2022
Arima, Eugenio Y.; Denvir, Audrey; Young, Kenneth R.; González-Rodríguez, Antonio; García-Oliva, Felipe
Modelling avocado-driven deforestation in Michoacán, Mexico Artículo de revista
En: Environmental Research Letters, vol. 17, iss. 3, 2022, ISSN: 17489326.
Resumen | Enlaces | Etiquetas: climate change, commodities, land change modelling, land use change
@article{Arima2022,
title = {Modelling avocado-driven deforestation in Michoacán, Mexico},
author = {Eugenio Y. Arima and Audrey Denvir and Kenneth R. Young and Antonio González-Rodríguez and Felipe García-Oliva},
doi = {10.1088/1748-9326/ac5419},
issn = {17489326},
year = {2022},
date = {2022-01-01},
journal = {Environmental Research Letters},
volume = {17},
issue = {3},
publisher = {IOP Publishing Ltd},
abstract = {As demand for avocado climbs, avocado production in Michoacán - Mexico's biggest avocado growing region - expands into new places. We use a spatial probit model to project the geographic distribution of likely future avocado expansion and analyze those results to determine (a) threats to specific forest types and (b) how the distribution of avocado is shifting spatially under current and future climate scenarios. Our results suggest that avocado expansion in Michoacán is strongly driven by distance to existing agriculture, roads, and localities, as well as the dwindling availability of Andosol soils. As future expansion ensues, it presents risk of forest loss across various forest types, with pine-oak forest, mesophilic montane forest, and oyamel fir forest being of particular concern. Moreover, our results suggest that avocado production will occupy wider ranges in terms of temperature, precipitation, slope steepness and soil. The model predicts that climate change will alter the spatial distribution of avocado plantings, expanding into forest types at lower and at higher elevations. Forest loss threatens ecosystem degradation, and a wider avocado crop production footprint could lead to orchard establishment into dwindling forests that host a high diversity of native oaks and charismatic species, including the monarch butterfly.},
keywords = {climate change, commodities, land change modelling, land use change},
pubstate = {published},
tppubtype = {article}
}
As demand for avocado climbs, avocado production in Michoacán - Mexico's biggest avocado growing region - expands into new places. We use a spatial probit model to project the geographic distribution of likely future avocado expansion and analyze those results to determine (a) threats to specific forest types and (b) how the distribution of avocado is shifting spatially under current and future climate scenarios. Our results suggest that avocado expansion in Michoacán is strongly driven by distance to existing agriculture, roads, and localities, as well as the dwindling availability of Andosol soils. As future expansion ensues, it presents risk of forest loss across various forest types, with pine-oak forest, mesophilic montane forest, and oyamel fir forest being of particular concern. Moreover, our results suggest that avocado production will occupy wider ranges in terms of temperature, precipitation, slope steepness and soil. The model predicts that climate change will alter the spatial distribution of avocado plantings, expanding into forest types at lower and at higher elevations. Forest loss threatens ecosystem degradation, and a wider avocado crop production footprint could lead to orchard establishment into dwindling forests that host a high diversity of native oaks and charismatic species, including the monarch butterfly.
2018
Martins, Karina; Gugger, Paul F.; Llanderal-Mendoza, Jesus; González-Rodríguez, Antonio; Fitz-Gibbon, Sorel T.; Zhao, Jian Li; Rodríguez-Correa, Hernando; Oyama, Ken; Sork, Victoria L.
Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa Artículo de revista
En: Evolutionary Applications, vol. 11, iss. 10, pp. 1842-1858, 2018, ISSN: 17524571.
Resumen | Enlaces | Etiquetas: assisted gene flow, climate change, genotyping by sequencing, landscape genomics, natural selection, Quercus, restoration, Trans-Mexican Volcanic Belt
@article{Martins2018,
title = {Landscape genomics provides evidence of climate-associated genetic variation in Mexican populations of Quercus rugosa},
author = {Karina Martins and Paul F. Gugger and Jesus Llanderal-Mendoza and Antonio González-Rodríguez and Sorel T. Fitz-Gibbon and Jian Li Zhao and Hernando Rodríguez-Correa and Ken Oyama and Victoria L. Sork},
doi = {10.1111/eva.12684},
issn = {17524571},
year = {2018},
date = {2018-01-01},
journal = {Evolutionary Applications},
volume = {11},
issue = {10},
pages = {1842-1858},
publisher = {Wiley-Blackwell},
abstract = {Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 FST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.},
keywords = {assisted gene flow, climate change, genotyping by sequencing, landscape genomics, natural selection, Quercus, restoration, Trans-Mexican Volcanic Belt},
pubstate = {published},
tppubtype = {article}
}
Local adaptation is a critical evolutionary process that allows plants to grow better in their local compared to non-native habitat and results in species-wide geographic patterns of adaptive genetic variation. For forest tree species with a long generation time, this spatial genetic heterogeneity can shape the ability of trees to respond to rapid climate change. Here, we identify genomic variation that may confer local environmental adaptations and then predict the extent of adaptive mismatch under future climate as a tool for forest restoration or management of the widely distributed high-elevation oak species Quercus rugosa in Mexico. Using genotyping by sequencing, we identified 5,354 single nucleotide polymorphisms (SNPs) genotyped from 103 individuals across 17 sites in the Trans-Mexican Volcanic Belt, and, after controlling for neutral genetic structure, we detected 74 FST outlier SNPs and 97 SNPs associated with climate variation. Then, we deployed a nonlinear multivariate model, Gradient Forests, to map turnover in allele frequencies along environmental gradients and predict areas most sensitive to climate change. We found that spatial patterns of genetic variation were most strongly associated with precipitation seasonality and geographic distance. We identified regions of contemporary genetic and climatic similarities and predicted regions where future populations of Q. rugosa might be at risk due to high expected rate of climate change. Our findings provide preliminary details for future management strategies of Q. rugosa in Mexico and also illustrate how a landscape genomic approach can provide a useful tool for conservation and resource management strategies.