Mapping evolutionary process: a multi-taxa approach to conservation prioritization.

Human-induced land use changes are causing extensive habitat fragmentation. As a result, many species are not able to shift their ranges in response to climate change and will likely need to adapt in situ to changing climate conditions. Consequently, a prudent strategy to maintain the ability of populations to adapt is to focus conservation efforts on areas where levels of intraspecific variation are high. By doing so, the potential for an evolutionary response to environmental change is maximized. Here, we use modeling approaches in conjunction with environmental variables to model species distributions and patterns of genetic and morphological variation in seven Ecuadorian amphibian, bird, and mammal species. We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity. Reserves selected using species richness and complementarity showed little overlap with those based on genetic and morphological variation. Priority areas for intraspecific variation were mainly located along the slopes of the Andes and were largely concordant among species, but were not well represented in existing reserves. Our results imply that in order to maximize representation of intraspecific variation in reserves, genetic and morphological variation should be included in conservation prioritization.

Modeling environmentally associated morphological and genetic variation in a rainforest bird, and its application to conservation prioritization.

To better understand how environment shapes phenotypic and genetic variation, we explore the relationship between environmental variables across Ecuador and genetic and morphological variation in the wedge-billed woodcreeper (Glyphorynchus spirurus), a common Neotropical rainforest bird species. Generalized dissimilarity models show that variation in amplified fragment length polymorphism markers was strongly associated with environmental variables on both sides of the Andes, but could also partially be explained by geographic distance on the western side of the Andes. Tarsus, wing, tail, and bill lengths and bill depth were well explained by environmental variables on the western side of the Andes, whereas only tarsus length was well explained on the eastern side. Regions that comprise the highest rates of genetic and phenotypic change occur along steep elevation gradients in the Andes. Such environmental gradients are likely to be particularly important for maximizing adaptive diversity to minimize the impacts of climate change. Using a framework for conservation prioritization based on preserving ecological and evolutionary processes, we found little overlap between currently protected areas in Ecuador and regions we predicted to be important in maximizing adaptive variation.

Efficiency and concordance of alternative methods for minimizing opportunity costs in conservation planning.

Scarce resources and competing land-use goals necessitate efficient biodiversity conservation. Combining multicriteria analysis with conservation decision-support tools improves efficiency of conservation planning by maximizing outcomes for biodiversity while minimizing opportunity costs to society. An opportunity cost is the benefit that could have been received by taking an alternative course of action (i.e., costs to society of protecting an area for biodiversity rather than developing it for some other use). Although different ways of integrating multiple opportunity costs into conservation planning have been suggested, there have been no tests as to which method is most efficient. We compared the relative efficiency of 3 such procedures(Faith & Walker [1996], Sarkar et al. [2004], and a procedure of our own design) in a systematic conservation-planning framework for the Milne Bay Province of Papua New Guinea. We devised 14 opportunity costs and assigned these to 3 scenarios representing different conservation planning concerns: food security, macro-economic development, and biodiversity persistence. For each scenario, we compared the efficiency of the 3 methods in terms of amount of biodiversity protected relative to total expenditure for each opportunity cost. All 3 methods captured similar amounts of biodiversity, but differed in total cost. Our method had the least overall cost and was therefore most efficient. Nevertheless, there was a high correlation and geographical concordance among all 3 methods, indicating a high degree of spatial overlap. This suggests that choosing an appropriate approach may often depend on contextual factors related to the design of the planning question, rather than efficiency alone.