39 results on '"Miguel Angel Castillo-Santiago"'
Search Results
2. Cambio de uso del suelo en la cuenca del río Sabinal, Chiapas, México/Land-use change in the Sabinal river watershed, Chiapas, Mexico
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Mercedes Concepción Gordillo-Ruiz and Miguel Angel Castillo-Santiago
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Chiapas ,cambio en la cobertura del suelo ,urbanización ,deforestación ,migración rural ,Agriculture - Abstract
. Con el propósito de conocer que los factores promueven el cambio en la cobertura del suelo en la cuenca del río Sabinal, Chiapas, este trabajo analiza la relación entre mapas de cambio en la cobertura del suelo y estadísticas socioeconómicas. Se elaboraron mapas de la cobertura del suelo de 1992 y 2009 con imágenes satelitales de alta resolución; también se colectaron y analizaron datos socioeconómicos relacionados con el uso del suelo. La comparación de los mapas muestra que la tasa de deforestación es del 0.5 %, la cual es más baja que la reportada en otras zonas de bosque tropical seco; la población rural se ha mantenido a niveles similares de 1990, pero la población urbana creció más del doble. La supercie promedio de potreros por productor se ha duplicado, pero la de cultivos se mantiene similar a 1992, ya que los campesinos prerieron sistemas de producción extensivos. Los terrenos agrícolas han disminuido en extensión y se han desplazado a zonas de mayor pendiente debido a la expansión de las áreas urbanas. Se encontró una alta dependencia de insumos de otras regiones del país, pero la producción de alimentos básicos en la cuenca se ha mantenido a niveles de 1991. more...
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- 2017
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Catalog
3. How effective are biodiversity conservation payments in Mexico?
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Sébastien Costedoat, Esteve Corbera, Driss Ezzine-de-Blas, Jordi Honey-Rosés, Kathy Baylis, and Miguel Angel Castillo-Santiago
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Medicine ,Science - Abstract
We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled. more...
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- 2015
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4. Comment on Gebhardt et al. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923–3943
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Jean-François Mas, Stéphane Couturier, Jaime Paneque-Gálvez, Margaret Skutsch, Azucena Pérez-Vega, Miguel Angel Castillo-Santiago, and Gerardo Bocco
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land cover mapping ,accuracy assessment ,Landsat ,image classification ,Monitoring, Reporting and Verification (MRV) ,Reduced Emissions from Deforestation and Degradation plus (REDD+) ,Science - Abstract
Gebhardt et al. (2014) presented the Monitoring Activity Data for the Mexican REDD+ program (MAD-MEX), an automatic nation-wide land cover monitoring system for the Mexican REDD+ MRV. Though MAD-MEX represents a valuable first effort toward establishing a national reference emissions level for the implementation of REDD+ in Mexico, in this paper, we argue that this land cover system has important limitations that may prevent it from becoming operational for REDD+ MRV. Specifically, we show that (1) the accuracy assessment of MAD-MEX land cover maps is optimistically biased; (2) the ability of MAD-MEX to monitor land cover change, including deforestation and forest degradation; is poor and (3) the use of an entirely automatic classification approach, such as that followed by MAD-MEX, is highly problematic in the case of a large and heterogeneous country like Mexico. We discuss these limitations and call into question the ability of a land cover monitoring system, such as MAD-MEX, both to elaborate a national reference emissions level and to monitor future forest cover change, as part of a REDD+ MRV system. We provide some insights with the aim of improving the development of nation-wide land cover monitoring systems in Mexico and elsewhere. more...
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- 2016
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5. Using satellite estimates of aboveground biomass to assess carbon stocks in a mixed-management, semi-deciduous tropical forest in the Yucatan Peninsula
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David T. Milodowski, Juan Manuel Dupuy, Miguel Angel Castillo-Santiago, Mathew Williams, Stephanie P. George-Chacón, Jean-François Mas, and José Luis Hernández-Stefanoni
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Yucatan peninsula ,Lidar ,Remote sensing (archaeology) ,Geography, Planning and Development ,Semi-deciduous ,Environmental science ,Forestry ,Satellite ,Aboveground biomass ,Spatial distribution ,Tropical forest ,Water Science and Technology - Abstract
Information on the spatial distribution of forest aboveground biomass (AGB) and its uncertainty is important to evaluate management and conservation policies in tropical forests. However, the scarcity of field data and robust protocols to propagate uncertainty prevent a robust estimation through remote sensing. We upscaled AGB from field data to LiDAR, and to landscape scale using Sentinel-2 and ALOS-PALSAR through machine learning, propagated uncertainty using a Monte Carlo framework and explored the relative contributions of each sensor. Sentinel-2 outperformed ALOS-PALSAR (R2 = 0.66, vs 0.50), however, the combination provided the best fit (R2 = 0.70). The combined model explained 49% of the variation comparing against plots within the calibration area, and 17% outside, however, 94% of observations outside calibration area fell within the 95% confidence intervals. Finally, we partitioned the distribution of AGB in different management and conservation categories for evaluating the potential of different strategies for conserving carbon stock. more...
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- 2021
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6. Historia y cambios en el paisaje en dos ejidos de la Selva Lacandona, Chiapas
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Francisco Vázquez, Diana del Carmen Ríos Quiroz, Miguel Angel Castillo Santiago, and Leopoldo Medina Sanson
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Geography, Planning and Development ,Earth-Surface Processes - Abstract
El diseño de estrategias exitosas para la conservación de los bosques demanda un entendimiento de las causas que originan el cambio de uso del suelo. En este trabajo se realizó un análisis histórico del cambio de uso del suelo en dos ejidos de la Selva Lacandona, en Chiapas. Se combinaron cartografía participativa y percepción remota para reconstruir los cambios ocurridos en el período 1986-2018, adicionalmente se realizaron talleres participativos y entrevistas semiestructuradas. Identificamos tres etapas en la historia de cambios en el uso del suelo, a) la colonización y adaptación (1986-1994), b) la intervención productiva (1994-2005) y c) la expansión ganadera y la conservación de los bosques (2005-2018). En cada una de ellas, los factores económicos y políticos causantes del cambio contribuyeron manera diferenciada y fueron mediados a nivel local por la organización específica en cada ejido. Se observó una fuerte disminución de las áreas dedicadas a la producción agrícola en favor de la ganadería. A pesar de que en la última etapa se han destinado recursos públicos para promover la conservación de los bosques, la infraestructura construida, la débil presencia institucional y la fuerte especialización en la producción bovina dificultan los esfuerzos por detener la deforestación. more...
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- 2021
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7. Near Real-Time Change Detection System Using Sentinel-2 and Machine Learning: A Test for Mexican and Colombian Forests
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Ana María Pacheco-Pascagaza, Yaqing Gou, Valentin Louis, John F. Roberts, Pedro Rodríguez-Veiga, Polyanna da Conceição Bispo, Fernando D. B. Espírito-Santo, Ciaran Robb, Caroline Upton, Gustavo Galindo, Edersson Cabrera, Indira Paola Pachón Cendales, Miguel Angel Castillo Santiago, Oswaldo Carrillo Negrete, Carmen Meneses, Marco Iñiguez, and Heiko Balzter more...
