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The Santiago-Guadalajara River Basin (SGRB), located in western Mexico, is one of the most polluted rivers in the country. A pesticide monitoring program was carried out from January 2022 to September 2022, during which time water samples collected at 25 sites in the main stem and tributaries revealed the presence of 13 of the 24 pesticides analyzed, including α-BHC, β-BHC, γ-BHC (Lindane), γ-Chlordane, Hexachlorobenzene, Heptachlor, Aldrin, α-Endosulfan, DDT, -4,4, Methoxychlor, Chlorpyrifos-methyl, Endosulfan sulfate, and Dicofol. A high level of correlation was found between the identified pesticides, which could mean that several of these pesticides reached a stable level within the monitored water bodies. Most of the identified pesticides are classified as high environmental risk according to the Stockholm Convention because of their persistence and high degree of toxicity to the environment and human health. A Pesticide Toxicity Index (PTI) was applied to identify the streams considered to be of concern due to the presence of pesticides exceeding the threshold limits established by national and international guidelines. Performing a calculation for the entire Santiago-Guadalajara River Basin, the PTI reached a value of 0.833, which, according to the criteria of this method, classifies it as a “Moderate” level of risk for aquatic life. Increased regulatory and surveillance measures by state and federal authorities are required to prevent the use of these pesticides, which have been restricted globally.

Global biodiversity is negatively affected by anthropogenic climate change. As species distributions shift due to increasing temperatures and precipitation fluctuations, many species face the risk of extinction. In this study, we explore the expected trend for plant species distributions in Central America and southern Mexico under two alternative Representative Concentration Pathways (RCPs) portraying moderate (RCP4.5) and severe (RCP8.5) increases in greenhouse gas emissions, combined with two species dispersal assumptions (limited and unlimited), for the 2061-2080 climate forecast. Using an ensemble approach employing three techniques to generate species distribution models, we classified 1924 plant species from the region's (sub)tropical forests according to IUCN Red List categories. To infer the spatial and taxonomic distribution of species' vulnerability under each scenario, we calculated the proportion of species in a threat category (Vulnerable, Endangered, Critically Endangered) at a pixel resolution of 30 arc seconds and by family. Our results show a high proportion (58-67%) of threatened species among the four experimental scenarios, with the highest proportion under RCP8.5 and limited dispersal. Threatened species were concentrated in montane areas and avoided lowland areas where conditions are likely to be increasingly inhospitable. Annual precipitation and diurnal temperature range were the main drivers of species' relative vulnerability. Our approach identifies strategic montane areas and taxa of conservation concern that merit urgent inclusion in management plans to improve climatic resilience in the Mesoamerican biodiversity hotspot. Such information is necessary to develop policies that prioritize vulnerable elements and mitigate threats to biodiversity under climate change.

Canopy fuels determine the characteristics of the entire complex of forest fuels due to their constant changes triggered by the environment; therefore, the development of appropriate strategies for fire management and fire risk reduction requires an accurate description of canopy forest fuels. This paper presents a method for mapping the spatial distribution of canopy fuel loads (CFLs) in alignment with their natural variability and three-dimensional spatial distribution. The approach leverages an object-based machine learning framework with UAV multispectral data and photogrammetric point clouds. The proposed method was developed in the mixed forest of the natural protected area of “Sierra de Quila”, Jalisco, Mexico. Structural variables derived from photogrammetric point clouds, along with spectral information, were used in an object-based Random Forest model to accurately estimate CFLs, yielding R2 = 0.75, RMSE = 1.78 Mg, and an average Biasrel = 18.62%. Canopy volume was the most significant explanatory variable, achieving a mean decrease in impurity values greater than 80%, while the combination of texture and vegetation indices presented importance values close to 20%. Our modelling approach enables the accurate estimation of CFLs, accounting for the ecological context that governs their dynamics and spatial variability. The high precision achieved, at a relatively low cost, encourages constant updating of forest fuels maps to enable researchers and forest managers to streamline decision making on fuel and forest fire management.

