ESTRUCTURA ARBÓREA Y VARIABILIDAD TEMPORAL DEL NDVI EN LOS “BAJOS INUNDABLES” DE LA PENÍNSULA DE YUCATÁN, MÉXICO

The Low-statured Inundated Forest (SBI inSpanish) of the Yucatan Peninsula of Mexico occurs in closed valleys with flat terrainand insufficient drainage (polje), typical ofkarstic landscapes. It is composed of fewwoody species, has a canopy up to 10 mhigh, and is important for its role as a refugium for fauna and as a seed source. Variousassociations are distinguished within thisvegetation type, such as tintales, pucteales,and mucales. In order improve the differentiation between SBI and non-inundatedsurrounding forest, spectral reflectance of the SBI was analyzed using NDVI over timealong a transect from the interior of a poljeto the surrounding forest in three landscapeson a humidity gradient captured on LandsatETM satellite images. Plots were established along each transect for describing thestructure and composition of the vegetation,monitoring phenology and inundation level,and relating these to the NDVI. The SBIplots showed a species richness (30) similarto that of the surrounding forest (29), buthad a higher density (4570 ind/ha versus2426 ind/ha) and higher diversity (ShannonWiener 3.02). NDVI values increased fromthe interior of the polje to the surroundingforest and showed a higher contrast in thedry period. Thus, the image of that seasonyielded a better classification of the SBI.La selva baja inundable (SBI) se encuentraen valles cerrados de terreno plano condeficiente drenaje (polje), típico para paisajes cársticos. Está compuesta de pocasespecies leñosas, con un dosel que nosobrepasa los 10 m de altura, y cumple unimportante papel como refugio de fauna yfuente de germoplasma florístico; se distinguen diversas asociaciones en este tipode vegetación, como los tintales, puctealesy mucales. Para definir mejor la diferenciaentre la SBI y la selva no inundable a sualrededor, se analizó la respuesta espectralde la vegetación de SBI mediante el índicede vegetación NDVI a lo largo del tiempo,en un transecto desde su interior hacia laselva circundante, en tres paisajes sobre ungradiente de humedad captado en imágenesde satélite Landsat ETM. En cada transectose establecieron parcelas para conocer laestructura y composición vegetal, estadofenológico y niveles de inundación a finde relacionarlos con la variabilidad de larespuesta del NDVI. Las parcelas de SBIpresentaron una riqueza específica (30) similar a la de la selva circundante (29), pero con mayor densidad de individuos (4570ind/ha contra 2426 ind/ha) y mayor diversidad (Shannon Wiener, 3.02). Los valoresde NDVI aumentan desde el interior de laSBI hacia la selva circundante con mayorcontraste en la época de secas, por lo quela imagen de esta época proporcionó unamejor clasificación de la SBI

The Tree Biodiversity Network (BIOTREE-NET): prospects for biodiversity research and conservation in the Neotropics

Biodiversity research and conservation efforts in the tropics are hindered by the lack of knowledge of the assemblages found there, with many species undescribed or poorly known. Our initiative, the Tree Biodiversity Network (BIOTREE-NET), aims to address this problem by assembling georeferenced data from a wide range of sources, making these data easily accessible and easily queried, and promoting data sharing. The database (GIVD ID NA-00-002) currently comprises ca. 50,000 tree records of ca. 5,000 species (230 in the IUCN Red List) from \u3e2,000 forest plots in 11 countries. The focus is on trees because of their pivotal role in tropical forest ecosystems (which contain most of the world\u27s biodiversity) in terms of ecosystem function, carbon storage and effects on other species. BIOTREE-NET currently focuses on southern Mexico and Central America, but we aim to expand coverage to other parts of tropical America. The database is relational, comprising 12 linked data tables. We summarise its structure and contents. Key tables contain data on forest plots (including size, location and date(s) sampled), individual trees (including diameter, when available, and both recorded and standardised species name), species (including biological traits of each species) and the researchers who collected the data. Many types of queries are facilitated and species distribution modelling is enabled. Examining the data in BIOTREE-NET to date, we found an uneven distribution of data in space and across biomes, reflecting the general state of knowledge of the tropics. More than 90% of the data were collected since 1990 and plot size varies widely, but with most less than one hectare in size. A wide range of minimum sizes is used to define a \u27tree\u27. The database helps to identify gaps that need filling by further data collection and collation. The data can be publicly accessed through a web application at http://portal.biotreenet.com. Researchers are invited and encouraged to contribute data to BIOTREE-NET