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tropical forests ,near real-time ,Tropical forests ,Science ,vegetation change detection ,Vegetation change detection ,Ecology and Environment ,machine learning ,Laboratory of Geo-information Science and Remote Sensing ,Computer Science ,Machine learning ,General Earth and Planetary Sciences ,Data and Information ,deforestation ,Near real-time ,Laboratorium voor Geo-informatiekunde en Remote Sensing ,Deforestation - Abstract
The commitment by over 100 governments covering over 90% of the world’s forests at the COP26 in Glasgow to end deforestation by 2030 requires more effective forest monitoring systems. The near real-time (NRT) change detection of forest cover loss enables forest landowners, government agencies and local communities to monitor natural and anthropogenic disturbances in a much timelier fashion than the thematic maps that are released every year. NRT deforestation alerts enable the establishment of more up-to-date forest inventories and rapid responses to unlicensed logging. The Copernicus Sentinel-2 satellites provide operational Earth observation (EO) data from multi-spectral optical/near-infrared wavelengths every five days at a global scale and at 10 m resolution. The amount of acquired data requires cloud computing or high-performance computing for ongoing monitoring systems and an automated system for processing, analyzing and delivering the information promptly. Here, we present a Sentinel-2-based NRT change detection system, assess its performance over two study sites, Manantlán in Mexico and Cartagena del Chairá in Colombia, and evaluate the forest changes that occurred in 2018. An independent validation with very high-resolution PlanetScope (~3 m) and RapidEye (~5 m) data suggests that the proposed NRT change detection system can accurately detect forest cover loss (> 87%), other vegetation loss (> 76%) and other vegetation gain (> 71%). Furthermore, the proposed NRT change detection system is designed to be attuned using in situ data. Therefore, it is scalable to larger regions, entire countries and even continents. more...
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- 2022
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8. Regeneración y conservación del bosque comunitario, el caso de Chichila, Guerrero
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Mauricio Valencia Negrete, Miguel Angel Castillo Santiago, Eduardo Bello Baltazar, and Miguel Ángel Vásquez Sánchez
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Forestry - Abstract
A pesar de que a escala global se han estudiado las causas del cambio de uso de suelo, localmente existen pocos estudios detallados. En este trabajo se estudiaron los cambios de cobertura y uso de suelo de una comunidad agraria en Guerrero, México, en un periodo de 24 años. Se emplearon imágenes satelitales y ortofotos para elaborar mapas de vegetación y usos de suelo de alta resolución de los años 1995, 2009 y 2019. Adicionalmente se realizaron entrevistas a actores clave y se acopiaron y analizaron estadísticas productivas para identificar las causas del cambio en el uso del suelo. En los primeros años (1995–2009), se registró un aumento de la cobertura forestal de 259 ha (5.3%) y una disminución en la agricultura de 145 ha (3%). En la última etapa (2009–2019) la cobertura forestal aumentó 56 ha (1.2%) y la clase agricultura disminuyó 59 ha (1.2%). La recuperación de la cobertura forestal estuvo relacionada con un par de factores concomitantes, tales como el abandono de tierras agrícolas debido a la migración y el fortalecimiento de las reglas de acceso a los recursos forestales, este último en buena medida fue motivado por los beneficios obtenidos de la provisión de servicios ambientales hidrológicos de los bosques comunitarios. more...
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- 2022
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9. Combining LiDAR data and airborne imagery of very high resolution to improve aboveground biomass estimates in tropical dry forests
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Miguel Angel Castillo-Santiago, Juan Manuel Dupuy, Kristofer D. Johnson, J. Luis Hernández-Stefanoni, and Gabriela Reyes-Palomeque
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0106 biological sciences ,Very high resolution ,Tropical and subtropical dry broadleaf forests ,010504 meteorology & atmospheric sciences ,Environmental science ,Forestry ,Lidar data ,Atmospheric sciences ,Aboveground biomass ,010603 evolutionary biology ,01 natural sciences ,0105 earth and related environmental sciences - Abstract
Knowledge of the spatial distribution of aboveground biomass (AGB) is crucial to guide forest conservation and management to maintain carbon stocks. LiDAR has been highly successful for this purpose, but has limited availability. Very-high resolution ( more...
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- 2019
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10. Cambios en la cobertura y uso del suelo en la región del Soconusco, Chiapas
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Rosa Elena Escobar Flores and Miguel Angel Castillo Santiago
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intensificación de la agricultura ,urbanización ,pérdida de sistemas agroforestales ,palma de aceite ,Biodiversity ,Forestry ,uso de suelo ,Land cover ,Vegetation ,SD1-669.5 ,Environmental technology. Sanitary engineering ,Geography ,Deforestation ,deforestación ,Urbanization ,Threatened species ,General Earth and Planetary Sciences ,Land use, land-use change and forestry ,Mangrove ,TD1-1066 ,General Environmental Science - Abstract
El Soconusco se caracteriza por ser una de las regiones agrícolas más productivas del estado de Chiapas, en la que aún se conservan zonas de alta biodiversidad amenazadas por el cambio de uso del suelo. El objetivo de este trabajo fue analizar las trayectorias del cambio en la cobertura y usos del suelo en tres cuencas de dicha región durante un período de 25 años. Se clasificaron imágenes de satélite de 1990, 2000 y 2015. Los resultados mostraron una significativa pérdida de la vegetación natural (bosques, manglares y vegetación secundaria), además de la expansión de los asentamientos humanos. Se identificaron procesos diferentes de cambio en cada uno de los paisajes evaluados: Costa, Planicie y Sierra. En la Planicie, el cambio de uso de suelo predominante fue la sustitución de cultivos básicos por plantaciones agrícolas. En los paisajes de Sierra y Costa, donde hay remanentes importantes de bosques, el cambio más evidente fue la deforestación. A pesar de que en la región se registraron fuertes incrementos en la densidad poblacional y en las áreas urbanas, las zonas dedicadas a la producción de cultivos básicos se han mantenido sin modificaciones. El patrón de cambios en la cobertura de suelo indica que la región de estudio está en un proceso de intensificación de la agricultura y de la urbanización. more...
- Published
- 2021
11. Estimación de la distribución espacial de los bosques perturbados en Chiapas, México, usando datos satelitales e información auxiliar
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Miguel ángel Castillo-Santiago, Edith Mondragon-Vazquez, Flor Rocío Espinosa-Jiménez, Rosa Elena Escobar-Flores, Rafael García-González, Roberto Domínguez-Vera, Sandra Patricia Chanona-Pérez, Jean Francois Mas, and José Luis Hernández-Stefanoni more...
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Biomasa leñosa ,bosques secundarios ,fragmentación forestal ,sistemas agroforestales ,tipos de vegetación ,Botany ,QK1-989 - Abstract
Antecedentes: Los mapas de bosques perturbados son útiles para identificar afectaciones sobre la biodiversidad y los servicios ecosistémicos. Los métodos que emplean únicamente datos espectrales para detectar las perturbaciones a nivel regional tienen limitaciones. El conocimiento de expertos y el análisis de fragmentación puede mejorar la estimación. Preguntas: ¿Cuál es la distribución de los bosques perturbados en una región de alta biodiversidad? ¿Qué tipos de vegetación y regiones son las más afectadas? Descripción de los datos: imágenes satelitales SPOT 2015, Sentinel-2 de 2019. Se colectó información de la vegetación en 653 sitios. Además, se usaron datos de herbario, censos agrícolas y del Inventario Nacional Forestal. Lugar y fecha del estudio: Estado de Chiapas, durante 2018-2022. Métodos: Se elaboró un mapa híbrido de los tipos de vegetación enfatizando la identificación de bosques secundarios, también se realizó un análisis de fragmentación y se calculó la biomasa leñosa por tipo de bosque. Resultados: El 40 % de la superficie del Estado mantiene una cobertura arbórea; pero solo en el 12 % no se aprecia perturbación; la mayor parte de los bosques no perturbados se encuentran en tres regiones: Selva Lacandona, Sierra Madre y Planicie del Golfo. En general la biomasa de los bosques perturbados es significativamente menor que la de su contraparte madura. Conclusiones: En Chiapas la distribución de los bosques en buen estado de conservación está restringida; casi la mitad de ellos se encuentran fuera de las ANP, por lo que es imperativo promover estrategias adicionales para su manejo y conservación. more...
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- 2024
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12. Mapeo de la biomasa aérea de los bosques mediante datos de sensores remotos y R
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José Luis Hernández Stefanoni, Miguel Ángel Castillo Santiago, Juan Andrés Mauricio, Jean-François Mas, Fernando Tun Dzul, Juan Manuel Dupuy Rada, José Luis Hernández Stefanoni, Miguel Ángel Castillo Santiago, Juan Andrés Mauricio, Jean-François Mas, Fernando Tun Dzul, and Juan Manuel Dupuy Rada more...