La planta del agave tiene un significativo valor económico y cultural, puesno solo se considera un producto agrícola y forestal, sino que además se emplea en la elaboración de una cantidad importante de productos. En México, uno de los derivados más representativos del agave son las bebidas destiladas de mezcal y tequila, cuya venta se ha incrementado fuera del país. En respuesta a esta demanda, Guerrero ha reportado un crecimiento anual de la producción de mezcal del 1,5 %, con un aumento en la superficie de más de 1.000 hectáreas entre 2015 y 2020. Este auge comercial ha generado una expansión e intensificación de la siembra y producción de la Agave spp. (Asparagaceae), así como el uso de técnicas agrícolas de producción inadecuadas y cambios en la tecnología tradicional. Es por ello que el objetivo de este trabajo fue localizar espacialmente el agave mezcal, en particular las especies Agave cupreataTrel. & Berger y Agave angustifoliaHaw., con tecnologías geomáticas para identificar los ambientes diversificados del agave (silvestre o cultivado) que fortalezcan los procesos agroproductivos y potencien los subproductos del cultivo. El estudio encontró que la superficie potencial del cultivo de agave es superior a lo reportado por fuentes oficiales en más de 25.000 hectáreas y que los cálculos realizados con tecnologías geomáticas tienen una precisión del 91% para identificar áreas adecuadas para el aprovechamiento y la conservación de estas dos especies de importancia económica.

Abstract Quercus‐dominated forests in the Neotropics compose one of the broadest distributed ecosystems of mountainous zones whose species distribution has been explained by climate change adaptation over an abrupt physiography. This study aims to comprehend the contribution of environmental and spatial processes influential in species composition of Quercus‐dominated forests. A database of 86 plots, randomly located in a highly diverse spot of the Mexican Neotropics, was examined; it involved vegetation, environment, and spatial data. Local spatial variables were derived from distance‐based Moran's eigenvector maps, while regional spatial variables were obtained from geographical coordinates (latitude/longitude). Redundancy analysis and variance partitioning were run to reveal the relative importance of environmental and spatial processes explaining plant species composition of Quercus‐dominated forests and ascertain the environmental variables controlling the species composition at the different spatial scales (local and regional). Results showed that both local and regional spatial variables significantly control species composition in Quercus‐dominated forests, with the regional scale accounting for a higher explained variance than the local scale. At the regional scale, elevation, aspect, litter, maturity, and Mg were significant in explaining species community composition; elevation variance was twofold higher than variance for aspect and litter. At the local scale, elevation accounted for the highest variation followed by maturity, P, N, and Mg. The analysis also tested the variation of species community composition over environmental gradients mainly determined by elevation. This study indicated the importance of elevation at both local and regional spatial scales as an important driver in Quercus‐dominated forests distribution, probably related to Quercus species adaptation to temperature and precipitation. Finally, evidence from this research emphasizes the significance and necessity of a multiscale analysis to discern the spatial structured environment responsible for the high species diversity and broad distribution of forests dominated by Quercus genus in the Neotropics.

This study aimed at the qualitative and quantitative analyses of the botanical contents of the textbooks of Natural Sciences of the rural schools at the primary level, whose purpose was to identify possibilities of contextualization in intercultural dialogue in science education. We found 88 references with a botanical theoretical approach and 82 proposed related to eight botanical themes: nutritional value, taxonomy, morphology, physiology, ecology, ethnobotany, evolution and anatomy; in addition to 133 visual resources related to the regional or national context were found. Although some contents, proposed activities and visual resources make direct references to the student´s cultural knowledge, and may contribute to the sociocultural contextualization of knowledge during intercultural dialogue, it is necessary that contents contemplate the relationships with the history and philosophy of this science to that the students understand the epistemologies involved, the nature of science, as well as the context of applicability.

El objetivo de este trabajo fue evaluar la carga microbiológica de coliformes totales (CT), Staphylococcus aureus y Salmonella spp en leche y quesos frescos como indicadores de prácticas de proceso que se realizan en queserías de diferentes localidades de la región de Salinas, San Luis Potosí. Se muestrearon 15 establecimientos, se obtuvieron muestras de leche y queso y se les realizó un análisis de composición de la leche y microbiológico. El 65 % de las unidades de producción no pasteuriza la leche o utiliza cuajo natural. Los conteos más elevados en leche fueron de 42 x 109 y 40 x 109 UFC/ml para S. aureus y CT, respectivamente. Para queso, las cuentas de 32 x 109 y 26 x 109 UFC/g para S. aureus y CT, respectivamente. Además, se detectó presencia de Salmonella en leche y queso. Se concluye que la falta de higiene en los utensilios y equipos en los que se elaboran los quesos, así como el uso de cuajo natural, pueden ser un riesgo para la salud del consumidor.

