Modeling the Potential Distribution of Picea chihuahuana Martínez, an Endangered Species at the Sierra Madre Occidental, Mexico

Aguilar-Soto, Victor; Melgoza‐Castillo, Alicia; Villarreal‐Guerrero, Federico; Wehenkel, Christian; Pinedo-Alvarez, Carmelo

doi:10.3390/f6030692

Cited by 20 publications

(15 citation statements)

References 27 publications

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“…However, it will be important to specifically consider local micro climatic conditions that are not easy modelled with simple macro climate models (Aguilar-Soto et al, 2015), but can be recorded at new local weather stations within the populations.…”

Section: Discussionmentioning

confidence: 99%

Discrimination ofPicea chihuahuanaMartinez populations on the basis of climatic, edaphic, dendrometric, genetic and population traits

Dominguez-Guerrero

Mariscal-Lucero

Hernández-Díaz

et al. 2017

PeerJ

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BackgroundPicea chihuahuana, which is endemic to Mexico, is currently listed as “Endangered” on the Red List. Chihuahua spruce is only found in the Sierra Madre Occidental (SMO), Mexico. About 42,600 individuals are distributed in forty populations. These populations are fragmented and can be classified into three geographically distinct clusters in the SMO. The total area covered by P. chihuahuana populations is less than 300 ha. A recent study suggested assisted migration as an alternative to the ex situ conservation of P. chihuahuana, taking into consideration the genetic structure and diversity of the populations and the predictions regarding the future climate of the habitat. However, detailed background information is required to enable development of plans for protecting and conserving species and for successful assisted migration. Thus, it is important to identify differences between populations in relation to environmental conditions. The genetic diversity of populations, which affect vigor, evolution and adaptability of the species, must also be considered. In this study, we examined 14 populations of P. chihuahuana, with the overall aim of discriminating the populations and form clusters of this species.MethodsEach population was represented by one 50 × 50 m plot established in the center of its respective location. Climate, soil, dasometric, density variables and genetic and species diversities were assessed in these plots for further analyses. The putatively neutral and adaptive AFLP markers were used to calculate genetic diversity. Affinity Propagation (AP) clustering technique and k-means clustering algorithm were used to classify the populations in the optimal number of clusters. Later stepwise binomial logistic regression was applied to test for significant differences in variables of the southern and northern P. chihuahuana populations. Spearman’s correlation test was used to analyze the relationships among all variables studied.ResultsThe binomial logistic regression analysis revealed that seven climate variables, the geographical longitude and sand proportion in the soil separated the southern from northern populations. The northern populations grow in more arid and continental conditions and on soils with lower sand proportion. The mean genetic diversity using all AFLP studied of P. chihuahuana was significantly correlated with the mean temperature in the warmest month, where warmer temperatures are associated to larger genetic diversity. Genetic diversity of P. chihuahuana calculated with putatively adaptive AFLP was not statistically significantly correlated with any environmental factor.DiscussionFuture reforestation programs should take into account that at least two different groups (the northern and southern cluster) of P. chihuahuana exist, as local adaptation takes place because of different environmental conditions.

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Section: Discussionmentioning

confidence: 99%

Discrimination ofPicea chihuahuanaMartinez populations on the basis of climatic, edaphic, dendrometric, genetic and population traits

Dominguez-Guerrero

Mariscal-Lucero

Hernández-Díaz

et al. 2017

PeerJ

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“…Data were reclassified using the software ArcGis v9.2 (ESRI 2006;Pliscoff and Fuentes-Castillo 2011). Some previous studies of threatened species (Aguilar-Soto et al 2015;Rovzar et al 2013) established ranges of probability of occurrence based on the distribution of species. The 0.7 to 1 range indicates high probability of occurrence, where most geographic records are located; 0.5 to 0.7 indicates medium probability, including the remaining records; and finally threshold to 0.5 represents low probability of occurrence.…”

Section: Methodsmentioning

confidence: 99%

Predictive species distribution model of two endemic kangaroo rats from Mexico: Dipodomys ornatus and D. phillipsii (Rodentia: Heteromyidae)