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Este libro proporciona una guía para llevar a cabo el mapeo de la biomasa aérea del bosque en grandes superficies relacionando datos de campo con la información derivada de imágenes de satélite. La metodología para el mapeo de esta variable utiliza scripts desarrollados en el lenguaje R, e incluye la estimación de la biomasa en campo, preprocesamiento de las imágenes, ajuste de modelos de predicción, así como su aplicación para obtener mapas de distribución espacial. Esta obra se dirige a investigadores, estudiantes, técnicos forestales de organizaciones no gubernamentales y del gobierno, y a usuarios de la percepción remota en general que requieran obtener mapas de diferentes atributos de la vegetación en sus sitios de interés. more...
- Published
- 2021
13. Sustained participation in a Payments for Ecosystem Services program reduces deforestation in a Mexican agricultural frontier
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Hugo Charoud, Sebastien Costedoat, Santiago Izquierdo-Tort, Lina Moros, Sergio Villamayor-Tomás, Miguel Ángel Castillo-Santiago, Sven Wunder, and Esteve Corbera
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Medicine ,Science - Abstract
Abstract Payments for Ecosystem Services (PES) provide conditional incentives for forest conservation. PES short-term effects on deforestation are well-documented, but we know less about program effectiveness when participation is sustained over time. Here, we assess the impact of consecutive renewals of PES contracts on deforestation and forest degradation in three municipalities of the Selva Lacandona (Chiapas, Mexico). PES reduced deforestation both after a single 5-year contract and after two consecutive contracts, but the impacts are only detectable in higher deforestation-risk parcels. Enrollment duration increases PES impact in these parcels, which suggests a positive cumulative effect over time. These findings suggest that improved spatial targeting and longer-term enrollment are key enabling factors to improve forest conservation outcomes in agricultural frontiers. more...
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- 2023
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14. Carbon Stocks, Species Diversity and Their Spatial Relationships in the Yucatán Peninsula, Mexico
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Juan Manuel Dupuy, Fernando Tun-Dzul, José Luis Hernández-Stefanoni, Carlos Portillo-Quintero, Juan Andres-Mauricio, and Miguel Angel Castillo-Santiago
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Tropical and subtropical dry broadleaf forests ,L-band SAR ,Science ,Biodiversity ,Species diversity ,chemistry.chemical_element ,Spatial distribution ,biodiversity ,aboveground biomass ,tropical dry forests ,texture analysis ,national forest inventory ,Climate change mitigation ,chemistry ,General Earth and Planetary Sciences ,Environmental science ,Physical geography ,Species richness ,Carbon ,Global biodiversity - Abstract
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 ( more...
- Published
- 2021
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15. Improving aboveground biomass maps of tropical dry forests by integrating LiDAR, ALOS PALSAR, climate and field data
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Jean-François Mas, J. Luis Hernández-Stefanoni, Gabriela Reyes-Palomeque, Stephanie P. George-Chacón, Juan Manuel Dupuy, Juan Andres-Mauricio, Blanca Castellanos-Basto, Miguel Angel Castillo-Santiago, Fernando Tun-Dzul, Charlotte E. Wheeler, and Raúl Abel Vaca more...
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Tropical and subtropical dry broadleaf forests ,Synthetic aperture radar ,Yucatan peninsula ,010504 meteorology & atmospheric sciences ,Forest biomass ,L-band SAR ,0211 other engineering and technologies ,02 engineering and technology ,Management, Monitoring, Policy and Law ,Spatial distribution ,01 natural sciences ,law.invention ,law ,Earth and Planetary Sciences (miscellaneous) ,Radar ,Climatic water deficit ,lcsh:Environmental sciences ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,Remote sensing ,lcsh:GE1-350 ,Global and Planetary Change ,Biomass (ecology) ,Research ,Sampling (statistics) ,Random forest ,Lidar ,Texture analysis ,General Earth and Planetary Sciences ,Environmental science - Abstract
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. more...
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- 2019
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16. Factors Limiting Formation of Community Forestry Enterprises in the Southern Mixteca Region of Oaxaca, Mexico
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José Antonio Hernández-Aguilar, Héctor Sergio Cortina-Villar, Miguel Angel Castillo-Santiago, and Luis Enrique García-Barrios
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Conservation of Natural Resources ,media_common.quotation_subject ,Forest management ,Forests ,010501 environmental sciences ,01 natural sciences ,Trees ,Ecosystem services ,Scarcity ,Mexico ,0105 earth and related environmental sciences ,media_common ,040101 forestry ,Global and Planetary Change ,Ecology ,Agroforestry ,business.industry ,Environmental resource management ,Forestry ,04 agricultural and veterinary sciences ,Payment ,Pollution ,Government Programs ,Geography ,Community forestry ,Ecotourism ,Capital (economics) ,0401 agriculture, forestry, and fisheries ,Social Planning ,business ,Temperate rainforest - Abstract
Many studies have considered community-based forestry enterprises to be the best option for development of rural Mexican communities with forests. While some of Mexico's rural communities with forests receive significant economic and social benefits from having a community forestry enterprise, the majority have not formed such enterprises. The purpose of this article is to identify and describe factors limiting the formation of community forestry enterprise in rural communities with temperate forests in the Southern Mixteca region of Oaxaca, Mexico. The study involved fieldwork, surveys applied to Community Board members, and maps developed from satellite images in order to calculate the forested surface area. It was found that the majority of Southern Mixteca communities lack the natural and social conditions necessary for developing community forestry enterprise; in this region, commercial forestry is limited due to insufficient precipitation, scarcity of land or timber species, community members' wariness of commercial timber extraction projects, ineffective local governance, lack of capital, and certain cultural beliefs. Only three of the 25 communities surveyed have a community forestry enterprise; however, several communities have developed other ways of profiting from their forests, including pine resin extraction, payment for environmental services (PES), sale of spring water, and ecotourism. We conclude that community forestry enterprise are not the only option for rural communities to generate income from their forests; in recent years a variety of forest-related economic opportunities have arisen which are less demanding of communities' physical and social resources. more...
- Published
- 2017
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17. Applicability of biodiversity databases to regional conservation planning in the tropics: A case study evaluation of the effect of environmental bias on the performance of predictive models of species richness
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Miguel Angel Castillo-Santiago, Rocío Rodiles-Hernández, Alfonso A. González-Díaz, Miriam Soria-Barreto, Luis Antonio Muñoz-Alonso, and Raúl Abel Vaca
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0106 biological sciences ,Multivariate statistics ,Ecology ,Biodiversity ,Species diversity ,Sampling (statistics) ,010603 evolutionary biology ,01 natural sciences ,010601 ecology ,Environmental science ,Physical geography ,Species richness ,Taxonomic rank ,Additive model ,Ecology, Evolution, Behavior and Systematics ,Nature and Landscape Conservation ,Sampling bias - Abstract
The biodiversity data typically available for fitting distributional models in the tropics come from museum and scientific collections which are often incomplete and prone to sampling and environmental biases. Nevertheless, most studies undertaken in tropical regions assume that collection data offers a satisfactory environmental coverage without any quantitative assessment. In this study, we investigate the effects of differences in environmental bias and coverage provided by distributional data when aggregated into different grid cell sizes, on the performance of species richness-environment models and predictions. We use an extensive data compilation, including national and regional collections, on the distribution of amphibians, reptiles and fishes in the hydrologic region of the Usumacinta River as a case study. General additive models and environmental variables are used to construct predictive models at 40, 20, 10 and 5 km grid resolutions, based on well-sampled cells. The best multivariate models included nonparametric interaction terms for the effects of precipitation and temperature and suggested an altitudinal shift in the relative importance of energy and water in determining the distribution of species richness. For fishes, geomorphology accounted for fine scale variation in species richness along the hydrologic network, indicated by peaks in species diversity at the junction of the major rivers where major accumulation of water and sediments occurs. For all taxonomic groups, we found that sampling biases deviated most from the mean bias at the extremes of gradients accounting for important environmental factors. The pattern of environmental bias changed with grid size, with the form and amount of change being case-specific. Biases affected distribution predictions when compared with unbiased datasets. Moreover, not all models resulted best at coarser resolution as it is commonly assumed. Our results demonstrate that bias in the available data must be evaluated before mapping biodiversity distributions, irrespective of the choice of scale. more...
