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Conservation priorities that are based on species distribution, endemism, and vulnerability may underrepresent biologically unique species as well as their functional roles and evolutionary histories. To ensure that priorities are biologically comprehensive, multiple dimensions of diversity must be considered. Further, understanding how the different dimensions relate to one another spatially is important for conservation prioritization, but the relationship remains poorly understood. Here, we use spatial conservation planning to (i) identify and compare priority regions for global mammal conservation across three key dimensions of biodiversity—taxonomic, phylogenetic, and traits—and (ii) determine the overlap of these regions with the locations of threatened species and existing protected areas. We show that priority areas for mammal conservation exhibit low overlap across the three dimensions, highlighting the need for an integrative approach for biodiversity conservation. Additionally, currently protected areas poorly represent the three dimensions of mammalian biodiversity. We identify areas of high conservation priority among and across the dimensions that should receive special attention for expanding the global protected area network. These highpriority areas, combined with areas of high priority for other taxonomic groups and with social, economic, and political considerations, provide a biological foundation for future conservation planning efforts.

ContextSpatial conservation prioritization (SCP) has most often been applied to the design of reserve network expansion. In addition to occurrences of species and habitats inside protected area candidate sites, one may also be interested about network-level connectivity considerations.ObjectivesWe applied SCP to the identification of ecological networks to inform the development of a new regional plan for the region of Uusimaa (South-Finland, including the Finnish capital district).MethodsInput data were 59 high-quality layers of biotope and species distribution data. We identified ecological networks based on a combination of a Zonation balanced priority ranking map and a weighted range size rarity map, to account for both relative and absolute conservation values in the process. We also identified ecological corridors between protected areas and other ecologically high-priority areas using the corridor retention method of Zonation. Furthermore, we identified candidate sites for habitat restoration.ResultsWe found seven large ecological networks (132–1201 km2) which stand out from their surrounding landscape in terms of ecological value and have clear connectivity bottlenecks between them. Highest restoration needs were found between large high-priority sites that are connected via remnant habitat fragments in comparatively highly modified areas.ConclusionsLand conversion should be avoided in areas of highest ecological priorities and network-level connectivity. Restoration should be considered for connectivity bottlenecks. Methods described here can be applied in any location where relevant spatial data are available. The present results are actively used by the regional council and municipalities in the region of Uusimaa.

ContextAccording to Global Biodiversity Outlook 5, the Aichi Biodiversity Target regarding protected areas (PAs) has been partially achieved with limited progress in valid performance for biodiversity conservation and effective management. This suggests that not only the spatial planning of PAs but also the spatial prioritization for PAs under different management scenarios need more prudent decision-making.ObjectivesWe aim to develop a comprehensive approach to identify and prioritize PAs to maximize the effectiveness of biodiversity conservation while minimize the conservation costs.MethodsTaking Beijing-Tianjin-Hebei region as a case study, we consider the supply and demand of ecosystem services, and landscape connectivity to identify PAs. Systematic conservation planning decision support tool Marxan was employed to identify the priority areas of PAs under multi-target scenarios. The conservation costs, the critical step in the planning process, was estimated using habitat quality evaluation module embedding in InVEST model.ResultsThe results showed that the conservation costs for construction land and unused land were the highest, while the costs for forest land, grassland, and farmland were very low. Sensitivity analysis confirmed the most appropriate conservation goal was 50% of the total area. Therefore, we generated spatial prioritization outcomes based on this target. The highest priority area was mainly located in the northwest of Beijing, the north of Chengde, and the east of Zhangjiakou.ConclusionsIt is concluded that the proposed approach helps decision-makers to identify spatial prioritization for biodiversity conservation based on different scenarios and also yields insights into systematic conservation planning and management.

