How to resolve conflicting conservation objectives: A decision support tool for the global selection of multi- purpose protected areas

The establishment and maintenance of protected areas(PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values. Introduction Halting biodiversity loss is one of the major global challenges faced by humanity in the 21st century (Pereira et al. 2010; IPBES 2019). Human wellbeing, livelihoods and economics all rely on biodiversity, and an international collaborative effort is needed to conserve it (IPBES 2019; Dasgupta 2021a). A cornerstone of biodiversity conservation are protected areas (PAs). Aichi Target 11 of the Convention on Biological Diversity (CBD) called for an increase in PA coverage to 17% by 2020 for the terrestrial realm, and asked that these PAs should be of particular importance for biodiversity and ecosystem services, ecologically representative and well connected (Convention on Biological Diversity 2010); this goal has only partly been reached (Secretariat of the Convention on Biological Diversity 2020). PAs must be both sustainably funded and effectively managed if they are to protect biological resources, yet only about 20% of all PAs are considered to meet these criteria (Dasgupta 2021b). Meanwhile, many PAs have experienced downgrading, downsizing or degazettement (Golden Kroner et al. 2019) or are threatened by downsizing in the future (Kuempel et al. 2021). Both the allocation of sparse conservation funding for the maintenance of current PAs and the identification of additional sites to expand PA networks frequently require the application of prioritization approaches, and a wealth of methods have been developed. These range from using complex algorithms to optimize conservation networks towards specific conservation goals (e.g. by considering complementarity, connectivity, or cost efficiency (Margules & Pressey 2000; Moilanen et al. 2005, 2009) to identifying global hotspot areas for certain conservation objectives. By focusing on these global hotspots, priority areas for biodiversity conservation have been identified. Initial approaches considered various aspects of biodiversity to be captured such as species richness, endemism, habitat loss, or evolutionary history (Satterfield et al. 1998; Myers et al. 2000; Sechrest et al. 2002). Other approaches highlight the protection of areas that will limit further impacts of global change on biodiversity, for example, by identifying remaining wilderness areas (Watson et al. 2018) or those of irrecoverable carbon storage (Goldstein et al. 2020; Noon et al. 2021). All of these hotspot selection approaches have one aspect in common: they result in the identification of global priority areas for one or more specific conservation objectives. Although it has become increasingly important to align different conservation objectives, e.g. climate and biodiversity protection (Dinerstein et al. 2020; Pörtner et al. 2021), it is often unclear whether different conservation objectives will imply prioritizing the same sites. To date, efforts have compared the spatial alignment of conservation objectives such as terrestrial biodiversity, carbon storage and water quality regulation, and have identified areas with the highest synergies between these objectives (“Nature Map Earth” 2021; Jung et al. 2021). However, there is also evidence for trade-offs between different conservation objectives, e.g. between biodiversity and ecosystem integrity, in a speciesvs. ecosystem-based selection approach (Ceauşu et al. 2015). The weaker the alignment is among different conservation objectives, the greater the influence of priority setting (i.e., favoring certain conservation objectives) on the outcome of site selection approaches. If trade-offs are prevalent, explicit value-based decision making is necessary. The relative priority of different conservation objectives varies among different societal groups, which differ in their demands and values (Peter et al. 2021). Therefore, decisions as to which areas should be prioritized are strongly value based. All of this substantiates the need for a flexible approach to site selection, where different conservation objectives can be explicitly considered and weighed against each other, to facilitate deliberative societal and political decision making. Here, we introduce a transparent site selection approach that allows users to implement area prioritization among existing PAs based on various self-specified conservation objectives. By exclusively using biogeographic information that is publicly available at a global scale, we aimed to identify areas with the highest potential for a range of biodiversity and climate protection objectives. In our approach, we defined six different conservation objectives. We collated a broad set of conservation indicators that reflect these objectives. As a case study to explore the potential and limitations of this approach, we assembled a global dataset of 1347 sites in the context of the Legacy Landscapes Fund (LLF), a recently established foundation that provides long-term funding for protected areas (Legacy Landscapes Fund 2021). We assessed synergies and trade-offs among areas according to the different objectives at a global scale, as well as within biogeographic realms. Finally, we aimed to investigate how priority setting by different societal actors affects site selection by combining the multiple conservation objectives into broader conservation scenarios that weigh each objective according to user-specified priorities. A key aspect in this work was to make our results accessible to a broader audience, including decision makers. We therefore developed an open-source spatial decision support tool to facilitate the priority-based area selection process. Methods To identify sites with a high potential for both biodiversity and climate protection, we defined six overarching conservation objectives (Fig. 1), that address biodiversity conservation, climate protection, and their present and projected future status: 1) high current biodiversity, focusing on overall species richness, species endemism and evolutionary diversity, 2) high current ecosystem integrity, which focuses on pristine areas that have experienced few anthropogenic impacts, 3) high climate protection, which selects for sites that have large, irreplaceable carbon stocks, 4) large size, which prioritizes large sites, 5) high land-use stability, which focuses on the future likelihood of landuse change in the immediate surroundings of sites, and 6) high climatic stability, which highlights sites in which climate change is projected to have low impacts on current biodiversity. These conservation objectives were represented by one or multiple indicators. The biodiversity objective considered as indicators the total species richness of four vertebrate taxa (birds, mammals, amphibians and reptiles) as well as species endemism and evolutionary diversity to capture the amount of biodiversity as well as its irreplaceability; the ecosystem integrity objective considered biodiversity intactness, recent land-use change and the human footprint within the site; the climate protection objective considered the average amount of carbon per hectare that is stored in the vegetation and soil (up to 1 meter below ground) of the site and its vulnerability to typical land conversion; the size objective covers the extent of the site in km2; the land-use stability objective considered the projected change in land-use in a buffer zone around the site, and the climatic stability objective considered the biodiversity change based on the projected future turnover of the four vertebrate taxa and the projected change in tree cover within the site (see supplementary material for a detailed description of all indicators and citations of data sources). These objectives were developed in a discussion process among the broader conservation community. We introduced our approach at a two-day webinar which was attended by 35 experts with a strong conservation background. These included 1) conservation scientists, 2) international conservation NGOs, 3) the financial sector, and 4) policy sectors, in particular the German Federal Ministry for Economic Cooperation and Development (BMZ). These experts provided feedback on the objectives and indicators using a questionnaire (see supplementary material). They were asked to: 1) report any missing objectives, 2) report any missing indicators that should be included in the objectives and 3) rank the suggested objectives by their personal preferences. To translate personal preferences into site selection, the resulting ranks for each individual indicator were scaled from zero to one. Each objective consists of several underlying indicators (datasets), so by taking the mean across all indicators per objective these were weighted equally. These mean scores were then taken as input to weigh the different objectives against each other. To assess synergies and trade-offs among the conservation objectives, we used the LLF as a case study to assemble a global dataset of sites. The LL