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- 2020
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18. Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models
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Marylin Bejarano, Rocío Rodiles-Hernández, Raúl Abel Vaca, Miguel Angel Castillo-Santiago, Dario Alejandro Navarrete-Gutiérrez, and Duncan Golicher
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Insolation ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,Computer science ,Inference ,Forests ,010501 environmental sciences ,01 natural sciences ,Econometrics ,Land use, land-use change and forestry ,Deforestation ,Land tenure ,Additive model ,Geographic Areas ,Climatology ,Multidisciplinary ,Ecology ,Geography ,Agriculture ,Terrestrial Environments ,Professions ,Agricultural Workers ,Medicine ,Livestock ,Research Article ,Urban Areas ,Conservation of Natural Resources ,Science ,Land management ,Context (language use) ,Ecosystems ,Population Metrics ,Rivers ,Mexico ,0105 earth and related environmental sciences ,Population Density ,Spatial Analysis ,Models, Statistical ,Population Biology ,business.industry ,Ecology and Environmental Sciences ,Biology and Life Sciences ,Correction ,People and Places ,Earth Sciences ,Population Groupings ,business ,Forecasting - Abstract
Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems. Deforestation is a complex process driven by multiple proximate and underlying factors and a range of scales. In this study we use a multivariate statistical analysis to provide contextual explanation for deforestation in the Usumacinta River Basin based on partial pattern matching. Our approach avoided testing trivial null hypotheses of lack of association and investigated the strength and form of the response to drivers. As not all factors involved in deforestation are easily mapped as GIS layers, analytical challenges arise due to lack of a one to one correspondence between mappable attributes and drivers. We avoided testing simple statistical hypotheses such as the detectability of a significant linear relationship between deforestation and proximity to roads or water. We developed a series of informative generalised additive models based on combinations of layers that corresponded to hypotheses regarding processes. The importance of the variables representing accessibility was emphasised by the analysis. We provide evidence that land tenure is a critical factor in shaping the decision to deforest and that direct beam insolation has an effect associated with fire frequency and intensity. The effect of winter insolation was found to have many applied implications for land management. The methodology was useful for interpreting the relative importance of sets of variables representing drivers of deforestation. It was an informative approach, thus allowing the construction of a comprehensive understanding of its causes. more...
- Published
- 2019
19. Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests
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Juan Manuel Dupuy, Gabriela Reyes-Palomeque, Dinosca Rondon-Rivera, Stephanie P. George-Chacón, Fernando Tun-Dzul, José Luis Hernández-Stefanoni, Miguel Angel Castillo-Santiago, and Astrid Helena Huechacona-Ruiz more...
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Tropical and subtropical dry broadleaf forests ,Biomass (ecology) ,airborne laser scanner ,forest biomass ,plot size ,co-registration error ,Monte Carlo simulation ,010504 meteorology & atmospheric sciences ,Science ,0211 other engineering and technologies ,Tree allometry ,Regression analysis ,02 engineering and technology ,Vegetation ,Atmospheric sciences ,01 natural sciences ,Plot (graphics) ,Lidar ,General Earth and Planetary Sciences ,Environmental science ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,Woody plant - Abstract
Accurate estimates of above ground biomass (AGB) are needed for monitoring carbon in tropical forests. LiDAR data can provide precise AGB estimations because it can capture the horizontal and vertical structure of vegetation. However, the accuracy of AGB estimations from LiDAR is affected by a co-registration error between LiDAR data and field plots resulting in spatial discrepancies between LiDAR and field plot data. Here, we evaluated the impacts of plot location error and plot size on the accuracy of AGB estimations predicted from LiDAR data in two types of tropical dry forests in Yucatán, México. We sampled woody plants of three size classes in 29 nested plots (80 m2, 400 m2 and 1000 m2) in a semi-deciduous forest (Kiuic) and 28 plots in a semi-evergreen forest (FCP) and estimated AGB using local allometric equations. We calculated several LiDAR metrics from airborne data and used a Monte Carlo simulation approach to assess the influence of plot location errors (2 to 10 m) and plot size on ABG estimations from LiDAR using regression analysis. Our results showed that the precision of AGB estimations improved as plot size increased from 80 m2 to 1000 m2 (R2 = 0.33 to 0.75 and 0.23 to 0.67 for Kiuic and FCP respectively). We also found that increasing GPS location errors resulted in higher AGB estimation errors, especially in the smallest sample plots. In contrast, the largest plots showed consistently lower estimation errors that varied little with plot location error. We conclude that larger plots are less affected by co-registration error and vegetation conditions, highlighting the importance of selecting an appropriate plot size for field forest inventories used for estimating biomass. more...
- Published
- 2018
20. Logging Pattern and Landscape Change in Southern Mexico: Identifying Potential Weaknesses and Strengthening Conservation in Community-Based Management Programs through Landscape Analysis
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J A Ascanio-Lárraga, J L León-Cortés, Miguel Angel Castillo-Santiago, and E Ramírez-Segura
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0106 biological sciences ,Landscape change ,business.industry ,010604 marine biology & hydrobiology ,Environmental resource management ,Logging ,Fragmentation (computing) ,Forestry ,Plant Science ,Community-based management ,010603 evolutionary biology ,01 natural sciences ,Spatial heterogeneity ,Geography ,Landscape analysis ,Landscape history ,business - Published
- 2018
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21. Identification of coffee agroforestry systems using remote sensing data: a review of methods and sensor data
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Agustín Escobar-López, Miguel Ángel Castillo-Santiago, Jean F. Mas, José Luis Hernández-Stefanoni, and Jorge Omar López-Martínez
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Shade-grown coffee ,classifier ,rustic ,polyculture ,monoculture ,Physical geography ,GB3-5030 - Abstract
Coffee is one of the most important agricultural commodities. Agroforestry systems (AFS) are increasingly used in coffee cultivation because of environmental benefits, adaptability of the systems, and economic profits. However, identifying the spatial distribution of AFS through remote sensing continues to be challenging. The current systematic review focuses on the accuracies obtained and the computational methods and satellite data used in mapping coffee AFS between 2000 and 2020. To facilitate the analysis, we ordered the mapped AFS into five classes according to their density and species composition of shade trees. The Kruskal-Wallis test was applied to evaluate significative differences among classes. Both shade-tree densities and species composition affected the accuracy level. The worst results were obtained in AFS retaining many woody species from the original forest and high tree density (user accuracy [Formula: see text]0.5). About the methods, maximum likelihood was the most widely used with very variable results; some non-parametric methods such as CART, ISODATA, RF, SMA, and SVM presented consistently high accuracy ([Formula: see text]0.75). High spatial resolution multispectral imagery was suitable for mapping AFS; very few studies were found with radar imagery, so it would be desirable to increase its use combined with optical data. more...
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- 2024
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22. Estimating the spatial distribution of woody biomass suitable for charcoal making from remote sensing and geostatistics in central Mexico
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Jean-François Mas, Ignacio Torres, Alejandro Flamenco-Sandoval, José Luis Hernández-Stefanoni, A.M. Fernández, Miguel Angel Castillo-Santiago, Adrian Ghilardi, and Ken Oyama
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Hydrology ,Renewable Energy, Sustainability and the Environment ,Ecology ,Geography, Planning and Development ,Tree allometry ,Geostatistics ,Management, Monitoring, Policy and Law ,Spatial distribution ,visual_art ,Linear regression ,visual_art.visual_art_medium ,Environmental science ,Satellite imagery ,Digital elevation model ,Charcoal ,Spatial analysis - Abstract
We present a cost-effective statistical approach that integrates satellite imagery, environmental variables and ground inventory data to map the spatial distribution of aboveground woody biomass suitable for charcoal making. The study was conducted in the Cuitzeo basin located in central Mexico, where charcoal is produced from oak forests covering approximately 10% of the total area (4033 km 2 ). Diameters of trees and sprouts in 78 plots of 0.2 ha each was measured. Allometric equations previously developed locally that only require tree diameters were employed to estimate the amount of woody biomass suitable for charcoal making i.e. the amount of wood that is loaded into the kilns. The performance of two statistical techniques for the interpolation of field data was assessed by cross-validation; these techniques were linear regression and regression-kriging, the second taking into account the spatial autocorrelation of data. Spectral bands, vegetation indices, texture measurements and variables derived from a Digital Elevation Model were examined as explanatory variables. Accounting for spatial autocorrelation (regression-kriging) improved the model's R 2 from 0.61 to 0.69, representing a relative error reduction of 11.3% (from 11.01 to 9.77 t ha − 1 of wood suitable for charcoal). The available stock was compared to current estimates of charcoal demand in the Cuitzeo basin and insights were given on how this information can be used to estimate the annual sustainable production potential of oak in order to account for supply–demand balances. more...