Flores-Zamarripa

Fernández

2018

Therya

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Predictive species distribution models (SDMs) allow identifying suitable areas for the conservation of populations of endangered species. Dipodomys ornatus and D. phillipsii are two Nearctic rodents endemic to Mexico that inhabit arid and semiarid environments. Endemic species have a restricted distribution, making it difficult to monitor their distribution and conservation status. Therefore, it is important to understand the interactions between these species and the environmental/ecological variables in their local habitat. In this study, we constructed SDMs for these two rodents using MaxEnt (Maximum Entropy model). Also, we defined the areas with the suitable ecological characteristics for the preservation of the species. In order to construct an SDM for each species, we used MaxEnt at a national scale (Mexico), with a resolution of 30 arc-sec (1 km 2 ). To this end, 91 presence data (63 for D. ornatus and 28 for D. phillipsii) reported in the literature and data bases were used, along with 27 climatic and ecological variables. Maps with a high predictive capability (Area under a Receiver Operating Characteristic [ROC] Curve = AUC > 0.9) were obtained for both species. Principal Component Analyses were carried out, resulting in 11 PCs that accounted for 95% of variability of the original environmental variables. The D. ornatus SDM is defined mainly by PC2, PC11 and PC1. PC4, PC2 and PC6 are the most influential variables in predicting the SDM of D. phillipsii. Sites with suitable environmental conditions for D. ornatus are located in the States of Durango, Zacatecas, Aguascalientes, San Luis Potosí, and Guanajuato, whereas the best environmental conditions for D. phillipsii were found in Puebla, Tlaxcala, Veracruz, and Hidalgo. As these species have a restricted distribution and field sampling is difficult, determining their conservation status is a complex issue; however, SDMs are a useful tool to identify areas with ideal characteristics to conduct surveys aimed at determining their conservation status or that could be used as future natural protected areas.Los modelos predictivos de distribución de especies (MDE), permiten identificar áreas con condiciones adecuadas para la conservación de especies en peligro de extinción. Dipodomys ornatus y D. phillipsii, son dos roedores neárticos, endémicos de México, que habitan principalmente en regiones áridas y semiáridas. Las especies endémicas poseen una distribución restringida, lo que dificulta monitorear su distribución y estado de conservación. Por lo tanto, es importante comprender las interacciones que existen entre las especies y las variables ambientales/ ecológicas de los sitios donde estas habitan. En este estudio, se realizó un MDE de estos dos roedores utilizando MaxEnt (Modelo de máxima entropía). También se definieron áreas con las características ecológicas necesarias para la sobrevivencia de las especies que pueden ser utilizadas en programas futuros de conservación. Para construir el MDE, se utilizó el modelo MaxEnt a una escala nacional (México)...

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“…However, Mexico is also the country with the highest rates of deforestation worldwide [8]. Many of its native ecosystems are gradually being reduced to small remnants of the original vegetation [9]. To ensure the sustainability of forests, we need to characterize their structure [10].…”

Section: Introductionmentioning

confidence: 99%

Spatial Analysis of Temperate Forest Structure: A Geostatistical Approach to Natural Forest Potential

Prieto‐Amparán

Santellano‐Estrada

Villarreal‐Guerrero

et al. 2019

Forests

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Forest ecosystems represent an important means of ecosystem services; they are key as carbon sinks, water collectors, soil stabilizers, suppliers of great biological diversity, among other benefits. In addition, regionalization based on forest conditions provides a valuable approach to understanding and analyzing spatial patterns, which is useful as a tool for the implementation of forest ecosystem protection and conservation programs. In this research, the structure of a temperate forest in the western Sierra Madre region of Mexico was analyzed and characterized. The study unit was the watershed and the analysis used a geospatial approach combined with multivariate techniques such as: Principal Component Analysis, Cluster Analysis (CA), Discriminant Analysis (DA) and Multivariate Analysis of Variance. We evaluated the relationships among spectral satellite data, thematic maps and structural forest variables. A total of 345 watersheds were grouped based on these variables. The grouping of watersheds under low, medium and high production conditions was carried out with CA, defining 3 groups. The validation of the grouping was performed through DA, estimating errors with the restitution method, as well as with the cross-validation method. Significant differences were found among the groups. The grouping of watersheds provides observable evidence of the variability of the forest condition throughout the area. This study allows identifying forest areas with different levels of productivity and can help to detect levels of vulnerability and ecological fragility in natural forests in temperate zones.

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Modeling the Potential Distribution of Picea chihuahuana Martínez, an Endangered Species at the Sierra Madre Occidental, Mexico

Cited by 20 publications

References 27 publications

Discrimination ofPicea chihuahuanaMartinez populations on the basis of climatic, edaphic, dendrometric, genetic and population traits

Discrimination ofPicea chihuahuanaMartinez populations on the basis of climatic, edaphic, dendrometric, genetic and population traits

Predictive species distribution model of two endemic kangaroo rats from Mexico: Dipodomys ornatus and D. phillipsii (Rodentia: Heteromyidae)

Spatial Analysis of Temperate Forest Structure: A Geostatistical Approach to Natural Forest Potential

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