Desmodus rotundus es transmisor de enfermedades zoonóticas y emergentes a los humanos y al ganado, como el caso de la rabia. La mayoría de las enfermedades infecciosas están limitadas espacialmente por la presencia del transmisor, cuya abundancia y supervivencia son influenciadas por las condiciones ambientales y la presencia de fuentes de alimentación. Una herramienta que facilita su estudio es el uso de los Sistemas de Información Geográfica. El objetivo de este estudio fue analizar la interacción de las poblaciones de murciélagos hematófagos y humanos, a través de la elaboración de un modelo probable de dispersión del D. rotundus basado en refugios conocidos y diferentes variables medioambientales, además de analizar la relación entre refugios identificados durante tres años y su cercanía con asentamientos humanos, como un proceso de coexistencia. El estudio se llevó a cabo en el estado de San Luis Potosí del año 2014 al 2016. Se identificaron un total de 180 refugios de D. rotundus distribuidos hacia la zona de la Huasteca, el 80 % de éstos fueron construidos por el hombre y el 57 % se encontraron habitados. Se calculó un buffer de 5 km a la redonda a partir de la ubicación de cada refugio, encontrando en su interior un total de 976 comunidades rurales y 15 ciudades, con 337,836 habitantes. La distancia media de los refugios hasta el primer asentamiento humano fue de 518.65 ± 11.33 m. Es necesario continuar estudiando la asociación entre la urbanización y el surgimiento de zoonosis, a través del entendimiento de las interacciones entre animales silvestres-ganadería - humanos.

The “Ecological Value” (EV) term has been spread in the literature since 1860; however, there is no consensus on its definition and the criteria for its assessment. To identify, assess and summarize the main definitions, criteria, indicators and applications behind the EV term, we performed a systematic literature review of 209 articles published over the last 10 years. Methods included documentation of the following data: i) study area, ii) study subject, iii) study object; iv) criteria, indicators and methods used in the analyses, v) applications of the EV term, and vi) if the study was performed in a natural protected area. Multiple Correspondence Analysis (MCA) was conducted to uncover the association among studies regarding the use of EV and to test for homogeneity among the articles publishing research involving EV. A bootstrap technique was used for MCA validation. The main findings exposed the polysemy of the term and the paucity in the definition, mainly derived by the lack of a theoretical framework. Only 74, out of the 209 revised articles, involved numerical analysis to evaluate criteria. The more recurrent criteria were those related with ecological properties (biodiversity, vulnerability) and with functional characteristics (fragmentation, connectivity and resilience). Remote sensing techniques were the more frequent method for the assessment of EV. The main applications in the use of this term were for natural and urban planning, biodiversity conservation and payment for ecosystem services. An explicit heterogeneity among articles, with and without numerical analysis, was denoted by MCA. Finally, we concluded that the EV term is highly related with the intrinsic values of the landscape.

Accurate description of forest fuels is necessary for developing appropriate fire management strategies aimed at reducing fire risk. Although field surveys provide accurate measurements of forest fuel load estimations, they are time consuming, expensive, and may fail to capture the inherent spatial heterogeneity of forest fuels. Previous efforts were carried out to solve this issue by estimating homogeneous response areas (HRAs), representing a promising alternative. However, previous methods suffer from a high degree of subjectivity and are difficult to validate. This paper presents a method, which allows eliminating subjectivity in estimating HRAs spatial distribution, using artificial intelligence machine learning techniques. The proposed method was developed in the natural protected area of “Sierra de Quila,” Jalisco, and was replicated in “Sierra de Álvarez,” San Luis Potosí and “Selva El Ocote,” Chiapas, Mexico, to prove its robustness. Input data encompassed a set of environmental variables including altitude, average annual precipitation, enhanced vegetation index, and forest canopy height. Four, three, and five HRAs with overall accuracy of 97.78%, 98.06%, and 98.92% were identified at “Sierra de Quila,” “Sierra de Álvarez,” and “Selva El Ocote,” respectively. Altitude and average annual precipitation were identified as the most explanatory variables in all locations, achieving a mean decrease in impurity values greater than 52.51% for altitude and up to 36.02% for average annual precipitation. HRAs showed statistically significant differences in all study sites according to the Kruskal–Wallis test (p-value < 0.05). Differences among groups were also significant based on the Wilcoxon–Mann–Whitney (p-value < 0.05) for all variables but EVI in “Selva El Ocote.” These results show the potential of our approach to objectively identify distinct homogeneous areas in terms of their fuel properties. This allows the adequate management of fire and forest fuels in decision-making processes.

