Ana S. L. Rodrigues

Global Biodiversity Conservation Priorities

The location of and threats to biodiversity are distributed unevenly, so prioritization is essential to minimize biodiversity loss. To address this need, biodiversity conservation organizations have proposed nine templates of global priorities over the past decade. Here, we review the concepts, methods, results, impacts, and challenges of these prioritizations of conservation practice within the theoretical irreplaceability/vulnerability framework of systematic conservation planning. Most of the templates prioritize highly irreplaceable regions; some are reactive (prioritizing high vulnerability), and others are proactive (prioritizing low vulnerability). We hope this synthesis improves understanding of these prioritization approaches and that it results in more efficient allocation of geographically flexible conservation funding.

Effectiveness of the global protected area network in representing species diversity

The Fifth World Parks Congress in Durban, South Africa, announced in September 2003 that the global network of protected areas now covers 11.5% of the planets land surface. This surpasses the 10% target proposed a decade earlier, at the Caracas Congress, for 9 out of 14 major terrestrial biomes. Such uniform targets based on percentage of area have become deeply embedded into national and international conservation planning. Although politically expedient, the scientific basis and conservation value of these targets have been questioned. In practice, however, little is known of how to set appropriate targets, or of the extent to which the current global protected area network fulfils its goal of protecting biodiversity. Here, we combine five global data sets on the distribution of species and protected areas to provide the first global gap analysis assessing the effectiveness of protected areas in representing species diversity. We show that the global network is far from complete, and demonstrate the inadequacy of uniform—that is, ‘one size fits all’—conservation targets.

Global gap analysis: Priority regions for expanding the global protected-area network

Abstract Protected areas are the single most important conservation tool. The global protected-area network has grown substantially in recent decades, now occupying 11.5% of Earths land surface, but such growth has not been strategically aimed at maximizing the coverage of global biodiversity. In a previous study, we demonstrated that the global network is far from complete, even for the representation of terrestrial vertebrate species. Here we present a first attempt to provide a global framework for the next step of strategically expanding the network to cover mammals, amphibians, freshwater turtles and tortoises, and globally threatened birds. We identify unprotected areas of the world that have remarkably high conservation value (irreplaceability) and are under serious threat. These areas concentrate overwhelmingly in tropical and subtropical moist forests, particularly on tropical mountains and islands. The expansion of the global protected-area network in these regions is urgently needed to prevent the loss of unique biodiversity.

Ecophylogenetics: advances and perspectives

Ecophylogenetics can be viewed as an emerging fusion of ecology, biogeography and macroevolution. This new and fast‐growing field is promoting the incorporation of evolution and historical contingencies into the ecological research agenda through the widespread use of phylogenetic data. Including phylogeny into ecological thinking represents an opportunity for biologists from different fields to collaborate and has provided promising avenues of research in both theoretical and empirical ecology, towards a better understanding of the assembly of communities, the functioning of ecosystems and their responses to environmental changes. The time is ripe to assess critically the extent to which the integration of phylogeny into these different fields of ecology has delivered on its promise. Here we review how phylogenetic information has been used to identify better the key components of species interactions with their biotic and abiotic environments, to determine the relationships between diversity and ecosystem functioning and ultimately to establish good management practices to protect overall biodiversity in the face of global change. We evaluate the relevance of information provided by phylogenies to ecologists, highlighting current potential weaknesses and needs for future developments. We suggest that despite the strong progress that has been made, a consistent unified framework is still missing to link local ecological dynamics to macroevolution. This is a necessary step in order to interpret observed phylogenetic patterns in a wider ecological context. Beyond the fundamental question of how evolutionary history contributes to shape communities, ecophylogenetics will help ecology to become a better integrative and predictive science.

Coverage Provided by the Global Protected-Area System: Is It Enough?

Abstract Protected-area targets of 10% of a biome, of a country, or of the planet have often been used in conservation planning. The new World Database on Protected Areas shows that terrestrial protected-area coverage now approaches 12% worldwide. Does this mean that the establishment of new protected areas can cease? This was the core question of the “Building Comprehensive Protected Area Systems” stream of the Fifth World Parks Congress in Durban, South Africa, in 2003. To answer it requires global gap analysis, the subject of the special section of BioScience for which this article serves as an introduction. We also provide an overview of the extraordinary data sets now available to allow global gap analysis and, based on these, an assessment of the degree to which existing protected-area systems represent biodiversity. Coverage varies geographically, but is less than 2% for some bioregions, and more than 12% of 11,633 bird, mammal, amphibian, and turtle species are wholly unrepresented. The global protected-area systems are far from complete.

