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Research Highlights: This study is one of few detailed analyses of plant diversity and vegetation patterns in African dry forests. We established permanent plots to characterize plant diversity, above-ground biomass, and vegetation patterns in a tropical dry forest in Kimbi-Fungom National Park, Cameroon. Our results contribute to long-term monitoring, predictions, and management of dry forest ecosystems, which are often vulnerable to anthropogenic pressures., Background and Objectives: Considerable consensus exists regarding the importance of dry forests in species diversity and carbon storage; however, the relationship between dry forest tree species composition, species richness, and carbon stock is not well established. Also, simple baseline data on plant diversity are scarce for many dry forest ecosystems. This study seeks to characterize floristic diversity, vegetation patterns, and tree diversity in permanent plots in a tropical dry forest in Northwestern Cameroon (Kimbi-Fungom National Park) for the first time., Materials and Methods: We studied associations between above-ground biomass and species composition, and how different vegetation types vary in terms of species composition, diversity, and carbon storage, in a dry forest in Kimbi-Fungom National Park, Cameroon. Vegetation was inventoried in 17 permanent 1-ha plots. Allometric equations were used to calculate above-ground biomass and carbon., Results: We found an average of 269.8 tree stems ha -1 and 43.1 species ha -1 . Five vegetation types: semi-deciduous, gallery, mixed vegetation, secondary and the grassland/woody savanna forest were classified using TWINSPAN analysis. The five vegetation types had an average above-ground biomass of 149.2 t ha -1 and 74.6 tC ha -1 of carbon in the 17 ha analyzed. Canonical correspondence analysis (CCA) showed the importance of semi-deciduous forest over grassland/woody savanna forest., Conclusions: This study demonstrated that the forest of the Kimbi-Fungom National Park is poor in plant diversity, biomass, and carbon, highlighting the need to implement efficient management practices. Fine-scale inventory data of species obtained in this study could be useful in developing predictive models for efficient management of tropical dry forests., (© 2020 The Author(s).)

The latitudinal diversity gradient (LDG), where the number of species increases from the poles to the Equator, ranks among the broadest and most notable biodiversity patterns on Earth. The pattern of species-rich tropics relative to species-poor temperate areas has been recognized for well over a century, but the generative mechanisms are still debated vigorously. We use simulations to test whether spatio-temporal climatic changes could generate large-scale patterns of biodiversity as a function of only three biological processes-speciation, extinction and dispersal-omitting adaptive niche evolution, diversity-dependence and coexistence limits. In our simulations, speciation resulted from range disjunctions, whereas extinction occurred when no suitable sites were accessible to species. Simulations generated clear LDGs that closely match empirical LDGs for three major vertebrate groups. Higher tropical diversity primarily resulted from higher low-latitude speciation, driven by spatio-temporal variation in precipitation rather than in temperature. This suggests that spatio-temporal changes in low-latitude precipitation prompted geographical range disjunctions over Earth's history, leading to high rates of allopatric speciation that contributed to LDGs. Overall, we show that major global biodiversity patterns can derive from interactions of species' niches (fixed a priori in our simulations) with dynamic climate across complex, existing landscapes, without invoking biotic interactions or niche-related adaptations.

We have tested the hypothesis that coarse-scale environmental features are associated with spatial variation in bovine tuberculosis (BTB) prevalence, based on extensive sampling and testing of cattle in the state of Jalisco, Mexico. Ecological niche models were developed to summarize relationships between BTB occurrences and aspects of climate, topography and surface. Model predictions, however, reflected the distributions of dairy cattle versus beef cattle, and the non-random nature of sampling any cattle, but did not succeed in detecting environmental correlates at spatial resolutions of 1 km. Given that the tests employed seek any predictivity better than random expectations, making the finding of no environmental associations conservative, we conclude that BTB prevalence is independent of coarsescale environmental features.