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ABSTRACT Species distribution modeling can be used to predict environmental suitability, and removing areas currently lacking appropriate vegetation can refine range estimates for conservation assessments. However, the uncertainty around geographic coordinates can exceed the fine resolution of remotely sensed habitat data. Here, we present a novel methodological approach to reflect this reality by processing habitat data to maintain its fine resolution, but with new values characterizing a larger surrounding area (the “neighborhood”). We implement its use for a forest‐dwelling species (Handleyomys chapmani) considered threatened by the IUCN. We determined deforestation tolerance threshold values by matching occurrence records with forest cover data using two methods: (1) extracting the exact pixel value where a record fell; and (2) using the neighborhood value (more likely to characterize conditions within the radius of actual sampling). We removed regions below these thresholds from the climatic suitability prediction, identifying areas of inferred habitat loss. We calculated Extent of Occurrence (EOO) and Area of Occupancy (AOO), two metrics used by the IUCN for threat level categorization. The values estimated here suggest removing the species from threatened categories. However, the results highlight spatial patterns of loss throughout the range not reflected in these metrics, illustrating drawbacks of EOO and showing how localized losses largely disappeared when resampling to the 2 × 2 km grid required for AOO. The neighborhood approach can be applied to various data sources (NDVI, soils, marine, etc.) to calculate trends over time and should prove useful to many terrestrial and aquatic species. It is particularly useful for species having high coordinate uncertainty in regions of low spatial autocorrelation (where small georeferencing errors can lead to great differences in habitat, misguiding conservation assessments used in policy decisions). More generally, this study illustrates and enhances the practicality of using habitat‐refined distribution maps for biogeography and conservation. 

ABSTRACT Species are distributed in predictable ways in geographic spaces. The three principal factors that determine geographic distributions of species are biotic interactions (B), abiotic conditions (A), and dispersal ability or mobility (M). A species is expected to be present in areas that are accessible to it and that contain suitable sets of abiotic and biotic conditions for it to persist. A species' probability of presence can be quantified as a combination of responses toB,A, andMviaecological niche modeling (ENM; also frequently referred to as species distribution modeling or SDM). This analytical approach has been used broadly in ecology and biogeography, as well as in conservation planning and decision‐making, but commonly in the context of ‘natural’ settings. However, it is increasingly recognized that human impacts, including changes in climate, land cover, and ecosystem function, greatly influence species' geographic ranges. In this light, historical distinctions between natural and anthropogenic factors have become blurred, and a coupled human–natural landscape is recognized as the new norm. Therefore,B,A, andM(BAM) factors need to be reconsidered to understand and quantify species' distributions in a world with a pervasive signature of human impacts. Here, we present a framework, termed human‐influenced BAM (Hi‐BAM, for distributional ecology that (i) conceptualizes human impacts in the form of six drivers, and (ii) synthesizes previous studies to show how each driver modifies the natural BAM and species' distributions. Given the importance and prevalence of human impacts on species distributions globally, we also discuss implications of this framework for ENM/SDM methods, and explore strategies by which to incorporate increasing human impacts in the methodology. Human impacts are redefining biogeographic patterns; as such, future studies should incorporate signals of human impacts integrally in modeling and forecasting species' distributions. 

Abstract Here we review and extend the equal fitness paradigm (EFP) as an important step in developing and testing a synthetic theory of ecology and evolution based on energy and metabolism. The EFP states that all organisms are equally fit at steady state, because they allocate the same quantity of energy, ~ 22.4 kJ/g/generation to the production of offspring. On the one hand, the EFP may seem tautological, because equal fitness is necessary for the origin and persistence of biodiversity. On the other hand, the EFP reflects universal laws of life: how biological metabolism – the uptake, transformation and allocation of energy – links ecological and evolutionary patterns and processes across levels of organisation from: (1) structure and function of individual organisms, (2) life history and dynamics of populations, and (3) interactions and coevolution of species in ecosystems. The physics and biology of metabolism have facilitated the evolution of millions of species with idiosyncratic anatomy, physiology, behaviour and ecology but also with many shared traits and tradeoffs that reflect the single origin and universal rules of life. 

This database compiles comprehensive occurrence information, based on voucher specimens of small-eared shrews, genusCryptotis, that occur from México to Peru. The database integrates the information obtained from four main sources: natural history museums, public databases, fieldwork and scientific literature. It contains 3,639 records from 53 species in 12 countries. Of the total, 83.54% have collecting dates, 51.36% of the specimens are sexed and 84.56% have decimal degrees coordinates. By generating this database and making it publicly available, we hope to improve the biological knowledge of this group of small mammals still poorly studied in the region. It aims to be a valuable resource for students, researchers, conservationists and decision-makers. The dataset contains information on all species of the genusCryptotisin the Neotropical Region (namely from México to Peru), incorporating the most updated taxonomic and nomenclatural changes. The database includes records in regions and countries that are poorly represented in currently available data repositories. Most records have verified temporal and spatial information. 

Species distribution models, also known as ecological niche models or habitat suitability models, have become commonplace for addressing fundamental and applied biodiversity questions. Although the field has progressed rapidly regarding theory and implementation, key assumptions are still frequently violated and recommendations inadvertently overlooked. This leads to poor models being published and used in real‐world applications. In a structured, didactic treatment, we summarize what in our view constitute the ten most problematic issues, or hazards, negatively affecting implementation of correlative approaches to species distribution modeling (specifically those that model suitability by comparing the environments of a species' occurrence records with those of a background or pseudoabsence sample). For each hazard, we state relevant assumptions, detail problems that arise when violating them, and convey straightforward existing recommendations. We also discuss five major outstanding questions of active current research. We hope this contribution will promote more rigorous implementation of these valuable models and stimulate further advancements.