Background. Huanglongbing is a lethal disease for citrus, affecting all citrus species, causing young plants that become infected fail to produce and adult plants become unproductive for a period of two to five years. Objective. The objective of this study was to determine the potential areas for the establishment of huanglongbing in Tabasco. Methodology. In order to achieve this objective, the model of maximum entropy (MaxEnt) was used, which is a general purpose machine learning method. For its validation, the Receiver Operating Characteristic (ROC) technique applied in presence-only distribution models was applied. To generate the model, 19 climatic variables taken from Worldclim were used, a soil variable taken from Jiménez et al., (2013) and 195 records of the presence of Candidatus Liberibacter asiaticus detected in plant material were used. Results. The results show that the municipalities of Huimanguillo and Balancán are the areas with the greatest potential distribution of the disease with values greater than 0.7. According to the area under the curve (AUC), the model has a high ability to predict correctly by presenting values of 0.936 in the training data. Implications. The present study could contribute to the planning of surveillance areas for the detection and control of huanglongbing disease. Conclusion. The model obtained is a good approximation of the potential presence of the disease in the state of Tabasco, giving clarity when choosing the surveillance areas for the pathogen and its vector.

Huanglongbing (HLB) es una de las enfermedades más destructivas que afecta a los cítricos en el mundo. En el continente americano, HLB se detectó primero en Brasil y posteriormente en Florida (Estados Unidos). Las áreas citrícolas de Colombia se mantuvieron libres de la enfermedad hasta que en abril de 2016 el Instituto Colombiano Agropecuario (ICA) declaró en cuarentena fitosanitaria al departamento de La Guajira por la presencia de HLB. En ese momento se intensificaron las acciones de control y erradicación; sin embargo, el informe del primer semestre de 2018 elaborado por el ICA reportó la presencia de HLB en seis departamentos del norte de Colombia. El presente estudio propone una metodología para analizar el riesgo potencial de HLB y su insecto vector Diaphorina citri mediante el uso de tecnología geoespacial, que permite determinar la ubicación de plantas hospederas, grados días de desarrollo del vector y variables bioclimáticas. Los resultados señalan que cerca del 15 % de las áreas citrícolas de Colombia se encuentra en un alto riesgo a la presencia de la enfermedad. Esta metodología se presenta como una opción para el monitoreo de la enfermedad a escala regional, ya que es automatizable y tiene una dinámica espacio-temporal alta que puede ser utilizada para la detección temprana de HLB.