La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Conservation efforts in Neotropical regions are often hindered by lack of data, since for many species there is a vacuum of information, and many species have not even been described yet. The International Network of Forest Inventory Plots (BIOTREE-NET) gathers and facilitates access to tree data from forest inventory plots in Mesoamerica, while encouraging data exchange between researchers, managers and conservationists. The information is organised and standardised into a single database that includes spatially explicit data. This article describes the scope and objectives of the network, its progress, and the challenges and future perspectives. The database includes above 50000 tree records of over 5000 species from more than 2000 plots distributed from southern Mexico through to Panama. Information is heterogeneous, both in nature and shape, as well as in the geographical coverage of inventory plots. The database has a relational structure, with 12 inter-connected tables that include information about plots, species names, dbh, and functional attributes of trees. A new system that corrects typographical errors and achieves taxonomic and nomenclatural standardization was developed using The Plant List (http://theplantlist.org/) as reference. Species distribution models have been computed for around 1700 species using different methods, and they will be publicly accessible through the web site in the future (http://portal.biotreenet.com). Although BIOTREE-NET has contributed to the development of improved species distribution models, its main potential lies, in our opinion, in studies at the community level. Finally, we emphasise the need to expand the network and encourage researchers willing to share data and to join the network and contribute to the generation of further knowledge about forest biodiversity in Neotropical regions

Estructura arbórea y variabilidad temporal del NDVI en los "bajos inundables" de la Península de Yucatán, México

The Low-statured Inundated Forest (SBI in Spanish) of the Yucatan Peninsula of Mexico occurs in closed valleys with flat terrain and insufficient drainage (polje), typical of karstic landscapes. It is composed of few woody species, has a canopy up to 10 m high, and is important for its role as a refu-gium for fauna and as a seed source. Various associations are distinguished within this vegetation type, such as tintales, pucteales, and mucales. In order improve the differentiation between SBI and non-inundated surrounding forest, spectral reflectance of the SBI was analyzed using NDVI over time along a transect from the interior of a polje to the surrounding forest in three landscapes on a humidity gradient captured on Landsat ETM satellite images. Plots were established along each transect for describing the structure and composition of the vegetation, monitoring phenology and inundation level, and relating these to the NDVI. The SBI plots showed a species richness (30) similar to that of the surrounding forest (29), but had a higher density (4570 ind/ha versus 2426 ind/ha) and higher diversity (Shannon Wiener 3.02). NDVI values increased from the interior of the polje to the surrounding forest and showed a higher contrast in the dry period. Thus, the image of that season yielded a better classification of the SBI.La selva baja inundable (SBI) se encuentra en valles cerrados de terreno plano con deficiente drenaje (polje), típico para paisajes cársticos. Está compuesta de pocas especies leñosas, con un dosel que no sobrepasa los 10 m de altura, y cumple un importante papel como refugio de fauna y fuente de germoplasma florístico; se distinguen diversas asociaciones en este tipo de vegetación, como los tintales, pucteales y mucales. Para definir mejor la diferencia entre la SBI y la selva no inundable a su alrededor, se analizó la respuesta espectral de la vegetación de SBI mediante el índice de vegetación NDVI a lo largo del tiempo, en un transecto desde su interior hacia la selva circundante, en tres paisajes sobre un gradiente de humedad captado en imágenes de satélite Landsat ETM. En cada transecto se establecieron parcelas para conocer la estructura y composición vegetal, estado fenológico y niveles de inundación a fin de relacionarlos con la variabilidad de la respuesta del NDVI. Las parcelas de SBI presentaron una riqueza específica (30) similar a la de la selva circundante (29), pero con mayor densidad de individuos (4570 ind/ha contra 2426 ind/ha) y mayor diversidad (Shannon Wiener, 3.02). Los valores de NDVI aumentan desde el interior de la SBI hacia la selva circundante con mayor contraste en la época de secas, por lo que la imagen de esta época proporcionó una mejor clasificación de la SBI

Carbon Stocks, Species Diversity and Their Spatial Relationships in the Yucatán Peninsula, Mexico

