includes the operationalization of GI covering 30% of the territory by 2030. In this paper, we demonstrate a GI mapping framework in the canton of Geneva. Our approach is based on the combined assessment of three ‘pillars’, namely species’ distribution, landscape structure and connectivity, and ecosystem services, to optimize the allocation of conservation actions using the spatial prioritization software, Zonation. The identified priority conservation areas closely overlap existing natural reserves. Including the three pillars in the landscape prioritization should also improve adhesion to the GI idea, without undermining the protection of threatened species. With regards to l...

Reliance on fossil fuels is causing unprecedented climate change and is accelerating environmental degradation and global biodiversity loss. Together, climate change and biodiversity loss, if not averted urgently, may inflict severe damage on ecosystem processes, functions and services that support the welfare of modern societies. Increasing renewable energy deployment and expanding the current protected area network represent key solutions to these challenges, but conflicts may arise over the use of limited land for energy production as opposed to biodiversity conservation. Here, we compare recently identified core areas for the expansion of the global protected area network with the renewable energy potential available from land-based solar photovoltaic, wind energy and bioenergy (in the form of Miscanthus 9 giganteus). We show that these energy sources have very different biodiversity impacts and net energy contributions. The extent of risks and opportunities deriving from renewable energy development is highly dependent on the type of renewable source harvested, the restrictions imposed on energy harvest and the region considered, with Central America appearing at particularly high potential risk from renewable energy expansion. Without restrictions on power generation due to factors such as production and transport costs, we show that bioenergy production is a major potential threat to biodiversity, while the potential impact of wind and solar appears smaller than that of bioenergy. However, these differences become reduced when energy potential is restricted by external factors including local energy demand. Overall, we found that areas of opportunity for developing solar and wind energy with little harm to biodiversity could exist in several regions of the world, with the magnitude of potential impact being particularly dependent on restrictions imposed by local energy demand. The evidence provided here helps guide sustainable development of renewable energy and contributes to the targeting of global efforts in climate mitigation and biodiversity conservation.

Human-induced changes to river loads of nutrients and sediments pose a significant threat to marine ecosystems. Ongoing land-use change can further increase these loads, and amplify the impacts of land-based threats on vulnerable marine ecosystems. Consequently, there is a need to assess these threats and prioritise actions to mitigate their impacts. A key question regarding prioritisation is whether actions in catchments to maintain coastal-marine water quality can be spatially congruent with actions for other management objectives, such as conserving terrestrial biodiversity. In selected catchments draining into the Gulf of California, Mexico, we employed Land ChangeModeller to assess the vulnerability of areas with native vegetation to conversion into crops, pasture, and urban areas. We then used SedNet, a catchment modelling tool, to map the sources and estimate pollutant loads delivered to the Gulf by these catchments. Following these analyses, we used modelled river plumes to ...

Gaps in research exist for country-wide analyses to identify areas of particular importance for biodiversity and ecosystem services to help reach Aichi Target 11 in developing countries. Here we provide a spatial conservation prioritization approach that ranks landowners for maximizing the representation of biodiversity features and ecosystem services, while exploring the trade-offs with agricultural and commercial forestry production and land cost, using Uruguay as a case study. Specifically, we explored four policy scenarios, ranging from a business as usual scenario where only biodiversity and ecosystem services were included in the analysis to a potentially unsustainable scenario where expansion of alternative land uses and economic development would be given higher priority over biodiversity and ecosystem services. At the 17% land target proposed for conservation, the representation levels for biodiversity and ecosystem services were, on average, higher under the business as usual scenario. However, a small addition to the proposed target (from 17 to 20%) allowed to meet same representation levels for biodiversity and ecosystem services, while decreasing conflict with agricultural and commercial forestry production and opportunity costs to local landowners. Under the unsustainable scenario, a striking 41% addition to the conservation target (from 17 to 58%) was needed to meet same representation levels for threatened ecosystems and ecosystem services, which are crucial to sustain human well-being. Our results highlight that more realistic and potentially higher conservation targets, than politically set targets, can be achieved at the country level when sustainable development needs are also accounted for.

Background: Spatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be accounted for during the prioritisation process. We quantified the sensitivity of an SCP application (using software Zonation) to possible sources of uncertainty in data-poor situations, including the use of different sur-rogate options; correction for sampling bias; how to integrate connectivity; the choice of species distribution modelling (SDM) algorithm; how cells are removed from the landscape; and two methods of assigning weights to species (red-list status or prediction uncertainty). Further, we evaluated the effectiveness of the Egyptian protected areas for conservation, and spatially allocated the top priority sites for further on-the-ground evaluation as potential areas for protected areas expansion. Results: Focal taxon (butterflies, reptiles, and mammals), sampling bias, connectivity and the choice of SDM algorithm were the most sensitive parameters; collectively these reflect data quality issues. In contrast, cell removal rule and species weights contributed much less to overall variability. Using currently available species data, we found the current effectiveness of Egypt's protected areas for conserving fauna was low. Conclusions: For SCP to be useful, there is a lower limit on data quality, requiring data-poor countries to improve sampling strategies and data quality to obtain unbiased data for as many taxa as possible. Since our sensitivity analysis may not generalise, conservation planners should use sensitivity analyses more routinely, particularly relying on more than one combination of SDM algorithm and surrogate group, consider correction for sampling bias, and compare the spatial patterns of predicted priority sites using a variety of settings. The sensitivity of SCP to connectivity parameters means that the responses of each species to habitat loss are important knowledge gaps.

Social networks play an important role in facilitating effective and sustained connections between people responsible for regional conservation plans and those responsible for local conservation actions. Yet, few studies have utilized social network analysis in systematic conservation planning initiatives; this, in spite of social network analysis being developed as a structural and relational approach to describe and analyze the characteristics of patterns of relationships that make collaborative efforts more or less effective at solving natural resource management problems. Systematic conservation planning provides a framework for allocating actions in time and space to promote the conservation of biodiversity. Our study discusses three potential contributions of social network analysis to systematic conservation planning: identifying stakeholders and their roles in social networks, and characterizing relationships between them; designing and facilitating strategic networking to strengthen linkages between local and regional conservation initiatives; and prioritizing conservation actions using measures of social connectivity alongside ecological data. We propose that social network analysis has the potential to be a valuable tool to support decision making in conservation planning. We identify challenges and future research questions to be addressed to allow the integration of social network analysis into conservation planning processes.

Social networks play an important role in facilitating effective and sustained connections between people responsible for regional conservation plans and those responsible for local conservation actions. Yet, few studies have utilized social network analysis in systematic conservation planning initiatives; this, in spite of social network analysis being developed as a structural and relational approach to describe and analyze the characteristics of patterns of relationships that make collaborative efforts more or less effective at solving natural resource management problems. Systematic conservation planning provides a framework for allocating actions in time and space to promote the conservation of biodiversity. Our study discusses three potential contributions of social network analysis to systematic conservation planning: identifying stakeholders and their roles in social networks, and characterizing relationships between them; designing and facilitating strategic networking to strengthen linkages between local and regional conservation initiatives; and prioritizing conservation actions using measures of social connectivity alongside ecological data. We propose that social network analysis has the potential to be a valuable tool to support decision making in conservation planning. We identify challenges and future research questions to be addressed to allow the integration of social network analysis into conservation planning processes.