Indigenous denominations of the marijuana in Mexico. Documentary research of the relationship between the pipiltzintzintli and the cannabis plant (XVI-XIX centuries)

Objetivo. Analizar las posibles denominaciones indígenas del cannabis durante el período novohispano, así como las probables continuidades de esta concepción durante el siglo XIX. Metodología. Se revisaron fuentes documentales y etnográficas que sugieren que la denominación indígena del cannabis se relacionó con el término pipiltzintzintli, cuya concepción transitó ―de manera subrepticia― de un cultivo industrial traído a América por los españoles hacia una droga psicoactiva. Resultados y conclusiones. El análisis de estas evidencias nos muestra que la relación existente entre estas denominaciones presenta algunas inconsistencias. Desde la perspectiva historiográfica se trata de un tema confuso, poco explorado y distante aún de conclusiones definitivas.Objective. To analyze the possible indigenous denominations of cannabis during the Novo Hispanic period, as well as the probable continuities of this designation during the 19th century. Methodology. Documentary and ethnographic sources were reviewed that suggest that the indigenous denomination of cannabis was related to the term pipiltzintzintli, whose conception passed ―surreptitiously― from an industrial crop brought to the Americas by the Spaniards to a psychoactive drug. Results and conclusions. The analysis of this evidence shows that the relationship between those denominations shows some inconsistencies. From a historiographical perspective, this is a confusing and little explored subject, still far from allowing for definitive conclusions

Using satellite estimates of aboveground biomass to assess carbon stocks in a mixed-management, semi-deciduous tropical forest in the Yucatan Peninsula

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

Identification of areas with high aboveground biomass and high species richness of the native forest at northeastern Uruguay

[EN] The native forests of Uruguay provide important ecosystem services. Despite this, there are few maps with the spatial distribution of vegetation attributes in the country. The objective of this study was to obtain maps with the spatial distribution of aboveground biomass and species richness that show areas with high concentrations of both variables, essential for climate change mitigation and biodiversity conservation. The study area includes the Gondwanan Sedimentary Basin ecoregion. Generalized Linear Models were used to estimate aboveground biomass and tree species richness, where the response variables were calculated using field data from the National Forest Inventory. Whereas, the predictor variables were obtained with spectral and texture information derived from Sentinel-2, and ALOS PALSAR; as well as environmental, topography and climate data. The biomass estimation model presented an explained deviance (D2) of 0,25, while in the species richness model, the D2 was 0,19. To evaluate both models, cross-validations were carried out, obtaining an R2 of 0.25 for aboveground biomass and 0,19 for species richness, with a relative mean square error of 45,8 % and 32,5 % respectively. The bivariate map with the joint distribution of species richness and aboveground biomass shows that there is a positive correlation between both variables in 63,8 % of the native forest area of the ecoregion. The results of this work could be used for the maintenance of carbon stocks and for the conservation of biodiversity.[ES] Los bosques nativos de Uruguay brindan importantes servicios ecosistémicos. A pesar de esto, son escasos los mapas con la distribución espacial de atributos de la vegetación en el país. El objetivo de este estudio fue obtener mapas con la distribución espacial de la biomasa aérea y la riqueza de especies que muestren zonas con altas concentraciones de ambas variables, fundamentales para la mitigación del cambio climático y la conservación la biodiversidad. El área de estudio comprende la ecorregión Cuenca Sedimentaria Gondwánica. Para la estimación de la biomasa aérea y la riqueza de especies se utilizaron Modelos Lineales Generalizados, donde las variables de respuesta fueron calculadas utilizando datos de campo del Inventario Forestal Nacional. Las variables explicativas en el modelo se obtuvieron con información espectral, de retrodispersión y de textura derivada de Sentinel-2, y ALOS PALSAR; así como de datos ambientales, de topografía y clima. El modelo para la estimación de biomasa presentó una devianza explicada (D2) de 0,25, mientras que el de riqueza de especies la D2 fue 0,19. Para evaluar ambos modelos se realizaron validaciones cruzadas, obteniendo un R2 de 0,25 para biomasa y de 0,20 para riqueza de especies, con un error cuadrático medio relativo de 45,8 % y de 32,5 %, respectivamente. El mapa bivariado con la distribución conjunta de la riqueza de especies y la biomasa aérea muestra que existe una correlación positiva entre ambas variables en el 63,8 % de la superficie de bosque nativo de la ecorregión. Los resultados de este trabajo podrían ser utilizados tanto para el mantenimiento de los almacenes de carbono, como para la conservación de la biodiversidad.Ocaño-Silveira, CE.; Valdez-Lazalde, JR.; Duno-De Stefano, R.; Hernández-Stefanoni, JL. (2024). Identificación de áreas con alta biomasa aérea y alta riqueza de especies en bosques nativos del nordeste de Uruguay. Revista de Teledetección. (63):37-52. https://doi.org/10.4995/raet.2024.2027237526