AbstractMangroves are a highly threatened ecosystem due to climate change and human activity, which increases coastal vulnerability. Knowledge about the ecological dynamics of mangroves on a centennial timescale can reveal the different responses in vegetation, which is useful for implementing basic actions for mangrove restoration, conservation and management. A mangrove ecosystem in the Cuyutlán Lagoon area along the Pacific coast of west-central Mexico is significantly altered as a result of industrialization, salt extraction, and road construction. The long-term dynamics of the mangrove ecosystem has also been controlled by Holocene climatic variability. This study reconstructs the environmental history of mangrove vegetation around the Cuyutlán Lagoon during the last ~1300 years in response to periods of human activity and climate change. The reconstruction was performed using paleoecological techniques in sediment cores that include the use of fossil pollen as a proxy for vegetation and magnetic susceptibility and geochemical data (determined by loss-on-ignition and X-ray fluorescence) as a proxy for past environmental changes. The chronology was determined using 14C dating and the age-depth model was constructed by linear interpolation. Redundancy analysis and non-metric multidimensional scaling (NMDS) were used to discern patterns of distribution of the different proxies. Results revealed that the mangrove pollen assemblage of the Cuyutlán Lagoon was dominated by the arboreal taxa Rhizophora mangle, Euphorbiaceae, Moraceae and Pinaceae, herbaceous taxa like Poaceae, Chenopodiaceae/Amaranthaceae, and aquatics such as Typhaceae and Cyperaceae. NMDS showed a clear separation between two events of human activity—the Spanish Occupation of Colima (~AD 1523-1524) and the opening of the Manzanillo port (~AD 1824-1825). Climate change events such as the Medieval Climate Anomaly (MCA) (~AD 800-1200) and the Little Ice Age (LIA) (~AD 1350-1850) were also successfully identified. The main responses were mangrove expansion (driven by R. mangle) during the LIA and the Manzanillo Port Opening, while the MCA was a highly perturbed period marked by multiple hurricane events and low or no pollen deposition in the sediment. During the Spanish Occupation, the aquatic taxa Typhaceae expanded together with an increase in Ca, Sr and carbonate contents.

Los esfuerzos de conservación en la región neotropical están limitados por la falta de información disponible sobre las especies, ya que muchas no han sido descritas o se tiene poca información sobre ellas. La Red Internacional de Inventarios Forestales (BIOTREE-NET) concentra y facilita el acceso a la información y el intercambio entre investigadores, gestores y conservacionistas, organizando y estandarizando los datos de especies de árboles procedentes de inventarios forestales en la región mesoamericana en una única base de datos que incluya información espacial. Este artículo explica el ámbito y objetivos de la red, describe la estructura de la base de datos e identifica los principales avances realizados, así como los retos y perspectivas futuras. La base de datos contiene más de 50 000 registros de árboles de unas 5000 especies, distribuidas en más de 2000 parcelas muestreadas desde el suroeste de México hasta Panamá. La información es heterogénea, tanto en su naturaleza y forma como en la cobertura geográfica de los inventarios. La base de datos tiene una estructura relacional, con 12 tablas interconectadas, incluyendo información sobre las parcelas, los nombres de las especies, el diámetro a la altura del pecho de los árboles medidos y sus atributos funcionales. Se ha desarrollado un sistema para la corrección de errores tipográficos y la estandarización taxonómica y nomenclatural utilizando como referencia The Plant List (http://theplantlist.org/). También se han generado modelos de distribución potencial para cerca de 1700 especies utilizando distintos métodos y en el futuro se prevé habilitar también el acceso público a los modelos de distribución de especies a través del portal web (http://portal.biotreenet.com). Aunque BIOTREE-NET ha contribuido al desarrollo de mejores modelos de distribución, su mayor potencial radica, en nuestra opinión, en el estudio a nivel de comunidades. Finalmente, se reconoce la necesidad de expandir la red a través de la participación de más investigadores interesados en colaborar con datos para ampliar el conocimiento sobre la biodiversidad forestal en la región neotropical.

Se estudiaron tres asociaciones florísticas dominadas por encinos (Quercus spp) en bosques montanos del centro-occidente de México con el fin de conocer si existe diferenciación estructural de sus poblaciones en función de las características del sitio donde se localizan. Se establecieron 84 parcelas circulares a lo largo de un gradiente ambiental de 10 km. Las variables consideradas para caracterizar la estructura de las poblaciones fueron la densidad, el área basal, la distribución diamétrica y un índice de rendimiento (IR) estimado mediante la sumatoria de los valores de densidad relativa y volumen relativo de cada una de las especies presentes en cada asociación florística. Para cada especie se estimó el coeficiente de Gini con el fin de determinar si se presenta una desigualdad en la distribución diamétrica de las poblaciones en función de la asociación florística donde se localiza; además se aplicó una prueba no-paramétrica para evaluar la diferencia en tamaños diamétricos de las seis especies que presentaron las abundancias más sobresalientes entre asociaciones y un modelo lineal general para determinar si la especie y la asociación donde ésta se encuentra, tiene un impacto en el tamaño diamétrico. Los resultados indicaron que existe diferenciación estructural entre especies de acuerdo a la asociación florística; la asociación donde se encontró el mayor número de especies de encino coexistiendo en el dosel (ocho especies), presentó valores intermedios de IR y la mayor desigualdad (G) en tamaños diamétricos. Con respecto a la variación de los tamaños diamétricos, solo tres especies mostraron diferencias significativas entre asociaciones. A partir de los resultados obtenidos se hipotetiza que la estructura diferencial de las especies por asociación, y en particular el tamaño diamétrico de las especies de encino, puede ser una respuesta estratégica de las especies para compartir, proporcionalmente al tamaño, los recursos del sitio y coexistir en el dosel.