Integrating information about the spatial distribution of carbon stocks and species diversity in tropical forests over large areas is fundamental for climate change mitigation and biodiversity conservation. In this study, spatial models showing the distribution of carbon stocks and the number of species were produced in order to identify areas that maximize carbon storage and biodiversity in the tropical forests of the Yucatan Peninsula, Mexico. We mapped carbon density and species richness of trees using L-band radar backscatter data as well as radar texture metrics, climatic and field data with the random forest regression algorithm. We reduced sources of errors in plot data of the national forest inventory by using correction factors to account for carbon stocks of small trees (<7.5 cm DBH) and for the temporal difference between field data collection and imagery acquisition. We created bivariate maps to assess the spatial relationship between carbon stocks and diversity. Model validation of the regional maps obtained herein using an independent data set of plots resulted in a coefficient of determination (R2) of 0.28 and 0.31 and a relative mean square error of 38.5% and 33.0% for aboveground biomass and species richness, respectively, at pixel level. Estimates of carbon density were influenced mostly by radar backscatter and climatic data, while those of species richness were influenced mostly by radar texture and climatic variables. Correlation between carbon density and species richness was positive in 79.3% of the peninsula, while bivariate maps showed that 39.6% of the area in the peninsula had high carbon stocks and species richness. Our results highlight the importance of combining carbon and diversity maps to identify areas that are critical—both for maintaining carbon stocks and for conserving biodiversity

Mapping Tree Species Deciduousness of Tropical Dry Forests Combining Reflectance, Spectral Unmixing, and Texture Data from High-Resolution Imagery

In tropical dry forests, deciduousness (i.e., leaf shedding during the dry season) is an important adaptation of plants to cope with water limitation, which helps trees adjust to seasonal drought. Deciduousness is also a critical factor determining the timing and duration of carbon fixation rates, and affecting energy, water, and carbon balance. Therefore, quantifying deciduousness is vital to understand important ecosystem processes in tropical dry forests. The aim of this study was to map tree species deciduousness in three types of tropical dry forests along a precipitation gradient in the Yucatan Peninsula using Sentinel-2 imagery. We propose an approach that combines reflectance of visible and near-infrared bands, normalized difference vegetation index (NDVI), spectral unmixing deciduous fraction, and several texture metrics to estimate the spatial distribution of tree species deciduousness. Deciduousness in the study area was highly variable and decreased along the precipitation gradient, while the spatial variation in deciduousness among sites followed an inverse pattern, ranging from 91.5 to 43.3% and from 3.4 to 9.4% respectively from the northwest to the southeast of the peninsula. Most of the variation in deciduousness was predicted jointly by spectral variables and texture metrics, but texture metrics had a higher exclusive contribution. Moreover, including texture metrics as independent variables increased the variance of deciduousness explained by the models from R2 = 0.56 to R2 = 0.60 and the root mean square error (RMSE) was reduced from 16.9% to 16.2%. We present the first spatially continuous deciduousness map of the three most important vegetation types in the Yucatan Peninsula using high-resolution imagery.Arts, Faculty ofGeography, Department ofReviewedFacultyResearche

Improving Species Diversity and Biomass Estimates of Tropical Dry Forests Using Airborne LiDAR

The spatial distribution of plant diversity and biomass informs management decisions to maintain biodiversity and carbon stocks in tropical forests. Optical remotely sensed data is often used for supporting such activities; however, it is difficult to estimate these variables in areas of high biomass. New technologies, such as airborne LiDAR, have been used to overcome such limitations. LiDAR has been increasingly used to map carbon stocks in tropical forests, but has rarely been used to estimate plant species diversity. In this study, we first evaluated the effect of using different plot sizes and plot designs on improving the prediction accuracy of species richness and biomass from LiDAR metrics using multiple linear regression. Second, we developed a general model to predict species richness and biomass from LiDAR metrics for two different types of tropical dry forest using regression analysis. Third, we evaluated the relative roles of vegetation structure and habitat heterogeneity in explaining the observed patterns of biodiversity and biomass, using variation partition analysis and LiDAR metrics. The results showed that with increasing plot size, there is an increase of the accuracy of biomass estimations. In contrast, for species richness, the inclusion of different habitat conditions (cluster of four plots over an area of 1.0 ha) provides better estimations. We also show that models of plant diversity and biomass can be derived from small footprint LiDAR at both local and regional scales. Finally, we found that a large portion of the variation in species richness can be exclusively attributed to habitat heterogeneity, while biomass was mainly explained by vegetation structure

Pearson correlation analysis of 18 variables obtained from Worldclim 1.4 [48] for 10,000 randomly chosen points across the study area.

Cells above the diagonal show the r value; cells below the diagonal show the density distribution. (PDF)</p