- Published
- 2013
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23. Comment on Gebhardt et al. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923–3943
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Gerardo Bocco, Stéphane Couturier, Miguel Angel Castillo-Santiago, Jean-François Mas, Margaret Skutsch, Azucena Pérez-Vega, and Jaime Paneque-Gálvez
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Monitoring, Reporting and Verification (MRV) ,010504 meteorology & atmospheric sciences ,business.industry ,Science ,Environmental resource management ,0211 other engineering and technologies ,Monitoring system ,02 engineering and technology ,Land cover ,01 natural sciences ,Reduced Emissions from Deforestation and Degradation plus (REDD+) ,Deforestation ,Forest cover ,General Earth and Planetary Sciences ,Environmental science ,land cover mapping ,Forest degradation ,business ,Landsat ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,Remote sensing ,accuracy assessment ,image classification - Abstract
Gebhardt et al. (2014) presented the Monitoring Activity Data for the Mexican REDD+ program (MAD-MEX), an automatic nation-wide land cover monitoring system for the Mexican REDD+ MRV. Though MAD-MEX represents a valuable first effort toward establishing a national reference emissions level for the implementation of REDD+ in Mexico, in this paper, we argue that this land cover system has important limitations that may prevent it from becoming operational for REDD+ MRV. Specifically, we show that (1) the accuracy assessment of MAD-MEX land cover maps is optimistically biased; (2) the ability of MAD-MEX to monitor land cover change, including deforestation and forest degradation; is poor and (3) the use of an entirely automatic classification approach, such as that followed by MAD-MEX, is highly problematic in the case of a large and heterogeneous country like Mexico. We discuss these limitations and call into question the ability of a land cover monitoring system, such as MAD-MEX, both to elaborate a national reference emissions level and to monitor future forest cover change, as part of a REDD+ MRV system. We provide some insights with the aim of improving the development of nation-wide land cover monitoring systems in Mexico and elsewhere. more...
- Published
- 2016
24. Déficit de leña en comunidades cafetaleras de Chenalhó, Chiapas
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Héctor Sergio Cortina-Villar, Juan Manuel Ramírez-López, Miguel Angel Castillo-Santiago, and Neptalí Ramírez-Marcial
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Consumption (economics) ,Agricultural science ,Geography ,Deforestation ,Environmental protection ,Stove ,Per capita ,Production (economics) ,General Medicine ,Energy source ,Firewood ,Indigenous - Abstract
La leña es fuente principal de energía para numerosas comunidades indígenas de México. Se estudió la relación entre consumo y abasto de leña y las estrategias que emprenden las familias para enfrentar el déficit de abasto de leña en un grupo de cafetaleros de la Sociedad Cooperativa Maya Vinic distribuidos en ocho comunidades de Chenalhó, Chiapas. El análisis incluyó talleres participativos, entrevistas, medición directa del consumo, colecta e identificación botánica de material vegetativo de especies usadas para leña. El consumo de leña para la época seca fue 3.7 ± 1.5 kg persona-1 día-1 y 3.9 ± 2.7 kg persona-1 día-1 en la temporada lluviosa. En general, las familias con mayor número de integrantes optimizan el uso de la leña al reducir la tasa de consumo per capita; familias con 10 a 12 integrantes consumen hasta 55% menos en relación con familias de 2-4 personas. La pérdida de la cobertura vegetal original ha resultado en una escasez de especies tradicionalmente usadas para leña (por ej., encinos) por lo que ahora se emplean especies provenientes de los sistemas agroforestales para satisfacer la demanda de leña. Las acciones para reducir el consumo se limitan a mantener apagada la fogata cuando no se preparan alimentos y usar prensa para disminuir los tiempos de preparación de las tortillas. Aunque algunas familias han adoptado el uso de estufas ahorradoras como estrategia para disminuir el consumo (4.1 ± 1.7 kg persona -1 día-1 ) no se encontraron diferencias significativas (p>0.05) con relación al consumo mediante el fogón tradicional (3.7 ± 1.5 kg persona -1 día-1 ). Aunque los cafetales son fuente continua de aprovisionamiento de leña, éstos no satisfacen las demandas, por lo que algunas familias deben comprarla con una inversión promedio de $1631 ± 1203 pesos al año. Se vislumbra que el déficit de leña se agudizará en los próximos años ante el incremento en la densidad poblacional, a la continua deforestación y empobrecimiento florístico de los fragmentos forestales que sirven como fuente de abastecimiento de leña. Hay bajas posibilidades de establecer plantaciones dendroenergéticas en las áreas actuales de producción de café, mientras éstas no compensen los beneficios económicos que se obtienen de los cafetales more...
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- 2012
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25. Estimation of tropical forest structure from SPOT-5 satellite images
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Miguel Angel Castillo-Santiago, Martin Ricker, and Bernardus H. J. de Jong
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Canopy ,Biomass (ecology) ,Forest inventory ,Variables ,media_common.quotation_subject ,Spectral bands ,Atmospheric sciences ,Basal area ,Linear regression ,General Earth and Planetary Sciences ,Cartography ,Tropical rainforest ,Mathematics ,media_common - Abstract
Predictions of tropical forest structure at the landscape level still present relatively high levels of uncertainty. In this study we explore the capabilities of high-resolution Satellite Pour l'Observation de la Terre (SPOT)-5 XS images to estimate basal area, tree volume and tree biomass of a tropical rainforest region in Chiapas, Mexico. SPOT-5 satellite images and forest inventory data from 87 sites were used to establish a multiple linear regression model. The 87 0.1-ha plots covered a wide range of forest structures, including mature forest, with values from 74.7 to 607.1 t ha-1. Spectral bands, image transformations and texture variables were explored as independent variables of a multiple linear regression model. The R2s of the final models were 0.58 for basal area, 0.70 for canopy height, 0.73 for bole volume, and 0.71 for biomass. A leave-one-out cross-validation produced a root mean square. error (RMSE) of 5.02 m2 ha-1 (relative RMSE of 22.8%) for basal area; 3.22 m (16.1%) for canopy height; 69.08 m3 ha-1 (30.7%) for timber volume, and 59.3 t ha-1 (21.2%) for biomass. In particular, the texture variable 'variance of near-infrared' turned out to be an excellent predictor for forest structure variables. more...
- Published
- 2010
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26. Carbon emissions from land-use change: an analysis of causal factors in Chiapas, Mexico
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Miguel Angel Castillo-Santiago, R. Tipper, A. Hellier, and B. H. J. de Jong
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Global and Planetary Change ,education.field_of_study ,Ecology ,business.industry ,Population ,Population density ,Deforestation ,Agriculture ,Greenhouse gas ,Environmental science ,Land use, land-use change and forestry ,Physical geography ,Land tenure ,Baseline (configuration management) ,education ,business - Abstract
This study examines the correlation between deforestation, carbon dioxide emissions and potential causal factors of land-use change within an area of 2.7 million ha in Chiapas, southern Mexico between 1975 and 1996. Digitized land-use maps and interpreted satellite images were used to quantify land-use changes. Geo-referenced databases of population and digitized maps of roads and topography were used to determine which factors could be used to explain observed changes in land-use. The study analyzed the relationship between carbon emissions during this period and two types of possible causal factors: “predisposing” factors that determine the susceptibility of a particular area of forest to change (slope, distance to agriculture and roads, land tenure) and “driving” factors representing the pressures for change (population density, poverty). The correlated factors were combined in risk matrices, which show the proportion of vulnerable carbon stocks lost in areas with defined social, economic and environmental characteristics. Such matrices could be used to predict future deforestation rates and provide a verifiable evidence-base for defining baseline carbon emissions for forest conservation projects. Based on the results of the analysis, two matrices were constructed, using population density as the single most important driving factor and distance from roads and distance from agriculture as the two alternatives for the predisposing factors of deforestation. more...
