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Recent models suggest that anthropogenic global warming will lead to an increase in the number of major hurricanes, which have strong effects on ecosystems and may modify animal population characteristics. The goal of this study was to assess the body condition of American crocodiles Crocodylus acutus of Cozumel and Banco Chinchorro islands, Mexico, and use it as a tool to better understand short- and long-term effects of hurricanes on crocodilian populations. Changes in body condition (Fulton’s K) of 392 crocodiles, captured between 2003 and 2015, were assessed and analyzed in response to a major hurricane through different environmental factors. Differences among populations and size classes, and between sexes, together with seasonal variation, were also evaluated. The body condition of crocodiles was generally good, with better condition for Banco Chinchorro, suggesting that these populations and the ecosystems they inhabit are healthy. Body condition for hatchlings and adults was higher than for other classes, with adults exhibiting the best condition. Body condition of Banco Chinchorro individuals varied seasonally, responding to reproductive events and environmental parameter fluctuations. We also found that C. acutus body condition is sensitive to the passage of tropical cyclones, most likely through their effects on salinity, temperature, and prey availability. Tropical cyclones have a 2fold effect on populations. In the short-term, crocodile health is negatively affected by disturbance, while the species seems to maintain and improve its body condition over the longer term. An increase in strong tropical cyclone frequency could impede the recovery of populations, while causing a continual decrease in crocodile body condition.

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.

Despite the ecological importance of wetland forests, their classification is still unsatisfactory, partly due to insufficient knowledge about the environmental drivers of their spatial heterogeneity. We examined the spatial variation of six community attributes in a tropical wetland forest and analyzed the underlying causes by using linear distance measures and geomorphological zonation as proxies of environmental heterogeneity. The study was conducted in a wetland forest located on a coastal plain of southern Mexico. Vegetation was sampled in two distinct landforms: coastal lagoon and river channel. For each plot we determined two other proxies of environmental variation, namely distance to the sea, and distance to closest water body. We assessed the effects of these environmental factors on wetland forest attributes through linear modelling. Except for species richness, all other attributes were heterogeneous across space, with aboveground biomass showing the largest variation. Overall, forest structural attributes in plots located along the highly dynamic main river channel were higher than those recorded around a relatively stable coastal lagoon, suggesting better conditions for wetland forest development in the former area. Models consistently included geomorphological zone, as well as distance proxies in most of them, with variable effects on community attributes. The spatial variation of this wetland forest was associated with different combinations of environmental proxies, with geomorphology being a key driver of this variability. A thorough understanding of the factors driving the spatial variation of wetland forests will lead to a more sensible ecological classification.

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 &alpha, 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 &alpha, diversity and structural attributes differed significantly among the three communities. The most inland community stood out for having the highest &alpha, 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.

Tropical wetlands are important in the global carbon (C) cycle and climate system. To elaborate government policies that protect wetland ecosystem services, spatially explicit data on the existing C stocks are needed. This study quantified above and below ground C stocks in mangrove, swamp forests, marshes, and grazed wetlands in three different regions in Mexico (Veracruz, Tabasco/Campeche, and Chiapas states), using a combination of remote sensing techniques and field data collection. We report a 0.688 Gt C stock in the areas investigated showing that these wetlands hold important C stocks. The total C stock of Mexico’s wetlands is expected to be considerably larger as our study is not a complete survey of Mexico’s total wetland area. Across the three regions, the currently unprotected swamp forests and marshes had substantial peat deposits storing ≈ 0.232 and 0.375 Pg C, respectively. The high C stocks found in swamp forests (1801 ± 283 Mg C ha−1) and marshes (1100 ± 376 Mg C ha−1) are likely to be vulnerable to human interventions such as drainage. Flooded grasslands, used for grazing, had substantially lower C storage (271 ± 122 Mg C ha−1), showing that grazed areas are less effective as C stores. Across sites the belowground C pool that was two orders of magnitude greater than the aboveground biomass C stocks. Carbon storage in wetland vegetation types differed among the three study regions, indicating the need for developing government policies considering a specific regional approach to protect the C stocks of coastal wetlands. Given that freshwater swamps had the greatest C stocks and freshwater marshes stored most C, these wetland peat deposits should be prioritized for conservation, via new legislation or inclusion in payment for ecosystem services schemes.

