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1.
Ecology ; 104(12): e4181, 2023 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-37784251

RESUMEN

Many animal-environment interactions are mediated by the physical forms of the environment, especially in tropical forests, where habitats are structurally complex and highly diverse. Higher structural complexity, measured as habitat surface area, may provide increased resource availability for animals, leading to higher animal diversity. Greater habitat surface area supports increased animal diversity in other systems, such as coral reefs and forest canopies, but it is uncertain how this relationship translates to communities of highly mobile, terrestrial mammal species inhabiting forest floors. We tested the relative importance of forest floor habitat structure, encompassing vegetation and topographic structure, in determining species occupancy and functional diversity of medium to large mammals using data from a tropical forest in the Udzungwa Mountains of Tanzania. We related species occupancies and diversity obtained from a multispecies occupancy model with ground-level habitat structure measurements obtained from a novel head-mounted active remote sensing device, the Microsoft HoloLens. We found that habitat surface area was a significant predictor of mean species occupancy and had a significant positive relationship with functional dispersion. The positive relationships indicate that surface area of tropical forest floors may play an important role in promoting mammal occupancy and functional diversity at the microhabitat scale. In particular, habitat surface area had higher mean effects on occupancy for carnivorous and social species. These results support a habitat surface area-diversity relationship on tropical forest floors for mammals.


Asunto(s)
Biodiversidad , Carnívoros , Animales , Bosques , Ecosistema , Mamíferos , Arrecifes de Coral
2.
PLoS One ; 10(2): e0118330, 2015.
Artículo en Inglés | MEDLINE | ID: mdl-25714404

RESUMEN

Growing threats to primates in tropical forests make robust and long-term population abundance assessments increasingly important for conservation. Concomitantly, monitoring becomes particularly relevant in countries with primate habitat. Yet monitoring schemes in these countries often suffer from logistic constraints and/or poor rigor in data collection, and a lack of consideration of sources of bias in analysis. To address the need for feasible monitoring schemes and flexible analytical tools for robust trend estimates, we analyzed data collected by local technicians on abundance of three species of arboreal monkey in the Udzungwa Mountains of Tanzania (two Colobus species and one Cercopithecus), an area of international importance for primate endemism and conservation. We counted primate social groups along eight line transects in two forest blocks in the area, one protected and one unprotected, over a span of 11 years. We applied a recently proposed open metapopulation model to estimate abundance trends while controlling for confounding effects of observer, site, and season. Primate populations were stable in the protected forest, while the colobines, including the endemic Udzungwa red colobus, declined severely in the unprotected forest. Targeted hunting pressure at this second site is the most plausible explanation for the trend observed. The unexplained variability in detection probability among transects was greater than the variability due to observers, indicating consistency in data collection among observers. There were no significant differences in both primate abundance and detectability between wet and dry seasons, supporting the choice of sampling during the dry season only based on minimizing practical constraints. Results show that simple monitoring routines implemented by trained local technicians can effectively detect changes in primate populations in tropical countries. The hierarchical Bayesian model formulation adopted provides a flexible tool to determine temporal trends with full account for any imbalance in the data set and for imperfect detection.


Asunto(s)
Bosques , Densidad de Población , Primates , Algoritmos , Animales , Conservación de los Recursos Naturales , Ecosistema , Geografía , Modelos Teóricos , Tanzanía , Clima Tropical
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