Maximising phylogenetic diversity in the selection of networks of conservation areas

Phylogenetic diversity (PD) is a biodiversity measure that takes account of phylogenetic relationships (hence evolutionary history) between taxa. It may therefore provide a better currency for conservation evaluation than taxonomic richness. Here, we demonstrate that, contrary to recent assertions, optimisation tools can be used to maximise PD in the context of complementary reserve selection, and that the spatial overlap between sets of sites maximising genus diversity and PD cannot be used as evidence that the first measure is a good surrogate for the second. Nevertheless, in our own analyses using data on bird genera in northwest South Africa we found that near equally effective results are obtained in the selection of complementary sets of sites when maximising for each of these two measures of biodiversity.

Protected Areas and Effective Biodiversity Conservation

Increasing the collective contribution of protected areas toward preventing species extinctions requires the strategic allocation of management efforts. Although protected areas (PAs) cover 13% of Earths land (1), substantial gaps remain in their coverage of global biodiversity (2). Thus, there has been emphasis on strategic expansion of the global PA network (3–5). However, because PAs are often understaffed, underfunded, and beleaguered in the face of external threats (6, 7), efforts to expand PA coverage should be complemented by appropriate management of existing PAs. Previous calls for enhancing PA management have focused on improving operational effectiveness of each PA [e.g., staffing and budgets (6)]. Little guidance has been offered on how to improve collective effectiveness for meeting global biodiversity conservation goals (3). We provide guidance for strategically allocating management efforts among and within existing PAs to strengthen their collective contribution toward preventing global species extinctions.

Boom-and-bust development patterns across the Amazon deforestation frontier.

Boom and Bust The Brazilian Amazon is renowned for its biodiversity and for its influence on climate regulation and geochemical cycles. It is also one of the countrys poorest regions. For decades, much economic development has been pursued through conversion of forest for agriculture and cattle-ranching. Rodrigues et al. (p. 1435) investigated whether this pattern of land use brings lasting prosperity by analyzing data on the economic development of nearly 300 municipalities across the deforestation frontier. Relative development, in terms of life expectancy, literacy, and standard of living, increases as deforestation begins but then declines again as the frontier passes through. As a result, pre- and postfrontier levels of development are similarly low, indicating a pattern of boom and bust. Rainforest loss in the Amazon is associated with ephemeral increase in people’s relative prosperity. The Brazilian Amazon is globally important for biodiversity, climate, and geochemical cycles, but is also among the least developed regions in Brazil. Economic development is often pursued through forest conversion for cattle ranching and agriculture, mediated by logging. However, on the basis of an assessment of 286 municipalities in different stages of deforestation, we found a boom-and-bust pattern in levels of human development across the deforestation frontier. Relative standards of living, literacy, and life expectancy increase as deforestation begins but then decline as the frontier evolves, so that pre- and postfrontier levels of human development are similarly low. New financial incentives and policies are creating opportunities for a more sustained development trajectory that is not based on the depletion of nature and ecosystem services.

ENERGY, SPECIES RICHNESS, AND HUMAN POPULATION SIZE: CONSERVATION IMPLICATIONS AT A NATIONAL SCALE

The maintenance of biodiversity rests on understanding and resolving conflict between patterns of species occurrence and human activity. Recent debate has centered on the relationship between species richness and human population density. However, conclusions have been limited by the lack of investigations of these relationships for individual countries, at which level most practical conservation actions are determined, and for a spatial resolution at which practical conservation planning takes place. Here, we report the results of the first such analysis, for birds in South Africa. Species richness and human density are positively correlated, apparently because both respond positively to increasing levels of primary productivity. High species richness is maintained by currently designated reserves, but the areas surrounding these have higher human population densities than expected by chance, placing the reserves under increasing external pressure. Not all species lie within protected areas, but the options are limited for building on the present network to generate a more comprehensive one, which protects all species and significantly reduces the conflict with human activities by designating new reserves in areas with lower human populations. Ultimately, the only solution to the conflict between biodiversity and people is likely to be individual-based regulation of human population size.

Optimisation in reserve selection procedures-why not?

Linear programming techniques provide an appropriate tool for solving reserve selection problems. Although this has long been known, most published analyses persist in the use of intuitive heuristics, which cannot guarantee the optimality of the solutions found. Here, we dispute two of the most common justifications for the use of intuitive heuristics, namely that optimisation techniques are too slow and cannot solve the most realistic selection problems. By presenting an overview of processing times obtained when solving a diversity of reserve selection problems, we demonstrate that most of those published could almost certainly be solved very quickly by standard optimisation software using current widely available computing technology. Even for those problems that take longer to solve, solutions with low levels of sub-optimality can be obtained quite quickly, presenting a better alternative to intuitive heuristics.