This study aims to provide a technique applied to archaeology to estimate lidar-based aboveground biomass (AGB) in contemporary tropical forests surrounding archaeological sites. Accurate AGB estimations are important to serve as a baseline to evaluate the wood resources that the ancient Maya could have used for the development of their cities. A lidar processing model is proposed to study the contemporary forest surrounding the Yaxnohcah archaeological site. As tropical forests are highly diverse environments where species are not uniformly distributed, it was necessary to consider the variation within the forest to obtain accurate AGB. Four vegetation communities were defined from a supervised classification of a Sentinel-2 satellite image. A stratified sample was then selected for the field survey that comprised 73 transects of 500 m² each. To estimate the transect AGB, we used an allometric equation that requires diameter, height, and wood density measurements for identified species. Linear-derived models provided the relationship between field data with lidar statistics for each vegetation type. Predicted average AGB values agreed with those obtained in the field. However, they significantly differed between vegetation types, averaging 83 Mg/ha for lowland forest, 178 for transition forest, and 215 for upland forest communities. From those results, we created a map with wall-to-wall AGB estimates following the distribution of vegetation classes that could complement archaeological research of past land use. Vegetation classification also helped determine that there is a spatial relationship between vegetation communities and the distribution of archaeological settlement features for the ancient city of Yaxnohcah.

Diaphorina citri Kuwayama (Asian citrus psyllid) is a quarantine pest found in at least 60 countries, causing indirect damage as a primary vector of pathogens associated with Huanglongbing in citrus trees. Huanglongbing-infected trees die within 3–8 years, accompanied by economic losses in citriculture. D. citri has spread in Mexico to several states and is a high risk to Mexican citriculture due to its ability to cause damage and the lack of a disease cure. The primary objective of this research was to enhance our understanding of the current status of D. citri in southeastern Mexico. This study analyzed the distribution of D. citri in Campeche, Mexico from 2013 to 2020. The study generated 572,619 D. citri records from 40,620 yellow sticky traps deployed in 10 of the 12 municipalities of the state. We employed advanced MaxEnt and DivaGIS software to accomplish this study. Results showed population fluctuations with a peak during June and July from 2013 to 2019 and July and September in 2020. The study found a higher presence of D. citri in Campeche, Tenabo, Carmen, Champotón, and Escárcega and a higher incidence in Citrus latifolia Tanaka ex Q. Jiménez and Citrus sinensis (L.) Osbeck crops. The variance in the number of D. citri adults captured per year and the dispersion index (a parameter measuring the ability of insects to leave one ecosystem and move to another in search of suitable conditions for their survival and reproduction) was greater than the annual mean, demonstrating a spatially distributed, right-skewed aggregate. The elliptical polygon or standard deviation ellipse indicated the tendency for a less elongated ellipse in 2013–2014. From 2015 to 2018 D. citri expanded north towards Hecelchakán and south towards Champotón, Escárcega, and Carmen. In 2019, D. citri expanded north towards Champotón, Campeche, Tenabo, Hecelchakán, and Calkiní. The months with the most activity between 2013 and 2020 were May, June, July, and August, with June having the highest numbers collected. The results of the enveloped tests (parameter measuring how environmental conditions influence the spatial patterns of insect populations) showed the adaptability of D. citri to different conditions. D. citri prefers temperatures of 24.6–27.9 °C and 1,050–1,500 mm of rainfall. Areas with high-risk for D. citri are coastal and northern parts of the study area. Central Campeche is suitable, and southern parts have low to medium risk. Our research shows the relationship between climatic factors and the distribution of D. citri in the state of Campeche, Mexico. Moreover, our findings will be crucial for implementing effective surveillance measures in areas where the probability model indicates the potential presence of D. citri. This is especially significant due to the remarkable adaptability of D. citri to diverse environmental conditions.

