Landsat data respond to variations in the structure of Caatinga plant communities along a successional gradient.

Plant community succession is generally approached with phytosociological methods, but field surveys are time-consuming, expensive, and limited to several of sites. Remote sensing offers an efficient and economical way to analyze vegetation on large extensions and in inaccessible areas. Most studies addressing remote sensing and tree community succession refer to forest physiognomies. We investigated whether structural changes that occur in non-forest physiognomies are identified by multispectral sensor images (OLI-Landsat). Thirteen 0.1-ha plots were set up in Caatinga fragments aging 10-15, 20-25, 30-35, 40-45 and >50 years to calculate the total density of individuals (TD), mean canopy height (H), total basal area (G) and total aboveground biomass (AGB). We performed correlation analyses between these structural descriptors and eight remote sensing variables (reflectance data and spectral indices) obtained from Landsat images at the end of the rainy season and during the dry season. Blue and short-wave infrared reflectances were negatively correlated with mean height, basal area and biomass, regardless of the analyzed scene (coefficients between -0.58 and -0.79). The litter layer (a non-photosynthetic vegetation component) and the soil exposure are important factors influencing the spectral data.

Spatial patterns and determinants of avocado frontier dynamics in Mexico.

The surging demand for commodity crops has led to rapid and severe agricultural frontier expansion globally and has put producing regions increasingly under pressure. However, knowledge about spatial patterns of agricultural frontier dynamics, their leading spatial determinants, and socio-ecological trade-offs is often lacking, hindering contextualized decision making towards more sustainable food systems. Here, we used inventory data to map frontier dynamics of avocado production, a cash crop of increasing importance in global diets, for Michoacán, Mexico, before and after the implementation of the North American Free Trade Agreement (NAFTA). We compiled a set of environmental, accessibility and social variables and identified the leading determinants of avocado frontier expansion and their interactions using extreme gradient boosting. We predicted potential expansion patterns and assessed their impacts on areas important for biodiversity conservation. Avocado frontiers expanded more than tenfold from 12,909 ha (1974) to 152,493 ha (2011), particularly after NAFTA. Annual precipitation, distance to settlements, and land tenure were key factors explaining avocado expansion. Under favorable climatic and accessibility conditions, most avocado expansion occurred on private lands. Contrary, under suboptimal conditions, most avocado expansion occurred on communal lands. Large areas suitable for further avocado expansion overlapped with priority sites for restoration, highlighting an imminent conflict between conservation and economic revenues. This is the first analysis of avocado frontier dynamics and their spatial determinants across a major production region and our results provide entry points to implement government-based strategies to support small-scale farmers, mostly those on communal lands, while trying to minimize the socio-environmental impacts of avocado production. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10113-022-01883-6.

Stage 1 registered report: spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level.

In this stage 1 registered report, we propose an analysis of the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We will compute weekly Moran index to assess spatial autocorrelation over time and identify clusters of the disease using the "flexibly shaped spatial scan" approach. Finally, different distance models will be compared to select the best suited to predict inter-municipality contagion. This study will help us understand the spread of the epidemic over the Mexican territory and give insights to model and predict the epidemic behavior.

Spatio-temporal dataset of COVID-19 outbreak in Mexico.

Our understanding of how COVID-19 spreads over a territory needs to be improved. For example, the evaluation of disease spatiotemporal distribution and its association with other characteristics can help identify covariates, model the behavior of the epidemic, and provide useful information for decision making. Data were compiled from the National Population Council (CONAPO), Google, the National Institute of Statistics and Geography (INEGI), and the Secretary of Health. The data describe the cases of COVID and characteristics of the population, such as distribution, mobility, and prevalence of chronic diseases such as diabetes, hypertension, and obesity. These data were processed to be compatible and georeferenced to a common geographic framework to facilitate spatial analysis in a geographic information system (GIS).

Spatiotemporal patterns of the COVID-19 epidemic in Mexico at the municipality level.

In recent history, Coronavirus Disease 2019 (COVID-19) is one of the worst infectious disease outbreaks affecting humanity. The World Health Organization has defined the outbreak of COVID-19 as a pandemic, and the massive growth of the number of infected cases in a short time has caused enormous pressure on medical systems. Mexico surpassed 3.7 million confirmed infections and 285,000 deaths on October 23, 2021. We analysed the spatio-temporal patterns of the COVID-19 epidemic in Mexico using the georeferenced confirmed cases aggregated at the municipality level. We computed weekly Moran's I index to assess spatial autocorrelation over time and identify clusters of the disease using the "flexibly shaped spatial scan" approach. Finally, we compared Euclidean, cost, resistance distances and gravitational model to select the best-suited approach to predict inter-municipality contagion. We found that COVID-19 pandemic in Mexico is characterised by clusters evolving in space and time as parallel epidemics. The gravitational distance was the best model to predict newly infected municipalities though the predictive power was relatively low and varied over time. This study helps us understand the spread of the epidemic over the Mexican territory and gives insights to model and predict the epidemic behaviour.

Improving aboveground biomass maps of tropical dry forests by integrating LiDAR, ALOS PALSAR, climate and field data.