Isolating the effects of land use and functional variation on Yucatán's forest biomass under global change

Tropical forests hold large stocks of carbon in biomass and face pressures from changing climate and anthropogenic disturbance. Forests' capacity to store biomass under future conditions and accumulate biomass during regrowth after clearance are major knowledge gaps. Here we use chronosequence data, satellite observations and a C-cycle model to diagnose woody C dynamics in two dry forest ecotypes (semi-deciduous and semi-evergreen) in Yucatán, Mexico. Woody biomass differences between mature semi-deciduous (90 MgC ha−1) and semi-evergreen (175 MgC ha−1) forest landscapes are mostly explained by differences in climate (c. 60%), particularly temperature, humidity and soil moisture effects on production. Functional variation in foliar phenology, woody allocation, and wood turnover rate explained c. 40% of biomass differences between ecotypes. Modeling experiments explored varied forest clearance and regrowth cycles, under a range of climate and CO2 change scenarios to 2100. Production and steady state biomass in both ecotypes were reduced by forecast warming and drying (mean biomass 2021–2100 reduced 16–19% compared to 2001–2020), but compensated by fertilisation from rising CO2. Functional analysis indicates that trait adjustments amplify biomass losses by 70%. Experiments with disturbance and recovery across historically reported levels indicate reductions to mean forest biomass stocks over 2021–2100 similar in magnitude to climate impacts (10–19% reductions for disturbance with recovery). Forest disturbance without regrowth amplifies biomass loss by three- or four-fold. We conclude that vegetation functional differences across the Yucatán climate gradient have developed to limit climate risks. Climate change will therefore lead to functional adjustments for all forest types. These adjustments are likely to magnify biomass reductions caused directly by climate change over the coming century. However, the range of impacts of land use and land use change are as, or more, substantive than the totality of direct and indirect climate impacts. Thus the carbon storage of Yucatan's forests is highly vulnerable both to climate and land use and land use change. Our results here should be used to test and enhance land surface models use for dry forest carbon cycle assessment regionally and globally. A single plant functional type approach for modeling Yucatán's forests is not justified

Environmental gradients and the evolution of successional habitat specialization: A test case with 14 Neotropical forest sites