- Published
- 2006
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27. Application of the ‘Climafor’ Approach to Estimate Baseline Carbon Emissions of a Forest Conservation Project in the Selva Lacandona, Chiapas, Mexico
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B. H. J. de Jong, A. Hellier, R. Tipper, and Miguel Angel Castillo-Santiago
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Hydrology ,Global and Planetary Change ,Ecology ,Sample size determination ,Deforestation ,Greenhouse gas ,Statistics ,Variance (land use) ,Environmental science ,Sample (statistics) ,Land cover ,Baseline (configuration management) ,Confidence interval - Abstract
We present a methodology for testing and applying a regional baseline for carbon (C) emissions from land-use change, using a spatial modelling approach (hereafter called the Climafor approach). The methodology is based on an analysis of causal factors of previous land-use change (Castillo et al. 2005). Carbon risk matrices constructed from the spatial correlation analysis between observed deforestation and driving factors (Castillo et al. 2005), are used to estimate future carbonemissions within acceptable limits for a forest conservation project. The performance of two risk matrices were tested by estimating carbon emissions between 1975 and 1996 from randomly selected sample plots of sizes varying from 1,600 to 10,000 ha and comparing the results of the observed emissions from these sample plots with the model estimations. Expected emissions from continued land-use change was estimated for the community applying the risk matrices to the current land cover. The methodology provides an objective means of constructing baseline scenarios including confidence intervals, using the sum of variances of the various data sources, such as measured carbon densities, classification errors, errors in the risk matrices, and differences between the model prediction and observed emissions of sample plots due to sample size. The procedures applied in this study also give an indication of the impact of the variance in the various data sources on the size of the confidence intervals, which allows project developers to decide what data sources are essential to improve his baseline. The modelling approach to estimate the deforestation pattern is based on readily available cartographic and census data, whereas data on carbon densities are required to assess the potential for forest conservation projects to offset carbon emissions. more...
- Published
- 2005
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28. Author Correction: Sustained participation in a Payments for Ecosystem Services program reduces deforestation in a Mexican agricultural frontier
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Hugo Charoud, Sebastien Costedoat, Santiago Izquierdo‑Tort, Lina Moros, Sergio Villamayor‑Tomás, Miguel Ángel Castillo‑Santiago, Sven Wunder, and Esteve Corbera
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Medicine ,Science - Published
- 2024
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29. Impacts of the loss of neotropical highland forests on the species distribution: a case study using resplendent quetzal an endangered bird species
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Miguel Angel Castillo-Santiago, Ken Oyama, Dario Alejandro Navarrete-Gutiérrez, and Sofía Solórzano
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Cloud forest ,biology ,Mesoamerica ,Ecology ,Species distribution ,Endangered species ,Evergreen ,biology.organism_classification ,Quetzal ,Geography ,Habitat ,Ecology, Evolution, Behavior and Systematics ,Nature and Landscape Conservation ,Resplendent quetzal - Abstract
We evaluated the impacts of land-cover changes of evergreen cloud forests on the distribution of quetzals in the four mountain regions of Chiapas, Mexico. The land-cover changes were estimated comparing satellite images of 1970 and 2000. We also simulated the amount of remnant forests 50 years in the future. The past and the current distributions of quetzals were based on literature records and recent field surveys. Our results showed that in 1970 the forests occupied 973 km 2 , and in 2000, 312 km 2 , and annual loss from 3.34 to 6.85%. Our simulation suggests that 50 years from now, only one region will maintain evergreen cloud forests. In addition, we documented literature reports of 39 forests inhabited by quetzals, but in 2001 there remained 11 smallisolated forests. In order to guarantee the survival of this species, conversation efforts must be made to protect the quetzal and its habitat throughout the entire Mesoamerica region. # 2003 Elsevier Ltd. All rights reserved. more...
- Published
- 2003
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30. How effective are biodiversity conservation payments in Mexico?
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Driss Ezzine-de-Blas, Esteve Corbera, Sébastien Costedoat, Jordi Honey-Rosés, Kathy Baylis, and Miguel Angel Castillo-Santiago
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Counterfactual thinking ,Natural resource economics ,Biodiversity ,lcsh:Medicine ,forêt tropicale ,Forests ,Additionality ,K01 - Foresterie - Considérations générales ,Gouvernance ,Politique de l'environnement ,Payment ,lcsh:Science ,media_common ,Multidisciplinary ,Environmental resource management ,Incentive ,protection de la forêt ,Forêt ,P01 - Conservation de la nature et ressources foncières ,Biodiversité ,Research Article ,Conservation of Natural Resources ,media_common.quotation_subject ,Context (language use) ,gestion des ressources naturelles ,Législation de l'environnement ,Ecosystems ,Deforestation ,Humans ,K70 - Dégâts causés aux forêts et leur protection ,Mexico ,Rainforests ,Land use ,business.industry ,lcsh:R ,Déboisement ,services écosystémiques ,approches participatives ,Conservation science ,Politique forestière ,lcsh:Q ,business - Abstract
We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled. more...
