Species and space: a combined gap analysis to guide management planning of conservation areas

Abstract

Context With accelerating global declines in biodiversity, establishment and expansion of conservation areas (CAs) have increasingly been advocated in recent decades. Gap analysis has been useful to evaluate the sufficiency and performance of CAs. Objectives Researchers often identify putative gaps in the protection of biodiversity in CA networks, drawing on evidence from species occurrence patterns (i.e., representation), yet the effect on the gap analyses of the spatial configuration of CAs is poorly understood. Methods Focusing on two large, charismatic carnivores of western Asia, Persian leopard and Asiatic cheetah, we used species distribution models (SDMs) to map potentially suitable habitats throughout the region. We calculated species representation for four categories of CAs within the conservation network in Iran and used a new application of graph theory to include their spatial configuration into our gap analysis. We then regressed species representation against spatial configuration to provide more insights into the performance of different categories of CAs. Results Results showed that the existing CA network conserves only 32% of the suitable habitats for the two species. Leveraging spatial configuration of the conservation areas into the gap analysis, however, revealed that the recentlyestablished less strictly CAs disproportionately provide a higher contribution to the collective effectiveness of the entire conservation network. Conclusions We introduce network bias as a new concept in reserve design and argue that incorporating spatial configuration into CA gap analysis improves the ability Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporationto evaluate the effectiveness of reserve network designs, and is an important decision support tool for integrated conservation planning. Response to Reviewers:Reviewer 1: Overall, it is a nicely written paper, which investigate the distribution range of two species of conservation importance in Iran and also the importance of existing conservation areas in providing structural connectivity among the species' core habitats. I have a few major concerns with the analysis used in the methods that authors should address before the manuscript being accepted.*Response: We are glad the reviewer thought the paper addressed an important and novel topic and appreciate the positive feedback on its overall presentation. KeywordsThe list of keywords is not fit to the paper and aims. Please re-write the keywords based on the aims and findings. Also write "species distribution models" instead of SDM. *Response: Done. We changed the keywords and wrote species distribution models instead of SDM. It is worth mentioning that we tried to not use keywords from the title of the manuscript. L28: As you know, PAs in Iran are classified into five main groups (i.e. national parks, wildlife refuges, protected areas, natural monuments, and no-hunting area). One of these classes are protected areas. So, I thinks that authors use a better title for overall ...

Prioritizing areas for conservation outside the existing protected area network in Bhutan: the use of multi-species, multi-scale habitat suitability models

“…When prioritizing land use and protected area establishment, past studies have frequently intersected connectivity models with protected areas and prioritized areas for protection based on the strength, centrality or connectedness of areas outside the existing connectivity network (Cushman et al 2018;Kaszta et al 2020;Ahmadi et al 2020;Ashrafzadeh et al 2020). These approaches, however, don't use formal optimization to select or prioritize new areas for protection and often have been limited to one (Cushman et al 2018) or a few (Cushman et al 2013) species.…”

Identifying priority core habitats and corridors for effective conservation of brown bears in Iran

“…Among the identified core habitats, the highest overlap between core habitats and protected areas was observed for core 1 and core 2. These two core habitats have also been documented to have a high potential for supporting other large carnivores of conservation concern, such as Persian leopards (Panthera pardus saxicolor) 86 . However, the coverage of protected areas could be improved for other identified core habitats which our analysis shows are relatively unprotected.…”

“…The dPC and dIIC indices are frequently used as connectivity measures in conservation prioritization studies 42,43,86,87 . The dIIC index considers both habitat amount and habitat reachability across the habitat network, and linkages as dispersal events between patches 84,86 . dIIC also quantifies the loss of connectivity if a patch is removed from the habitat network and can be decomposed into dIICflux (dIICf), dIICconnector (dIICc), dIICintra (dIICi).…”

“…dIIC also quantifies the loss of connectivity if a patch is removed from the habitat network and can be decomposed into dIICflux (dIICf), dIICconnector (dIICc), dIICintra (dIICi). dPC also considers both habitat amount and habitat reachability, and the probability of dispersal between patches, and can be decomposed into dPCflux (dPCf), dPCconnector (dPCc) and dPCintra (dPCi) 84,86 . dPCintra and dIICintra measure intrapatch connectivity, while flux fraction of a particular node (dPCflux and dIICflux) reflects both patch attributes (e.g., area of suitable habitats) and its position within the landscape, while connector fraction (dIICconnector and dPCconnector) depend only on the topological position of a patch in the landscape 88 .…”

“…Connector fraction quantifies the importance of the node as a stepping-stone for dispersal, i.e. facilitating dispersal between distant nodes 86 . We used a distance-probability value of 0.5 and 0.05 for minimum and maximum dispersal distances, respectively, as recommended by Saura and Torne 84 .…”