Global conservation strategies for two clades of snakes: combining taxon-specific goals with general prioritization schemes

Identifying the geographic distribution pattern of venomous snakes and regions of high snakebite risk in Iran

We describe species richness patterns of venomous snakes in Iran in order to produce snakebite risk prediction maps and identify gaps in regional health care centers capable of managing snakebites. We digitized distribution maps from the literature, Global Biodiversity Information Facility (GBIF), and the results of our own field studies of 24 terrestrial venomous snake species (including 4 endemic to Iran). Species richness patterns were associated with eight environmental factors. The variables have been extracted from the WorldClim dataset (bio12 = annual precipitation, bio15 = precipitation seasonality, bio17 = precipitation of the driest quarter, bio2 = mean diurnal range, bio3 = isothermality (bio2/bio7), bio4 = temperature seasonality, bio9 = mean temperature of the driest quarter and slope). Based on spatial analyses, species richness in Iran is highly affected by three environmental variables (bio12, 15, and 17) associated with precipitation. The relationship patterns among these predictors and species richness were strong and linear. The hotspot regions for venomous snakes species are concentrated on the western to southwestern and north to northeastern regions of Iran, which is partially consistent with the known Irano-Anatolian biodiversity hotspot. Because of the high number of endemic species and climatic conditions on the Iranian Plateau, the venoms of snakes distributed in those areas may contain novel properties and components.

Cheap and nasty? The potential perils of using management costs to identify global conservation priorities

The financial cost of biodiversity conservation varies widely around the world and such costs should be considered when identifying countries to best focus conservation investments. Previous global prioritizations have been based on global models for protected area management costs, but this metric may be related to other factors that negatively influence the effectiveness and social impacts of conservation. Here we investigate such relationships and first show that countries with low predicted costs are less politically stable. Local support and capacity can mitigate the impacts of such instability, but we also found that these countries have less civil society involvement in conservation. Therefore, externally funded projects in these countries must rely on government agencies for implementation. This can be problematic, as our analyses show that governments in countries with low predicted costs score poorly on indices of corruption, bureaucratic quality and human rights. Taken together, our results demonstrate that using national-level estimates for protected area management costs to set global conservation priorities is simplistic, as projects in apparently low-cost countries are less likely to succeed and more likely to have negative impacts on people. We identify the need for an improved approach to develop global conservation cost metrics that better capture the true costs of avoiding or overcoming such problems. Critically, conservation scientists must engage with practitioners to better understand and implement context-specific solutions. This approach assumes that measures of conservation costs, like measures of conservation value, are organization specific, and would bring a much-needed focus on reducing the negative impacts of conservation to develop projects that benefit people and biodiversity.