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Background: Mesoamerica is one of the most important biodiversity hotspots on the planet. Despite significant efforts made over two centuries to contribute to the floristic knowledge of this region, our understanding of its flora is still scattered and uneven. Questions: What is the magnitude of the vascular plant species richness in the Usumacinta River Basin? Study site and dates: Usumacinta River Basin (Guatemala and Mexico), 1838-2018. Methods: We compiled the checklist by systematizing the floristic information acquired from various sources derived from numerous floristic and ecological studies. Results: We recorded 6,977 species, 1,892 genera and 274 families. The largest numbers of species (5,746) and records (58,859) correspond to the Mexican portion of the Usumacinta River Basin, compared to its Guatemalan counterpart (4,445 species and 19,952 records). The most species-rich families were Orchidaceae (598 species), Fabaceae (512), and Asteraceae (476). The prevalence of these and all other families with significant contributions to the flora varied among three elevation-defined sectors into which the Usumacinta River Basin was subdivided (lower, middle, and upper basin). Conclusions: The Usumacinta River Basin is a strategic region for plant biodiversity conservation as it hosts almost one third of all vascular plant species known for Mesoamerica and ca. 6 % of the entire flora in the Americas. Further botanical exploration should focus on those areas of the basin for which little or no information is available in order to gain a better appreciation of its flora.

Deforestation is a major factor reducing natural habitats, leading to tropical ecosystems and biodiversity loss worldwide. The Lacandona region in southern Mexico holds one of the largest fragments of tropical rainforest in North America. We evaluated the deforestation of the Lacandona region harmonizing concepts and methodologies. An international (FAO definition), governmental (national definition), and regional definition of deforestation with applications at different scales were analyzed and harmonized with two classification methods (likelihood and spectral angle mapper (SAM)). We used 2015 and 2018 Landsat 8 images, and likelihood and SAM classifications were applied for FAO and regional definitions of deforestation. Overall, the best evaluated classifier in quantity was likelihood for 2015 and 2018 (kappa: 0.87 and 0.70, overall accuracy: 91.8 and 80.4%, and quantity disagreement: 4.1 and 10 %, respectively). The allocation disagreement only showed exchange between classes. Nevertheless, they did not show differences between classifiers, although 2015 had less disagreement than 2018: exchange, 4.1% for likelihood and SAM; shift: 0% for likelihood and SAM. Maps based on the regional definition of deforestation showed that the likelihood classification detected 11,441 ha less deforestation than SAM (40,538 and 51,979 ha, respectively). The FAO definition of deforestation showed that likelihood classification detected 11,914 ha less deforestation than SAM classification (37,152 and 49,066 ha, respectively). Further, the likelihood classification showed 3387 ha more of deforestation according to the regional definition than the FAO definition of deforestation (40,538 and 37,152 ha, respectively). SAM classification showed that the regional definition showed 2913 ha more deforestation than the FAO definition (51,979 and 49,066, respectively). We concluded that implementation of governmental programs in the Lacandona region requires estimations based on a careful selection of deforestation definitions and methods.

Antecedentes: La Reserva de la Biosfera Pantanos de Centla (RBPC) es considerada uno de los humedales más importantes de Mesoamérica. El objetivo principal de este estudio fue actualizar el listado de plantas vasculares con base en la revisión e integración de fuentes de información. Preguntas: ¿Cuál es la riqueza actual de plantas vasculares nativas en la RBPC? ¿Cuál es la forma de crecimiento y hábito más frecuente de estas especies? ¿Qué proporción de plantas son acuáticas? Área de estudio: Reserva de la Biosfera Pantanos de Centla, México. Métodos: La lista de especies se hizo a través de una revisión de la literatura, de colecciones digitales y herbarios. Resultados: La flora incluyó 813 taxones específicos, distribuidas en 462 géneros y 115 familias, de las cuales 731 son especies nativas, 64 introducidas y 18 cultivadas. Incluyendo únicamente a especies nativas, las familias mejor repsentadas fueron fueron Fabaceae, Poaceae y Cyperaceae. Las herbáceas fueron la forma de crecimiento más abundante con 432 especies, el hábito terrestre fue el más frecuente con 440 especies, incluyendo 63 acuáticas y 85 hidrófitas. Esta lista florística aumenta en un 15 % las especies nativas que se habían registrado para el RBPC Conclusiones: La actualización de la lista florística representa un aumento significativo en la diversidad de plantas vasculares para los humedales mexicanos. Esta información contribuye a la toma de decisiones correctas para el manejo de la biodiversidad de la RBPC y a un profundo conocimiento de los humedales en el país.

