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Abstract Broad‐scale assessments of plant–frugivore interactions indicate the existence of a latitudinal gradient in interaction specialization. The specificity (i.e. the similarity of the interacting partners) of plant–frugivore interactions could also change latitudinally given that differences in resource availability could favour species to become more or less specific in their interactions across latitudes.Species occurring in the tropics could be more taxonomically, phylogenetically and functionally specific in their interactions because of a wide range of resources that are constantly available in these regions that would allow these species to become more specialized in their resource usage.We used a data set on plant–avian frugivore interactions spanning a wide latitudinal range to examine these predictions, and we evaluated the relationship between latitude and taxonomic, phylogenetic and functional specificity of plant and frugivore interactions. These relationships were assessed using data on population interactions (population level), species means (species level) and community means (community level).We found that the specificity of plant–frugivore interactions is generally not different from null models. Although statistically significant relationships were often observed between latitude and the specificity of plant–frugivore interactions, the direction of these relationships was variable and they also were generally weak and had low explanatory power. These results were consistent across the three specificity measures and levels of organization, suggesting that there might be an interplay between different mechanisms driving the interactions between plants and frugivores across latitudes. 

Abstract Spatial biases are an intrinsic feature of occurrence data used in species distribution models (SDMs). Thinning species occurrences, where records close in the geographic or environmental space are removed from the modeling procedure, is an approach often used to address these biases. However, thinning occurrence data can also negatively affect SDM performance, given that the benefits of removing spatial biases might be outweighed by the detrimental effects of data loss caused by this approach. We used real and virtual species to evaluate how spatial and environmental thinning affected different performance metrics of four SDM methods. The occurrence data of virtual species were sampled randomly, evenly spaced, and clustered in the geographic space to simulate different types of spatial biases, and several spatial and environmental thinning distances were used to thin the occurrence data. Null datasets were also generated for each thinning distance where we randomly removed the same number of occurrences by a thinning distance and compared the results of the thinned and null datasets. We found that spatially or environmentally thinned occurrence data is no better than randomly removing them, given that thinned datasets performed similarly to null datasets. Specifically, spatial and environmental thinning led to a general decrease in model performances across all SDM methods. These results were observed for real and virtual species, were positively associated with thinning distance, and were consistent across the different types of spatial biases. Our results suggest that thinning occurrence data usually fails to improve SDM performance and that the use of thinning approaches when modeling species distributions should be considered carefully. 

Abundance–occupancy relationships predict that species that occupy more sites are also more locally abundant, where occupancy is usually estimated following the assumption that species can occupy all sampled sites. Here we use the National Ecological Observatory Network small-mammal data to assess whether this assumption affects abundance–occupancy relationships. We estimated occupancy considering all sampled sites (traditional occupancy) and only the sites found within the species geographic range (spatial occupancy) and realized environmental niche (environmental occupancy). We found that when occupancy was estimated considering only sites possible for the species to colonize (spatial and environmental occupancy) weaker abundance–occupancy relationships were observed. This shows that the assumption that the species can occupy all sampled sites directly affects the assessment of abundance–occupancy relationships. Estimating occupancy considering only sites that are possible for the species to colonize will consequently lead to a more robust assessment of abundance–occupancy relationships.