- Published
- 2015
31. An estimate of the number of tropical tree species
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Thomas R. Gillespie, Manichanh Satdichanh, Pascal Boeckx, R. Vásquez, Christine Fletcher, Antti Marjokorpi, Carlos Alfredo Joly, Meredith L. Bastian, Daniel L. Kelly, Serge A. Wich, Bráulio A. Santos, Gilles Dauby, Victor A. J. Adekunle, Jochen Schöngart, Kalle Ruokolainen, Bernardus H. J. de Jong, Swapan Kumar Sarker, Nigel C. A. Pitman, Frans Bongers, Mireille Breuer-Ndoundou Hockemba, Simone Aparecida Vieira, Jean-Philippe Puyravaud, Susan G. Letcher, Susan G. Laurance, Xinghui Lu, Luís Carlos Bernacci, Alvaro Duque, Terry Sunderland, Lourens Poorter, Priya Davidar, Corneille E. N. Ewango, Henrik Meilby, Timothy J. S. Whitfeld, Badru Mugerwa, Hugo Romero-Saltos, Nina Farwig, Daniel M. Griffith, Ary Teixeira de Oliveira Filho, Miguel Angel Castillo-Santiago, I Fang Sun, Márcio de Morisson Valeriano, Jeremy A. Lindsell, Rafael L. Assis, Sandra L. Yap, Iêda Leão do Amaral, Kanehiro Kitayama, Elizabeth Kearsley, Heike Culmsee, Víctor Arroyo-Rodríguez, Marc P. E. Parren, Plinio Sist, H. S. Suresh, Francis Q. Brearley, Michael Kessler, Karl A. O. Eichhorn, Wilson Roberto Spironello, Asyraf Mansor, David B. Clark, Gabriella Fredriksson, Shin-ichiro Aiba, H. S. Dattaraja, Akira Itoh, Deborah A. Clark, Jürgen Homeier, Peter J. Bellingham, Raman Sukumar, Emanuel H. Martin, Eduardo Martins Venticinque, Saara J. DeWalt, Johanna Hurtado, Maria Teresa Fernandez Piedade, Marcio Seiji Suganuma, Jérôme Millet, Hannsjoerg Wöll, Tariq Stévart, Kipiro Damas, Patrick A. Jansen, Jangwei Tang, Sarayudh Bunyavejchewin, Navendu V. Page, Matt Bradford, Kenneth J. Feeley, Katrin Böhning-Gaese, Peter S. Ashton, Rama Chandra Prasad, Yves Laumonier, Runguo Zang, Pedro V. Eisenlohr, Polyanna da Conceição Bispo, Tsuyoshi Yoneda, Vincent P. Medjibe, Giselda Durigan, Philippe Saner, Luciana F. Alves, Eduardo Schmidt Eler, Shauna-Lee Chai, Andrea Permana, Jennifer S. Powers, Andy Hector, Andes Hamuraby Rozak, Robin L. Chazdon, Lilian Blanc, Kuswata Kartawinata, Christine B. Schmitt, Leandro Valle Ferreira, Eduardo van den Berg, João Roberto dos Santos, Rakan A. Zahawi, Duncan W. Thomas, Jean-Louis Doucet, Eduardo da Silva Pinheiro, Brad Boyle, Tran Van Do, Jean-Claude Razafimahaimodison, Bruno Garcia Luize, Robert M. Kooyman, Daniel J. Metcalfe, Axel Dalberg Poulsen, James Grogan, Xiaobo Yang, Yukai Chen, Marcelo Tabarelli, Eduardo Luís Martins Catharino, Ekananda Paudel, Felipe Zamborlini Saiter, Douglas Sheil, Jean Paul Metzger, D. Mohandass, Richard Field, Eizi Suzuki, Florian Wittmann, Felipe P. L. Melo, Peguy Tchouto, Ervan Rutishauser, Nobuo Imai, Johan van Valkenburg, Fernanda Santos, Hidetoshi Nagamasu, Darley C.L. Matos, C. Yves Adou Yao, Renato Valencia, Connie J. Clark, Patricia Alvarez-Loayza, Rahmad Zakaria, Juan Carlos Montero, Robert K. Colwell, Reuben Nilus, Francesco Rovero, John R. Poulsen, Nimal Gunatilleke, David Kenfack, John N. Williams, Rhett D. Harrison, Jean-François Gillet, William F. Laurance, Campbell O. Webb, Natalia Targhetta, Pia Parolin, Susana Ochoa-Gaona, Onrizal, David Harris, Patricia Balvanera, Jan Reitsma, Narayanaswamy Parthasarathy, J. W. Ferry Slik, Mark Schulze, Michael J. Lawes, Ida Theilade, Giriraj Amarnath, Geraldo Antônio Daher Corrêa Franco, Eileen Larney, Olle Forshed, and Hans Verbeeck more...
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Identification ,Databases, Factual ,Biodiversity ,coverage ,forêt tropicale ,Forests ,Fisher's log series ,Spatial richness patterns ,Corrections ,Trees ,Tropical climate ,espèce (taxon) ,Bos- en Natuurbeleid ,biodiversity ,Multidisciplinary ,Ecology ,Inventaire forestier ,Flore ,F70 - Taxonomie végétale et phytogéographie ,Biological Sciences ,PE&RC ,Biosystematiek ,Fisher?s log series ,Phylogeography ,P01 - Conservation de la nature et ressources foncières ,Biodiversité ,Banque de données ,Zone tropicale ,Conservation of Natural Resources ,Rainforest ,Tree inventory ,abundance distributions ,ta1172 ,Pantropical ,Tropical tree species richness ,Biology ,rain-forests ,pantropical ,Statistics, Nonparametric ,Forest and Nature Conservation Policy ,Species Specificity ,global patterns ,Bosecologie en Bosbeheer ,Ecosystem ,Tropical Climate ,Composition botanique ,diversity estimation ,Species diversity ,Généralités ,area ,15. Life on land ,sample ,Forest Ecology and Forest Management ,plant diversity ,ÁRVORES FLORESTAIS (CONSERVAÇÃO) ,Wildlife Ecology and Conservation ,Biosystematics ,Species richness ,U30 - Méthodes de recherche ,richness - Abstract
The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼40,000 and ∼53,000, i.e. at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa., 0, SCOPUS: ar.j, info:eu-repo/semantics/published more...
- Published
- 2015
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32. Dinámica del uso de suelo y vegetación en paisajes altamente modificados por actividades agropecuarias en el sur de México
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Susana Maza-Villalobos, Edith Alvarado Sosa, Ana Deysi Arriaza Rodríguez, Francisco Infante, and Miguel Ángel Castillo-Santiago
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Agrobiodiversidad ,Conservación ,Deforestación ,Botany ,QK1-989 - Abstract
Antecedentes: La identificación de los usos de suelo particulares (e.g., tipo de cultivo) que generan la pérdida de los diferentes tipos de vegetación, las tendencias de degradación y la pérdida de biodiversidad ha sido limitadamente explorada en estudios sobre dinámica del uso de suelo en paisajes agropecuarios. Preguntas: ¿Cuáles son las superficies ocupadas por los diferentes usos de suelo y vegetación? ¿cuál es la permanencia, tasa de cambio y tasa de pérdida de los diferentes usos de suelo y vegetación? ¿qué usos de suelo dirigen los cambios observados? Área de estudio y fechas: Soconusco, Chiapas, México. Período: 2000-2017. Métodos: Se usaron imágenes de Google Earth, el método de fotointerpretación y la verificación en campo para generar mapas de cambio de uso de suelo y vegetación. Se crearon matrices de permanencia/transición y se calcularon tasas de cambio relativo y de pérdida de superficie para los diferentes usos de suelo y vegetación. Resultados: La zona de actividad agropecuaria y la vegetación natural fueron las categorías con mayor superficie y permanencia. La mayor tasa de ganancia anual de superficie se observó en la zona de actividad agropecuaria, influenciada por el incremento de cultivos de importancia económica (mango y palma africana). La mayor tasa de pérdida anual se registró en la vegetación natural, y fue dirigida principalmente por la transición de tular y de vegetación secundaria hacia zonas agropecuarias. Conclusiones: Ante la limitada formación de vegetación secundaria y la alta permanencia/incremento de zonas agropecuarias, es importante considerar acciones que diversifiquen estos paisajes agropecuarios. more...
- Published
- 2023
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33. Carbon Flux and Patterns of Land-Use/ Land-Cover Change in the Selva Lacandona, Mexico
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Ben H. J. De Jong, Susana Ochoa-Gaona, Miguel Angel Castillo-Santiago, Neptalí Ramírez-Marcial, and Michael A. Cairns
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Ecology ,Geography, Planning and Development ,Environmental Chemistry ,General Medicine - Published
- 2000
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34. Agroforestry Systems and Local Institutional Development for Preventing Deforestation in Chiapas, Mexico
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Lorena Soto-Pinto, Guillermo Jiménez-Ferrer, and Miguel Angel Castillo-Santiago
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geography ,geography.geographical_feature_category ,Agroforestry ,Deforestation ,Soil retrogression and degradation ,Forest management ,Logging ,Tropics ,Secondary forest ,Land use, land-use change and forestry ,Forestry ,Old-growth forest - Abstract
The transformation of natural forest to secondary forest and pastures has been the most common process of land use change in tropical countries in recent decades (FAO, 2010). The main causes of deforestation include institutional factors, markets, public policies and global forces, which often act synergistically (Deininger and Minten, 1999; Bocco et al. 2001; Lambin et al., 2001). Mexico is a country with 64,802x103 ha of forested land, and it is one of the ten countries with the largest area of primary forest (3% of total). The annual net loss of deforestation in Mexico has been estimated to be 0.52% for the period of 1990-2010, but the net loss, on average, has decreased over the past few years (FAO, 2010). The highest deforestation rates are concentrated in the south and central regions of the country, as documented elsewhere: 8.4% in el Nevado de Toluca, state of Mexico (1972-2000) (Maass et al., 2006); 8% in Patzcuaro, Michoacan (1960-1990) (Klooster, 2000); 6.9% in some areas of Campeche (ReyesHernandez et al., 2003); 6.1% in the highlands of the state of Chiapas (Cayuela et al., 2006; Echeverria et al., 2007); and 2-6.7% in Selva Lacandona, also in Chiapas (Ortiz-Espejel & Toledo, 1998; de Jong et. al., 2000). Precisely, the states of Chiapas and Yucatan have registered the highest rate of forest conversion to grasslands and slash-and-burn cultivation over the past two decades, and Chiapas alone has contributed towards 12% of national deforestation during the period 1993-2007 (De Jong et al, 2010; Diaz-Gallegos et al., 2010). In Mexico, deforestation occurs because forests become converted to agriculture, livestock and urban areas. But also because logging activities fail to meet the requirements of forest management plans. All these processes result in the loss of forest goods and services (Lambin et al. 2003), and they contribute to ecosystem fragmentation (Ochoa-Gaona & Gonzalez Espinosa, 2000; Cayuela et al., 2006), biological invasions (Hobbs, 2000), greenhouse gas emissions (Watson et al., 2000), biodiversity loss (Lugo et al., 1993), soil degradation (Lal, 2004) and water siltation (Sweeney et al., 2004). more...