Aim Deforestation is rapidly altering Southeast Asian landscapes, resulting in some of the highest rates of habitat loss worldwide. Among the many species facing declines in this region, clouded leopards rank notably for their ambassadorial potential and capacity to act as powerful levers for broader forest conservation programmes. Thus, identifying core habitat and conservation opportunities are critical for curbing further Neofelis declines and extending umbrella protection for diverse forest biota similarly threatened by widespread habitat loss. Furthermore, a recent comprehensive habitat assessment of Sunda clouded leopards (N. diardi) highlights the lack of such information for the mainland species (N. nebulosa) and facilitates a comparative assessment. Location Southeast Asia. Methods Species–habitat relationships are scale‐dependent, yet <5% of all recent habitat modelling papers apply robust approaches to optimize multivariate scale relationships. Using one of the largest camera trap datasets ever collected, we developed scale‐optimized species distribution models for two con‐generic carnivores, and quantitatively compared their habitat niches. Results We identified core habitat, connectivity corridors, and ranked remaining habitat patches for conservation prioritization. Closed‐canopy forest was the strongest predictor, with ~25% lower Neofelis detections when forest cover declined from 100 to 65%. A strong, positive association with increasing precipitation suggests ongoing climate change as a growing threat along drier edges of the species’ range. While deforestation and land use conversion were deleterious for both species, N. nebulosa was uniquely associated with shrublands and grasslands. We identified 800 km2 as a minimum patch size for supporting clouded leopard conservation. Main conclusions We illustrate the utility of multi‐scale modelling for identifying key habitat requirements, optimal scales of use and critical targets for guiding conservation prioritization. Curbing deforestation and development within remaining core habitat and dispersal corridors, particularly in Myanmar, Laos and Malaysia, is critical for supporting evolutionary potential of clouded leopards and conservation of associated forest biodiversity.

Aim: To quantify and compare species coverage in priority areas for conservation identified using species richness as opposed to approaches that use individual species range maps. Location: Global. Methods: We compare the coverage of species when global priority areas for conservation are identified based on (1) twelve species richness maps of all and small-range amphibians, birds and mammals and all and small-range threatened (i.e., vulnerable, endangered and critically endangered) species; (2) weighted range size rarity, a richness measure corrected for range size; and (3) a complementarity-based analysis including species range maps for 21,075 terrestrial vertebrate species listed by the International Union for the Conservation of Nature. We also assessed whether any combination of small-range and/or threatened species richness could be a suitable surrogate for a complementarity-based analysis by assessing species coverage in priority areas located using (1) richness of small-range species only; (2) richness of all threatened species only; and (3) richness of small-range and threatened species. Results: Our results show clear differences in the spatial pattern of priority areas for conservation among the prioritizations based on species richness, weighted range size rarity and species range maps, with the species richness-based priority areas being highly aggregated in the tropics and the species range map priority areas being more evenly spread among the global terrestrial area. We also find that identifying priority areas for conservation using species richness produces a lower coverage of species than priority areas based on complementarity methods and identified using species range maps, where just one species was left without any protection. Main Conclusions: As methods and software currently exist for processing large numbers of individual species distribution maps in spatial prioritization, the use of species richness appears to be an unnecessary simplification of biodiversity pattern.

Aim: To propose and compare priority sites for conservation and restoration of woody plants under diverse climate and land use scenarios, considering socio-economic costs, presence of protected areas and distribution of forest remnants. Location: The Atlantic Forest Biodiversity Hotspot, Brazil. Methods: We used ecological niche modelling to estimate geographical distributions for 2,255 species under current and future climate scenarios, which we analysed in relation to spatially explicit land use projections, maps of forest remnants derived from remote sensing and socio-economic variables for each municipality within the Atlantic Forest region. We identified spatial priorities that complement the current network of protected areas under three different prioritization scenarios: (1) conservation of existing forest remnants only; (2) conservation of remnants followed by restoration of degraded habitat; and (3) unconstrained actions, in which management location is not defined a priori. We compared our results under different levels of land protection, with targets of 10%, 17% and 20% of the Atlantic Forest extent. Results: Current forest remnants cover only 12% of the Atlantic Forest, so targets of 17% and 20% were achieved only through active restoration. Targets of 17% and 20% captured most species and represented on average 26%-34% of species' distributions. The spatial pattern of degraded habitats negatively affected representation of biodiversity and implied higher costs and reduced efficiency of planning. We did not observe major differences between conservation prioritizations based on contrasting climate change scenarios. Main conclusions: Protection of forest remnants alone will not suffice to safeguard woody plant species under climate and land use changes; therefore, restoration actions are urgently needed in the Atlantic Forest. With integrated management actions and multicriterion nationwide planning, reaching the 17% of land protection of Aichi biodiversity targets will constitute an important step towards protecting Atlantic Forest biodiversity.

