Area-based conservation is a widely used approach for maintaining biodiversity, and there are ongoing discussions over what is an appropriate global conservation area coverage target. To inform such debates, it is necessary to know the extent and ecological representativeness of the current conservation area network, but this is hampered by gaps in existing global datasets. In particular, although data on privately and community-governed protected areas and other effective area-based conservation measures are often available at the national level, it can take many years to incorporate these into official datasets. This suggests a complementary approach is needed based on selecting a sample of countries and using their national-scale datasets to produce more accurate metrics. However, every country added to the sample increases the costs of data collection, collation and analysis. To address this, here we present a data collection framework underpinned by a spatial prioritization algorithm, which identifies a minimum set of countries that are also representative of 10 factors that influence conservation area establishment and biodiversity patterns. We then illustrate this approach by identifying a representative set of sampling units that cover 10% of the terrestrial realm, which included areas in only 25 countries. In contrast, selecting 10% of the terrestrial realm at random included areas across a mean of 162 countries. These sampling units could be the focus of future data collation on different types of conservation area. Analysing these data could produce more rapid and accurate estimates of global conservation area coverage and ecological representativeness, complementing existing international reporting systems.

Protected areas (PAs) have been selected using either subjective or objective criteria applied to an extremely limited subset of biodiversity. Improved availability of species distribution data, better statistical tools to predict species distributions and algorithms to optimize spatial conservation planning allow many impediments to be overcome, particularly on small islands. This study analyses whether 219 species are adequately protected by PAs on Pico Island (the Azores, Portugal), and if they are as efficient as possible, maximizing species protection while minimizing costs. We performed distribution modelling of species’ potential distributions, proposed individual conservation targets (considering the context of each species in the archipelago and their current conservation status) to determine the efficiency of current PAs in meeting such targets and identify alternative or complementary areas relevant for conservation. Results showed that current PAs do not cover all taxa, leaving out important areas for conservation. We demonstrate that by using optimization algorithms it is possible to include most species groups in spatial conservation planning in the Azores with the current resources. With increasing availability of data and methods, this approach could be readily extended to other islands and regions with high endemism levels.

Marine protected areas (MPAs) are increasingly being considered and used for the management of fisheries targeting mobile fish populations. Here, the recent modelling literature on MPA effects for mobile fish populations and their fisheries is reviewed. Modelling studies conducted since 2011 have filled a considerable number of knowledge gaps on the impacts of MPAs for species exhibiting home-range behaviour, nomadic movements or behavioural polymorphism, and on the effects of “targeted MPAs”, which aim to protect relatively small areas where migratory fishes spend an inordinate fraction of time or are highly vulnerable to fishing (e.g., nursery or spawning zones). Also, in recent years, two studies investigated the consequences of MPAs targeting highly migratory (tuna-like) fish populations for the first time in the history of MPA modelling. Recent modelling studies found that MPAs aimed at protecting mobile species may have positive conservation effects under a relatively wide range of situations, but may generate long-term fisheries benefits only under a very limited set of conditions. In particular, MPAs were not found to be beneficial for the fisheries targeting highly migratory populations. Strategies producing both conservation and fisheries benefits were identified, which depend on fish movement patterns and numerous aspects of fish life history and fisheries dynamics. However, in view of the diversity of fish movement patterns in MPA systems and current dynamics in resource management, it is clear that additional modelling work is needed to fully understand how protected areas affect mobile fish populations and their fisheries and to be able to implement pertinent MPAs. In particular, future modelling studies should systematically assess the effects of MPAs in relation to other management tools to find strategies that are most effective in meeting management objectives, and explore the impacts of “dynamic” MPAs that follow highly migratory fish populations in space and time.

Effective conservation of rare plant species requires a detailed understanding of their unique distributions and habitat requirements to identify conservation targets. Research suggests that local conservation efforts may be one of the best means for accomplishing this task. We conducted a geographical analysis of the local distributions of rare plants in Napa County, California, to identify spatial relationships with individual habitat types. We measured the potential contribution of individual habitats to rare plant conservation by integrating analyses on overall diversity, species per area, specificity-weighted richness, presence of hotspots, and the composition of the rare plant community in each habitat type. This combination of analyses allowed us to determine which habitats are most significant for rare plant conservation at a local scale. Our analyses indicated that several habitat types were consistently associated with rare plant species. In broad terms, grasslands, oak forests, coniferous forests, wetlands, serpentines, chaparral, and rock outcrops were most consistently highlighted. No single habitat stood out in every analysis however, and therefore we conclude that careful selection of an assemblage of habitats that best represents diverse, restricted and unique rare plant communities will be the most efficient approach to protecting rare plant habitat at local scales. Accordingly we present a means of identifying conservation targets and protecting global biodiversity through local efforts.