Societal processes of rural change and globalization may change homegardens and their contribution to the conservation of agrobiodiversity, particularly of species occurring naturally in regional vegetation. The best way to determine if this occurs is through longitudinal studies. We conducted such a study, inventorying tree species in a sample of 38 homegardens in 2009, 2012 and 2015. The homegardens were located in the subregions of mountain slopes, fluvial plains and coastal plains in the tropical lowlands of Tabasco, Mexico. We analysed changes in species richness by geographic origin, species richness and species composition in each inventory. We identified 169 tree species in the three inventories, of which 74.6% were native or neotropical and 25.4% introduced. Of the 140 species recorded in 2009, 88% remained in 2015, whereas 12% had been replaced and nine additional species had arrived. Mean species richness increased between 2009 and 2015 (P = 0.03) and between 2012 and 2015 (P = 0.001). Increases resulted from increased mean neotropical (P = 0.01) and introduced (P = 0.01) species richness, and constant native species richness. Differences in species composition between the three subregions in 2009 persisted in 2012 and 2015 (P

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.

Google Earth provides a freely available, global mosaic of high-resolution imagery from different sensors that has become popular in environmental and ecological studies. However, such imagery lacks the near-infrared band often used in studying vegetation, thus its potential for estimating vegetation properties remains unclear. In this study, we assess the potential of Google Earth imagery to describe and predict vegetation attributes. Further, we compare it to the potential of SPOT imagery, which has additional spectral information. We measured basal area, vegetation height, crown cover, density of individuals, and species richness in 60 plots in the oak forests of a complex volcanic landscape in central Mexico. We modelled each vegetation attribute as a function of surface metrics derived from Google Earth and SPOT images, and selected the best-supported linear models from each source. Total species richness was the best-described and predicted variable: the best Google Earth-based model explained nearly as much variation in species richness as its SPOT counterpart (R2 = 0.44 and 0.51, respectively). However, Google Earth metrics emerged as poor predictors of all remaining vegetation attributes, whilst SPOT metrics showed potential for predicting vegetation height. We conclude that Google Earth imagery can be used to estimate species richness in complex landscapes. As it is freely available, Google Earth can broaden the use of remote sensing by researchers and managers in low-income tropical countries where most biodiversity hotspots are found.

The importance of space as an ecological factor is an emerging paradigm in community ecology, particularly as a driving force of biodiversity patterns. We analysed β-diversity linked to spatial structure in four communities (tropical dry forest, savanna, xerophytic vegetation, subdeciduous forest) that occur in a tropical complex landscape of southern Mexico. The landscape was described through an object-oriented classification of a Quickbird satellite image. The classification revealed a highly heterogeneous spatial arrangement of the four communities. Global (landscape-level) P-diversity was 0.12 (mean Sorensen index), a value smaller than those observed for the individual communities (0.20-0.41). By using multivariate classic and partial Mantel tests, and Mantel correlograms based on two distance classes, we analysed P-diversity spatial variation related to landscape configuration. The Mantel statistic values for the four communities combined were negative and very similar both for the classic Mantel (rM = -0.23) and the partial Mantel test (rM = -0.19). Correlograms proved significant spatial autocorrelation across most of the analysed distance classes, except in the case of riparian subdeciduous forest. Tropical dry forest and savanna occupy large, highly connected areas in the landscape. Correlograms for these two communities showed decreasing trends, starting at positive, significant autocorrelation values at short distances. The loss of floristic autocorrelation beyond a 5000 m distance for the tropical dry forest may reflect spatially autocorrelated dispersal, and thus a dispersal-limited community. Xerophytic vegetation displayed a distinctly different correlogram, with a wavy shape showing an alternation of positive and negative values, in agreement with the insular configuration of this community in the landscape. We suggest that the routinely incorporation of a spatial approach in community ecology research will help in furthering our understanding of the elusive issues of species turnover across space.

Several remote sensing proxies, such as image texture, have been used to describe the spatial variation of different tropical forest’s attributes at medium scales. Fourier transformed ordination (FOTO) and gray level co-occurrence matrix (GLCM) are two texture methods frequently used in these studies but seldom compared. Therefore, the objective of this study was to compare the potential of these metrics to describe and predict structural and diversity attributes of a tropical swamp forest located in southeast Mexico. FOTO and GLCM textures were extracted from the panchromatic (Pan) band, the near-infrared (NIR) and red (R), of a very high spatial resolution (VHSR) image. Six different types of models that incorporated between one and three texture variables were constructed to describe each forest attribute. Simpson (R2 = 0.71) and Shannon (R2 = 0.67) diversity indices followed by the aboveground biomass (R2 = 0.65) were the attributes that obtained models with a higher goodness-of-fit values. In terms of its modeling potential, GLCM greatly surpassed FOTO textures. Our results show that VHSR textures (especially R- and NIR-derived GLCM metrics) allow for a reliable estimation of important tropical swamp forest attributes associated with its diversity and structure.