1. Range maps represent the geographic distribution of species, and they are commonly used to determine species coverage within protected areas and to find additional places needing protection. However, range maps are characterized by commission errors, where species are thought to be present in locations where they are not. When available, habitat suitability models can reduce commission errors in range maps, but these models are not always available. Adopting a coarse spatial resolution is often seen as an alternative approach for reducing the effect of commission errors, but this comes with poorly explored conservation trade-offs. 2. Here, we characterize these trade-offs by identifying scenarios of protected area expansion for the world's threatened terrestrial mammals under different resolutions (10-200 km) and distribution data deriving from range maps and habitat suitability models. 3. We found that planning new protected areas using range maps results in an overestimation of the species protection level when compared with habitat suitability models (which are more closely related to species presence). This overestimation increases when more area is selected for protection and is higher when higher spatial resolutions are employed. 4. Adopting coarse resolutions reduced the overestimation of species protection and also halved the spatial incongruence between protected areas prioritized from range maps or habitat suitability models. However, this came at a very high cost, with an area of up to four times greater (12 M km² vs. 3 M km²) needed to adequately protect all species. 5. Synthesis and applications. Our findings demonstrate that adopting coarse resolutions in protected area planning results in unsustainable increases in costs, with limited benefits in terms of reducing the effect of commission errors in species range maps. We recommend that, if some level of uncertainty is acceptable to practitioners, using range maps at resolutions of 20-30 km is the best compromise for reducing the effect of commission errors while maintaining cost-efficiency in conservation analyses.

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 21st 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.

There is high-level political support for the use of green infrastructure (GI) across Europe, to maintain viable populations and to provide ecosystem services (ES). Even though GI is inherently a spatial concept, the modern tools for spatial planning have not been recognized, such as in the recent European Environment Agency (EEA) report. We outline a toolbox of methods useful for GI design that explicitly accounts for biodiversity and ES. Data on species occurrence, habitats, and environmental variables are increasingly available via open-access internet platforms. Such data can be synthesized by statistical species distribution modeling, producing maps of biodiversity features. These, together with maps of ES, can form the basis for GI design. We argue that spatial conservation prioritization (SCP) methods are effective tools for GI design, as the overall SCP goal is cost-effective allocation of conservation efforts. Corridors are currently promoted by the EEA as the means for implementing GI design, but they typically target the needs of only a subset of the regional species pool. SCP methods would help to ensure that GI provides a balanced solution for the requirements of many biodiversity features (e.g., species, habitat types) and ES simultaneously in a cost-effective manner. Such tools are necessary to make GI into an operational concept for combating biodiversity loss and promoting ES.

Conservation policies and environmental impact assessments commonly target threatened species and habitats. Nevertheless, macroecological research provides reasons why also common species should be considered. We investigate the consequences of focussing solely on legally protected species and habitats in a spatial conservation planning context using a comprehensive, benthic marine data set from the northern Baltic Sea. Using spatial prioritization and surrogacy analysis, we show that the common approach in conservation planning, where legally listed threatened species and habitats are the focus of conservation efforts, could lead to poor outcomes for common species (and therefore biodiversity as a whole), allowing them to decline in the future. If conservation efforts were aimed solely at threatened species, common species would experience a loss of 62% coverage. In contrast, if conservation plans were based only on common species, threatened species would suffer a loss of 1%. Threatened species are rare and their ecological niches distinct, making them poor surrogates for biodiversity. The best results are achieved by unified planning for all species and habitats. The minimal step towards acknowledging common species in conservation planning would be the inclusion of the richness of common species, complemented by information on indicator species or species of high importance for ecosystem functioning. The trade-off between planning for rare and common species should be evaluated, to minimize losses to biodiversity.