BACKGROUND: Reliable information about the spatial distribution of aboveground biomass (AGB) in tropical forests is fundamental for climate change mitigation and for maintaining carbon stocks. Recent AGB maps at continental and national scales have shown large uncertainties, particularly in tropical areas with high AGB values. Errors in AGB maps are linked to the quality of plot data used to calibrate remote sensing products, and the ability of radar data to map high AGB forest. Here we suggest an approach to improve the accuracy of AGB maps and test this approach with a case study of the tropical forests of the Yucatan peninsula, where the accuracy of AGB mapping is lower than other forest types in Mexico. To reduce the errors in field data, National Forest Inventory (NFI) plots were corrected to consider small trees. Temporal differences between NFI plots and imagery acquisition were addressed by considering biomass changes over time. To overcome issues related to saturation of radar backscatter, we incorporate radar texture metrics and climate data to improve the accuracy of AGB maps. Finally, we increased the number of sampling plots using biomass estimates derived from LiDAR data to assess if increasing sample size could improve the accuracy of AGB estimates. RESULTS: Correcting NFI plot data for both small trees and temporal differences between field and remotely sensed measurements reduced the relative error of biomass estimates by 12.2%. Using a machine learning algorithm, Random Forest, with corrected field plot data, backscatter and surface texture from the L-band synthetic aperture radar (PALSAR) installed on the on the Advanced Land Observing Satellite-1 (ALOS), and climatic water deficit data improved the accuracy of the maps obtained in this study as compared to previous studies (R2 = 0.44 vs R2 = 0.32). However, using sample plots derived from LiDAR data to increase sample size did not improve accuracy of AGB maps (R2 = 0.26). CONCLUSIONS: This study reveals that the suggested approach has the potential to improve AGB maps of tropical dry forests and shows predictors of AGB that should be considered in future studies. Our results highlight the importance of using ecological knowledge to correct errors associated with both the plot-level biomass estimates and the mismatch between field and remotely sensed data.

High overlap between traditional ecological knowledge and forest conservation found in the Bolivian Amazon.

It has been suggested that traditional ecological knowledge (TEK) may play a key role in forest conservation. However, empirical studies assessing to what extent TEK is associated with forest conservation compared with other variables are rare. Furthermore, to our knowledge, the spatial overlap of TEK and forest conservation has not been evaluated at fine scales. In this paper, we address both issues through a case study with Tsimane' Amerindians in the Bolivian Amazon. We sampled 624 households across 59 villages to estimate TEK and used remote sensing data to assess forest conservation. We ran statistical and spatial analyses to evaluate whether TEK was associated and spatially overlapped with forest conservation at the village level. We find that Tsimane' TEK is significantly and positively associated with forest conservation although acculturation variables bear stronger and negative associations with forest conservation. We also find a very significant spatial overlap between levels of Tsimane' TEK and forest conservation. We discuss the potential reasons underpinning our results, which provide insights that may be useful for informing policies in the realms of development, conservation, and climate. We posit that the protection of indigenous cultural systems is vital and urgent to create more effective policies in such realms.

Monitoreo de los patrones de deforestación en el corredor biológico Mesoamericano, México / Monitoring deforestation patterns in the Mesoamerican biological corridor, Mexico / Monitoramento dos padrões de desmatamento no corredor biológico Mesoamericano, México

Se realizó un monitoreo de la deforestación en el Corredor Biológico Mesoamericano, porción mexicana (CBM-M), a través de la comparación de las bases cartográficas de uso y cobertura del suelo elaborados por el INEGI y el Inventario Forestal Nacional del 2000 hecho por el Instituto de Geografía de la UNAM, ambas en escala 1:250000. Se integró un sistema de información geográfica que permitió elaborar mapas de procesos de cambio y cuantificar tasas y matrices de cambio para esta importante región biológica. La pérdida forestal estimada en el CBM-M fue de un 1´10(6)ha en 22 años, con una tasa de deforestación de -0,7%, donde los pastizales representaron el 70% de los cambios. La conversión de bosques a pastizales se presentó en forma más acentuada en el corredor biológico Montes Azules-El Triunfo (CBM-T), afectando 14% de su superficie, mientras que en el corredor biológico Calakmul-Sian Ka’an (CBC-S) representó el 7%. La deforestación por agricultura de temporal se distribuyó en el 5% del CBM-M, no obstante este proceso de cambio fue mayor en el CBC-S (6%, 231000ha), ya que significó casi el doble de la superficie que estos cambios ocuparon en el CBM-T (4%, 126000ha). Los resultados sugieren que el CBM-T presenta severa antropización y las áreas deforestadas tienden a fusionarse, lo que pone en riesgo la conectividad de este corredor biológico.