La investigación llevó por propósito estructurar un modelo para orientar a la planificación territorial, con base en la sostenibilidad, el quehacer en los espacios mineros, la gestión del riesgo de desastres en unión directa con la adaptación al cambio climático y la generación de resiliencia socio-ambiental en América Latina y el Caribe. Este fin se cimienta en los mandatos de todos los Objetivos para el Desarrollo Sostenible (ODS), Agenda 2030 (Naciones Unidas, 2019), las premisas de la Oficina de las Naciones Unidas para la Reducción del Riesgo de Desastres (UNISDR, 2017), las guías del Grupo Intergubernamental de Expertos sobre el Cambio Climático (IPCC, 2018) y, las recomendaciones del Consejo Internacional de Minería y Metales (ICMM, 2019). La propuesta presenta un diseño de campo no-experimental de corte transversal ajustado a un estudio de tipo proyectivo. Se aplicó un muestreo aleatorio simple con resultado de 67 ONG (N = 80). El diagnóstico fue derivado a través de una escala con consistencia interna (α = 0,95; p < 0,05). El Modelo Orientativo de la Planificación Territorial Sostenible de la Minería fue ensamblado siguiendo las asociaciones significativas entre sus componentes, los impactos socio-ambientales de la minería (W = 0,936; γ = -0,867; p < 0,01), y con respecto a la gestión de riesgo de desastres (d = 0,947; γ = 1,000; p < 0,01). El estudio concluyó que el Modelo mitiga directamente las causas que gestan a los impactos socio-ambientales negativos y fomenta, mediante sus ejes transversales, la reducción de riesgos en los espacios mineros.

El presente trabajo presenta los elementos fundamentales del análisis espacial y su aplicación estratégica para la promoción y gestión de la co-investigación en espacios colaborativos. Los análisis multicriterio son considerados como una guía metodológica poderosa que combinados con los Sistemas de Información Geográfica; constituyen el análisis espacial que posibilita la integración, análisis, síntesis y difusión de conocimiento. Además, sirve de apoyo en los procesos de gestión de proyectos de investigación y docencia de manera integral, en el marco de las Instituciones de Educación Superior. Retoma parte de los resultados de una investigación que recogió las opiniones de profesores, estudiantes y directivos, las cuales se analizaron con base en los planteamientos teórico-metodológicos de los estudios organizacionales . Se identificaron los roles y se diagnosticó el sistema de comunicación interna; además se analizaron las memorias derivadas del Seminario, Laboratorios Urbanos Ante la Pandemia para identificar los principales retos. Ambos insumos justifican y sustentan el diseño de la estrategia. Se presenta el esquema procedimental del método de Análisis Jerárquico, adecuado a la realidad del Laboratorio de la Forma Urbana de la Universidad Autónoma Metropolitana Azcapotzalco. La propuesta establece un parámetro estandarizado que opera con base en el análisis de la información geográfica y los principios de la co-investigación. Con esta estrategia, las personas y equipos que encabezan proyectos de investigación y/o académicos, tendrán la posibilidad de gestionar los procesos y productos derivados del trabajo colaborativo para alcanzar la excelencia en los centros educativos.Palabras clave: Análisis espacial, Análisis Jerárquico, co-investigación, espacio y trabajo colaborativo.

This study explores the detection and classification of aguadas (ponds) in the Bajo El Laberinto region, in the Calakmul Biosphere Reserve, Campeche, Mexico, using remote sensing techniques. Lidar-derived digital elevation models (DEMs), orthophotos and satellite imagery from multiple sources were employed to identify and characterize these water reservoirs, which played a crucial role in ancient Maya water management and continued to be vital for contemporary wildlife. By comparing different visualization techniques and imagery sources, the study demonstrates that while lidar data provides superior topographic detail, satellite imagery—particularly with nominal 3 m, or finer, spatial resolution with a near-infrared band—offers valuable complementary data including present-day hydrological and vegetative characteristics. In this study, 350 aguadas were identified in the broader region. The shapes, canopy cover, and topographic positions of these aguadas were documented, and the anthropogenic origin of most features was emphasized. The paper’s conclusion states that combining various remote sensing datasets enhances the identification and understanding of aguadas, providing insights into ancient Mayan adaptive strategies and contributing to ongoing archaeological and ecological research.