The U-net is nowadays among the most popular deep learning algorithms for land use/land cover (LULC) mapping; nevertheless, it has rarely been used with synthetic aperture radar (SAR) and multispectral (MS) imagery. On the other hand, the discrimination between plantations and forests in LULC maps has been emphasized, especially for tropical areas, due to their differences in biodiversity and ecosystem services provision. In this study, we trained a U-net using different imagery inputs from Sentinel-1 and Sentinel-2 satellites, MS, SAR and a combination of both (MS + SAR); while a random forests algorithm (RF) with the MS + SAR input was also trained to evaluate the difference in algorithm selection. The classification system included ten classes, including old-growth and secondary forests, as well as old-growth and young plantations. The most accurate results were obtained with the MS + SAR U-net, where the highest overall accuracy (0.76) and average F1-score (0.58) were achieved. Although MS + SAR and MS U-nets gave similar results for almost all of the classes, for old-growth plantations and secondary forest, the addition of the SAR band caused an F1-score increment of 0.08–0.11 (0.62 vs. 0.54 and 0.45 vs. 0.34, respectively). Consecutively, in comparison with the MS + SAR RF, the MS + SAR U-net obtained higher F1-scores for almost all the classes. Our results show that using the U-net with a combined input of SAR and MS images enabled a higher F1-score and accuracy for a detailed LULC map, in comparison with other evaluated methods.

The provision of valuable ecosystem services by tropical swamp forests (mainly carbon sequestration and storage in biomass and soil) explains their ecological importance. Current efforts toward the conservation of these ecosystems, however, face strong limitations as their spatial variation is largely unknown, particularly in regions where they occur over large areas. Here, we analyze the α-diversity (i.e., effective number of species or true diversity) and community structure variability of three tropical swamp forest communities distributed along an approximately 300 km long portion of the Usumacinta River Basin, southern Mexico. We sampled eighty-three 625-m2 plots to characterize the diversity and structural attributes of the woody plant communities. We recorded 2302 individuals belonging to 60 species and 25 families. Both α-diversity and structural attributes differed significantly among the three communities. The most inland community stood out for having the highest α-diversity for three true diversity values. Interestingly, the mangrove Rhizophora mangle L. was one of the dominant species, both in the swamp forest located closest to the coast and in the community farthest away from the sea. Basal area and density of individuals also had their maxima in the most inland swamp forest. The diversity and structural differences observed among the examined swamp forests seem to be related to contrasting environmental conditions, such as water salinity, distance to the coastline, and the hydrological dynamics of the Usumacinta River. We emphasize the urgency to conserve R. mangle populations in the swamp forest located farthest away from the coast due to its unusual habitat association, which appears to be a relictual condition.

Abstract Numerous studies have focused on the relationship between landscape structure and plant diversity based on the patch‐mosaic landscape paradigm, by deriving structural data from classified images. Since the use of discrete classes poses limitations for predicting biodiversity patterns in complex, low human‐impacted ecosystems, two alternative methods have been used to analyze changes of landscape attributes in a continuum: moving‐window metrics and surface metrics (image texture). Here, we compare these two approaches for predicting richness of all plant species, legume species, legume trees, legume shrubs, legume forbs, and legume climbers across a tropical landscape in Mexico, based on the records of vascular plants in 250 10 × 10 m plots. Multiple regression and variance partitioning methods were used to analyze the effects of the two landscape descriptors (moving‐window and surface metrics), scale (400‐ and 200‐m moving‐window sides), and space (based on the extraction of principal coordinates of neighbor matrices’ vectors) on species richness. The predictive power of all metrics was relatively small for total species richness, but generally higher for legume species. For legume forbs, surface metrics‐based models indicated a direct association between species richness and landscape homogeneity. Moving‐window metrics were highly sensitive to the biological group and to spatial scale, likely due to a leftover effect of image classification procedures. Conversely, surface metrics were more independent from scale and taxonomy. Attempts to predict species richness in highly diverse, low human‐impacted tropical ecosystems more rapidly and accurately should better rely on surface metrics rather than on moving‐window metrics, in line with the continuous landscape paradigm.

Two main theories have attempted to explain variation in plant species composition (β-diversity). Niche theory proposes that most of the variation is related to environment (environmental filtering), whereas neutral theory posits that dispersal limitation is the main driver of β-diversity. In this study, we first explored how α- and β-diversity of plant functional groups defined by growth form (trees, shrubs and lianas, which represent different strategies of resource partitioning), and dispersal syndrome (autochory, anemochory and zoochory, which represent differences in dispersal limitation) vary with successional age and topographic position in a tropical dry forest. Second, we examined the effects of environmental, spatial, and spatially-structured environmental factors on β-diversity of functional groups; we used the spatial structure of sampling sites as a proxy for dispersal limitation, and elevation, soil properties and forest stand age as indicators of environmental filtering. We recorded 200 species and 22,245 individuals in 276 plots; 120 species were trees, 41 shrubs and 39 lianas. We found that β-diversity was highest for shrubs, intermediate for lianas and lowest for trees, and was slightly higher for zoochorous than for autochorous and anemochorous species. All three dispersal syndromes, trees and shrubs varied in composition among vegetation classes (successional age and topographic position), whilst lianas did not. β-diversity was influenced mostly by proxies of environmental filtering, except for shrubs, for which the influence of dispersal limitation was more important. Stand age and topography significantly influenced α-diversity across functional groups, but showed a low influence on β-diversity -possibly due to the counterbalancing effect of resprouting on plant distribution and composition. Our results show that considering different plant functional groups reveals important differences in both α- and β-diversity patterns and correlates that are not apparent when focusing on overall woody plant diversity, and that have important implications for ecological theory and biodiversity conservation.