The deforestation in the Mexican portion of the Mesoamerican Biological Corridor (CBM-M) was assessed by comparing two cartographic sources at a scale 1:250000, the land use/cover maps from INEGI (National Institute of Geography, Statistics and Informatics) and the 2000 National Forest Inventory from the Institute of Geography of the National Autonomous University of Mexico. A geographical information system was integrated, which allowed mapping land use/cover change (LUCC) processes and calculating the change rate and matrix for this important biological region. The results show an average annual deforestation rate of 0.7% for the CBM-M, with a total forest reduction estimated in 1´10(6)ha over 22 years, where the conversion to grassland represented 70% of the changes. The forest to pastureland conversion was more important in the Montes Azules-El Triunfo Biogical corridor (CBM-T), affecting 14% of its surface; while in the Calakmul-Sian Ka’an Biological Corridor (CBC-S) it affected 7%. Deforestation to slash and burn agriculture occupied 5% of the Mesoamerican Biological corridor; however, this change process was more important in CBC-S (6%, 231000ha), almost twice the surface affected at the Montes Azules Biological Corridor (4%, 126000hectares). The results suggest that relevant man-made LUCC processes are taking place in the Montes Azules Biological Corridor, endangering the biological and ecological connectivity of this region.

Realizou-se um monitoramento do desmatamento no Corredor Biológico Mesoamericano, na porção mexicana (CBM-M), a través da comparação das bases cartográficas de uso e cobertura do solo elaborados pelo INEGI e o Inventário Florestal Nacional do ano 2000 feito pelo Instituto de Geografia da UNAM, ambas na escala 1:250000. Integrou-se um sistema de informação geográfica que permitiu elaborar mapas de processos de mudança e quantificar taxas e matrizes de mudança para esta importante região biológica. A perda florestal estimada no CBM-M foi de um 1×10(6)ha em 22 anos, com uma taxa de desmatamento de -0,7%, onde as pastagens representaram 70% das mudanças. A conversão de bosques a pastagens se apresentou em forma mais acentuada no corredor biológico Montes Azules-El Triunfo (CBM-T), afetando 14% de sua superfície, enquanto que no corredor biológico Calakmul-Sian Ka’an (CBC-S) representou 7%. O desmatamento por agricultura temporária se distribuiu em 5% do CBM-M, no entanto este processo de mudança foi maior em CBC-S (6%, 231.000ha), já que significou quase o dobro da superfície que estas mudanças ocuparam no CBM-T (4%, 126000ha). Os resultados sugerem que CBM-T apresenta severa antropização e as áreas desmatadas tendem a fusionar-se, o que põe em risco a conectividade deste corredor biológico.

Modelling vegetation diversity types in Mexico based upon topographic features

Se evaluó el papel de la topografía como variable sustituta para explicar patrones de diversidad de tipos de vegetación (DTV). Se calculó el índice de diversidad de vegetación de Simpson para todo el territorio mexicano utilizando mapas de uso del suelo y vegetación por medio de SIG. Se determinó la correlación entre diversidad de vegetación y algunos atributos topográficos (altitud, rango de elevación, pendiente, rugosidad y exposición), encontrándose correlación significativa entre las variables topográficas y la diversidad de vegetación (Coeficiente de Spearman >0,4, p=0,01 con tres variables: rango y promedio de elevación, y pendiente) con una ventana óptima de 80×80km². Luego se modeló los DTV con base en los atributos topográficos usando un enfoque de redes neurales artificiales. La comparación entre los mapas de DTV modelados y reales mostró que el modelo es una buena estimación de la diversidad de vegetación. El análisis de errores sugiere que los DTV no pueden explicarse totalmente por atributos topográficos, aunque éstos juegan un papel fundamental en los DTV a escala regional y continental. Las coberturas del suelo y la vegetación reflejan los patrones de distribución de la biodiversidad, por lo que la modelación de los DTV es un enfoque prometedor para evaluar la biodiversidad. La conclusión principal es que las variables topográficas, disponibles en diferentes escalas de resolución para la mayor parte del mundo, pueden ser utilizadas para representar patrones regionales de biodiversidad. Este aspecto es crucial en países tropicales, los cuales presentan alta biodiversidad pero frecuentemente carecen de bases de datos sobre coberturas del suelo confiables y actualizadas.

Assessing protected area effectiveness using surrounding (buffer) areas environmentally similar to the target area.

Many studies are based on the assumption that an area and its surrounding (buffer) area present similar environmental conditions and can be compared. For example, in order to assess the effectiveness of a protected area, the land use/cover changes are compared inside the park with its surroundings. However, the heterogeneity in spatial variables can bias this assessment: we have shown that most of the protected areas in Mexico present significant environmental differences between their interior and their surroundings. Therefore, a comparison that aims at assessing the effectiveness of conservation strategies, must be cautioned. In this paper, a simple method which allows the generation of a buffer area that presents similar conditions with respect to a set of environmental variables is presented. The method was used in order to assess the effectiveness of the Calakmul Biosphere Reserve, a protected area located in the south-eastern part of Mexico. The annual rate of deforestation inside the protected area, the standard buffer area (based upon distance from the protected area only) and the similar buffer area (taking into account distance along with some environmental variables) were 0.3, 1.3 and 0.6%, respectively. These results showed that the protected area was effective in preventing land clearing, but that the comparison with the standard buffer area gave an over-optimistic vision of its effectiveness.