- Published
- 2012
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35. Identifying Coffee Agroforestry System Types Using Multitemporal Sentinel-2 Data and Auxiliary Information
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Agustín Escobar-López, Miguel Ángel Castillo-Santiago, José Luis Hernández-Stefanoni, Jean François Mas, and Jorge Omar López-Martínez
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Sierra Madre ,Chiapas ,random forest ,shade coffee ,recursive feature elimination ,Science - Abstract
Coffee is one of the most important agricultural commodities of Mexico. Mapping coffee land cover is still a challenge because it is grown mainly on small areas in agroforestry systems (AFS), which are located in hard-to-access mountainous regions. The objective of this research was to map coffee AFS types in a mountainous region using the changing spectral response patterns over the dry season as well as supplementary data. We employed Sentinel-1, Sentinel-2 and ALOS-Palsar images, a digital elevation model, soil moisture layers, and 150 field plots. First, we defined three coffee AFS types based on their structural and spectral characteristics. Then, we performed a recursive feature elimination analysis to identify the most relevant predictor variables for each land use/cover class in the region. Next, we constructed a predictor variable dataset for each AFS type and one for the remaining land use/cover classes. Afterward, four maps were generated using a random forest (RF) classifier. Finally, we combined the four maps into a unique land-cover map through a maximum likelihood algorithm. Using a validation sample of 932 sites derived from Planet images (4.5 m pixel size), we estimated a 95% map overall accuracy. Two AFS types were classified as having low error; the third, with the highest tree density, had the lowest accuracy. The results obtained show that the infrared and near-infrared bands from the Sentinel-2 scenes are particularly useful for coffee AFS discrimination. However, supplementary data are required to improve the performance of the classifier. Our findings also highlight the importance of the multi-temporal and multi-dataset approach for identifying complex production systems in areas of high topographic heterogeneity. more...
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- 2022
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36. Correction: Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models.
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Raúl Abel Vaca, Duncan John Golicher, Rocío Rodiles-Hernández, Miguel Ángel Castillo-Santiago, Marylin Bejarano, and Darío Alejandro Navarrete-Gutiérrez
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Medicine ,Science - Abstract
[This corrects the article DOI: 10.1371/journal.pone.0222908.].
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- 2020
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37. Drivers of deforestation in the basin of the Usumacinta River: Inference on process from pattern analysis using generalised additive models.
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Raúl Abel Vaca, Duncan John Golicher, Rocío Rodiles-Hernández, Miguel Ángel Castillo-Santiago, Marylin Bejarano, and Darío Alejandro Navarrete-Gutiérrez
- Subjects
Medicine ,Science - Abstract
Quantifying patterns of deforestation and linking these patterns to potentially influencing variables is a key component of modelling and projecting land use change. Statistical methods based on null hypothesis testing are only partially successful for interpreting deforestation in the context of the processes that have led to their formation. Simplifications of cause-consequence relationships that are difficult to support empirically may influence environment and development policies because they suggest simple solutions to complex problems. Deforestation is a complex process driven by multiple proximate and underlying factors and a range of scales. In this study we use a multivariate statistical analysis to provide contextual explanation for deforestation in the Usumacinta River Basin based on partial pattern matching. Our approach avoided testing trivial null hypotheses of lack of association and investigated the strength and form of the response to drivers. As not all factors involved in deforestation are easily mapped as GIS layers, analytical challenges arise due to lack of a one to one correspondence between mappable attributes and drivers. We avoided testing simple statistical hypotheses such as the detectability of a significant linear relationship between deforestation and proximity to roads or water. We developed a series of informative generalised additive models based on combinations of layers that corresponded to hypotheses regarding processes. The importance of the variables representing accessibility was emphasised by the analysis. We provide evidence that land tenure is a critical factor in shaping the decision to deforest and that direct beam insolation has an effect associated with fire frequency and intensity. The effect of winter insolation was found to have many applied implications for land management. The methodology was useful for interpreting the relative importance of sets of variables representing drivers of deforestation. It was an informative approach, thus allowing the construction of a comprehensive understanding of its causes. more...
- Published
- 2019
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38. Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests
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José Luis Hernández-Stefanoni, Gabriela Reyes-Palomeque, Miguel Ángel Castillo-Santiago, Stephanie P. George-Chacón, Astrid Helena Huechacona-Ruiz, Fernando Tun-Dzul, Dinosca Rondon-Rivera, and Juan Manuel Dupuy more...
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airborne laser scanner ,forest biomass ,plot size ,co-registration error ,Monte Carlo simulation ,Science - Abstract
Accurate estimates of above ground biomass (AGB) are needed for monitoring carbon in tropical forests. LiDAR data can provide precise AGB estimations because it can capture the horizontal and vertical structure of vegetation. However, the accuracy of AGB estimations from LiDAR is affected by a co-registration error between LiDAR data and field plots resulting in spatial discrepancies between LiDAR and field plot data. Here, we evaluated the impacts of plot location error and plot size on the accuracy of AGB estimations predicted from LiDAR data in two types of tropical dry forests in Yucatán, México. We sampled woody plants of three size classes in 29 nested plots (80 m2, 400 m2 and 1000 m2) in a semi-deciduous forest (Kiuic) and 28 plots in a semi-evergreen forest (FCP) and estimated AGB using local allometric equations. We calculated several LiDAR metrics from airborne data and used a Monte Carlo simulation approach to assess the influence of plot location errors (2 to 10 m) and plot size on ABG estimations from LiDAR using regression analysis. Our results showed that the precision of AGB estimations improved as plot size increased from 80 m2 to 1000 m2 (R2 = 0.33 to 0.75 and 0.23 to 0.67 for Kiuic and FCP respectively). We also found that increasing GPS location errors resulted in higher AGB estimation errors, especially in the smallest sample plots. In contrast, the largest plots showed consistently lower estimation errors that varied little with plot location error. We conclude that larger plots are less affected by co-registration error and vegetation conditions, highlighting the importance of selecting an appropriate plot size for field forest inventories used for estimating biomass. more...
- Published
- 2018
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39. Determinantes de la distribución de Pinus ssp. en la Altiplanicie Central de Chiapas, México
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María Patrocinio Alba-López, Mario González-Espinosa, Neptalí Ramírez-Marcial, and Miguel Ángel Castillo-Santiago
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coníferas ,pinos ,regresión logística ,sistemas de información geográfica ,variables ambientales ,Botany ,QK1-989 - Abstract
Analizamos las relacionesdela benignidad ambiental, la estacionalidad y la calidad/fertilidad del suelo con la distribución de nueve especies de Pinus de Los Altos de Chiapas, México. Usamos información georreferenciada de 241 ejemplares herborizados colectados en 180 sitios entre 1939 y 1999. Tres componentes principales explicaron 76.5% de la variación en la distribución de las especies. El primer componente se relacionón con las condiciones de humedad, el segundo con la temperatura y el trcerocon la calidad/fertilidad del suelo. Se intentó exolicar la distribución de las especies con una regresión logística. La presencia de P. maximinoi, P. oocarpa, P. pseudostrobus y P. tecumumanii se explicó con la altitud (P more...
- Published
- 2003
- Full Text
- View/download PDF
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