Scientific knowledge of species and the ecosystems they inhabit is the cornerstone of modern conservation. However, research effort is not spread evenly among taxa (taxonomic bias), which may constrain capacity to identify conservation risk and to implement effective responses. Addressing such biases requires an understanding of factors that promote or constrain the use of a particular species in research projects. To this end, we quantified conservation science knowledge of the world's extant non-marine mammal species (n = 4108) based on the number of published documents in journals indexed on Clarivate Analytics' Web of Science TM. We use an innovative hurdle model approach to assess the relative importance of several ecological, biogeographical and cultural factors for explaining variation in research production between species. The most important variable explaining the presence/ absence of conservation research was scientific capacity of countries within the range of the species, followed by body mass and years since the taxonomic description. Research volume (more than one document) was strongly associated with number of years since the data describing on that species, followed by scientific capacity within the range of species, high body mass and invasiveness. The threat status was weakly associated to explain the presence/absence and research volume in conservation research. These results can be interpreted as a consequence of the dynamic interplay between the perceived need for conservation research about a species and its appropriateness as a target of research. As anticipated, the scientific capacity of the countries where a species is found is a strong driver of conservation research bias, reflecting the high variation in conservation research funding and human resources between countries. Our study suggests that this bias could be most effectively reduced by a combination of investing in pioneering research, targeted funding and supporting research in countries with low scientific capacity and high biodiversity.

The Caatinga is an ecologically unique semi-arid region of northeast Brazil characterized by high levels of endemism and severe anthropogenic threats from agricultural development and climate change. It is also one of the least known biomes in Brazil due to a combination of inadequate investment, low regional research capacity and difficult working conditions. However, while the lack of scientific knowledge of the Caatinga is well known, the spatial and temporal distribution of knowledge production has not been investigated. This is important because such biases undermine the development of effective conservation policy and practice and increase the uncertainty associated with conservation actions. Here, we map the geography of conservation knowledge production in the Caatinga and use an innovative hurdle model to identify the presumptive factors driving these patterns. Our analysis revealed strong geographic patterns, with research sites concentrated in the east of the region and in areas close to roads and research centres. There was also a positive association between conservation knowledge production and risk of desertification, indicating that conservation scientists are responding to conservation challenges faced by Caatinga’s fauna and flora arising from climate change. Our results also highlight the pivotal role of pioneer scientists (those who develop research sites in previously unstudied/understudied areas) in determining the future geographic patterns of knowledge production. We conclude our article with a brief discussion of potential policies for increasing the spatial representativeness of conservation research in this remarkable ecosystem.

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The humid forests of Amazonia are experiencing longer and more intense dry seasons, which are predicted to intensify by the end of the 21st century. Although tree species often have long generation times, they may still have the capacity to rapidly respond to changing climatic conditions through adaptive phenotypic plasticity. We, therefore, predicted that Amazonian trees have shifted their leaf morphology in response to the recent drier climate. We tested this prediction by analysing historical herbarium specimens of six Amazonian tree species collected over a 60-year period and comparing changes in leaf morphology with historical precipitation data. Moreover, we explored spatial and temporal biases in herbarium specimens and accounted for their potentially confounding effect in our analysis. We found pronounced biases in herbarium specimens, with nearly 20% of specimens collected in close geographic proximity and around the 1975s. When accounting for such biases, our results indicate a trend of decreasing leaf size after the 1970s, which may have been spurred by an observed reduction in rainfall. Our findings support the hypothesis that (some) Amazonian trees have the capacity to adaptively change their leaf phenotypes in response to the recent drier climate. Nevertheless, the unavoidable spatial and temporal biases in herbarium specimens call for caution when generalizing our findings to all Amazonian trees.

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