Abstract The sucrose contained in sugarcane is the main input for sugar production in Mexico. It is thus necessary to examine the ability of Mexican sugarcane farms to provide raw material in order to achieve a better sustainability and competiveness of sugar industry. Therefore, area expansion for sugar, bioenergy and biofuels will depend on weather and soil conditions, production cost changes, land tenure and plot size and the level of continued investment by stakeholders for innovations. Sugarcane cultivation is mainly located in the rainfed cultivation system; accordingly, crop fields have heterogeneous productivity, with a decrease of 11% in the last decade, and high vulnerability to weather effects. Therefore, requires a multidisciplinary approach, as Precision Agriculture (PA), Remotely Sensed yield estimation and Agro Ecological Zoning (AEZ), focused at regional and local scale, considering the biophysical constraints to improve the sustainable sugarcane production. The main findings of this study, with the application of AEZ and PA tools, showed that Mexican sugarcane crop fields have a differentiated land suitability into four levels: 20.07% of the total planted area is classified as high aptitude, 56.34% as medium, and 23.59% as low with high vulnerability to climate variability; We also determined that total potential sugarcane yield is 78.11 t ha−1, but actual yield is 68.60 t ha−1 (12% lower) because in 777,078 ha for the 2016/2017 harvest season; 13 sugar mills (25.5%) produced cane yield below 60 t ha−1, 21 between 60 and 80 t ha−1 (41.2%) and 17 above 80 t ha−1 (33.3%). Therefore, the unsuitable areas must be converted to agroecological management practices in combination with conventional approaches to increase yields. The Mexican sugar industry requires public policies differentiated by agro-ecological zone for yield and productivity optimization. [ABSTRACT FROM AUTHOR]

The present study demonstrates, for the first time, the feasibility of a two-step process consisting of Electro-Fenton (EF) followed by microalgae to treat highly loaded real food processing wastewater along with resource recovery. In the first step, EF with a carbon felt cathode and Ti/RuO 2 -IrO 2 anode was applied at different current densities (3.16 mA cm -2 , 4.74 mA cm -2 and 6.32 mA cm -2 ) to decrease the amount of organic matter and turbidity and enhance biodegradability. In the second step, the EF effluents were submitted to microalgal treatment for 15 days using a mixed culture dominated by Scenedesmus sp., Chlorosarcinopsis sp., and Coelastrum sp. Results showed that current density impacted the amount of COD removed by EF, achieving the highest COD removal of 77.5% at 6.32 mA cm -2 with >95% and 74.3% of TSS and PO 4 3- . Remarkably, not only 85% of the remaining organic matter was removed by microalgae, but also the totality of inorganic N and P compounds, as well as 65% of the Fe catalyst that was left after EF. The removal of inorganic species also demonstrates the high complementarity of both processes, since EF does not have the capacity to remove such compounds, while microalgae do not grow in the raw wastewater. Furthermore, a maximum of 0.8 g L -2 . Remarkably, not only 85% of the remaining organic matter was removed by microalgae, but also the totality of inorganic N and P compounds, as well as 65% of the Fe catalyst that was left after EF. The removal of inorganic species also demonstrates the high complementarity of both processes, since EF does not have the capacity to remove such compounds, while microalgae do not grow in the raw wastewater. Furthermore, a maximum of 0.8 g L -1 of biomass was produced after cultivation, with an accumulation of 32.2% of carbohydrates and 25.9% of lipids. The implementation of the two processes represents a promising sustainable approach for the management of industrial effluents, incorporating EF in a water and nutrient recycling system to produce biomass that could be valorized into clean fuels., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:, (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)