© 2015 British Ecological Society. Successional gradients are ubiquitous in nature, yet few studies have systematically examined the evolutionary origins of taxa that specialize at different successional stages. Here we quantify successional habitat specialization in Neotropical forest trees and evaluate its evolutionary lability along a precipitation gradient. Theoretically, successional habitat specialization should be more evolutionarily conserved in wet forests than in dry forests due to more extreme microenvironmental differentiation between early and late-successional stages in wet forest. We applied a robust multinomial classification model to samples of primary and secondary forest trees from 14 Neotropical lowland forest sites spanning a precipitation gradient from 788 to 4000 mm annual rainfall, identifying species that are old-growth specialists and secondary forest specialists in each site. We constructed phylogenies for the classified taxa at each site and for the entire set of classified taxa and tested whether successional habitat specialization is phylogenetically conserved. We further investigated differences in the functional traits of species specializing in secondary vs. old-growth forest along the precipitation gradient, expecting different trait associations with secondary forest specialists in wet vs. dry forests since water availability is more limiting in dry forests and light availability more limiting in wet forests. Successional habitat specialization is non-randomly distributed in the angiosperm phylogeny, with a tendency towards phylogenetic conservatism overall and a trend towards stronger conservatism in wet forests than in dry forests. However, the specialists come from all the major branches of the angiosperm phylogeny, and very few functional traits showed any consistent relationships with successional habitat specialization in either wet or dry forests. Synthesis. The niche conservatism evident in the habitat specialization of Neotropical trees suggests a role for radiation into different successional habitats in the evolution of species-rich genera, though the diversity of functional traits that lead to success in different successional habitats complicates analyses at the community scale. Examining the distribution of particular lineages with respect to successional gradients may provide more insight into the role of successional habitat specialization in the evolution of species-rich taxa

Environmental gradients and the evolution of successional habitat specialization: A test case with 14 Neotropical forest sites

https://www.scopus.com/inward/record.url?eid=2-s2.0-84939570316&partnerID=40&md5=fcadae8e6c274e8b7efca96099304a7cSuccessional gradients are ubiquitous in nature, yet few studies have systematically examined the evolutionary origins of taxa that specialize at different successional stages. Here we quantify successional habitat specialization in Neotropical forest trees and evaluate its evolutionary lability along a precipitation gradient. Theoretically, successional habitat specialization should be more evolutionarily conserved in wet forests than in dry forests due to more extreme microenvironmental differentiation between early and late-successional stages in wet forest. We applied a robust multinomial classification model to samples of primary and secondary forest trees from 14 Neotropical lowland forest sites spanning a precipitation gradient from 788 to 4000 mm annual rainfall, identifying species that are old-growth specialists and secondary forest specialists in each site. We constructed phylogenies for the classified taxa at each site and for the entire set of classified taxa and tested whether successional habitat specialization is phylogenetically conserved. We further investigated differences in the functional traits of species specializing in secondary vs. old-growth forest along the precipitation gradient, expecting different trait associations with secondary forest specialists in wet vs. dry forests since water availability is more limiting in dry forests and light availability more limiting in wet forests. Successional habitat specialization is non-randomly distributed in the angiosperm phylogeny, with a tendency towards phylogenetic conservatism overall and a trend towards stronger conservatism in wet forests than in dry forests. However, the specialists come from all the major branches of the angiosperm phylogeny, and very few functional traits showed any consistent relationships with successional habitat specialization in either wet or dry forests. Synthesis. The niche conservatism evident in the habitat specialization of Neotropical trees suggests a role for radiation into different successional habitats in the evolution of species-rich genera, though the diversity of functional traits that lead to success in different successional habitats complicates analyses at the community scale. Examining the distribution of particular lineages with respect to successional gradients may provide more insight into the role of successional habitat specialization in the evolution of species-rich taxa

Biodiversity recovery of Neotropical secondary forests

Old-growth tropical forests harbor an immense diversity of tree species but are rapidly being cleared, while secondary forests that regrow on abandoned agricultural lands increase in extent. We assess how tree species richness and composition recover during secondary succession across gradients in environmental conditions and anthropogenic disturbance in an unprecedented multisite analysis for the Neotropics. Secondary forests recover remarkably fast in species richness but slowly in species composition. Secondary forests take a median time of five decades to recover the species richness of old-growth forest (80% recovery after 20 years) based on rarefaction analysis. Full recovery of species composition takes centuries (only 34% recovery after 20 years). A dual strategy that maintains both old-growth forests and species-rich secondary forests is therefore crucial for biodiversity conservation in human-modified tropical landscapes. Copyright © 2019 The Authors, some rights reserved

Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics

Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km2 of land (28.1%of the total study area).Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forestmanagement, natural regeneration of second-growth forests provides a low-costmechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services. © 2016 The Authors

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

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

Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests

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