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Botanica 90(3) Botanical Sciences 90 (3): 331-340, 2012 ECOLOGY POTENTIAL DISTRIBUTION OF HUMID MOUNTAIN FOREST IN MEXICO GUSTAVO CRUZ-CÁRDENAS1,3, JOSÉ LUIS V ILLASEÑOR1, LAURO LÓPEZ-MATA2 AND ENRIQUE ORTIZ1 1Instituto de Biología, Departamento de Botánica, Universidad Nacional Autónoma de México, México D.F., México. 2Posgrado en Botánica, Colegio de Postgraduados, Campus Montecillo, Texcoco, México. 3Autor para la correspondencia: [email protected] Abstract: Humid Mountain Forest is one of the most important Mexican biomes due to the high fl oristic richness and endemism found within its small geographical extension. The distribution of this biome is not well known in the country; accordingly, the goal of this paper is to delimit its distribution by using potential distribution models of species characteristic to the biome as surrogates. Based on herbarium specimens housed at the National Herbarium of Mexico, a database of 78 species restricted or mostly restricted to Humid Mountain Forest was constructed. In addition, 56 environmental covariates (26 climatic, nine soil properties, nine topo- graphic attributes, and 14 remote sensing data) were assembled. Species modeling was done using MaxEnt. Twenty-three covari- ates defi ned the Humid Mountain Forest distribution in Mexico. Among these, normalized vegetation index for May, total annual precipitation, and organic carbon content in the soil were the most important. According to the models, Humid Mountain Forest in Mexico represents 7% of the total surface of the country and it is found in 25 of the 32 states. Chiapas, Guerrero, Michoacán, and Oaxaca are the most outstanding states since they collectively account for 74% of the total Humid Mountain Forest surface. Keywords: maximum entropy, MODIS remote sensing data, soil properties. Resumen: El Bosque Húmedo de Montaña es uno de los biomas más importantes de México, pues allí se encuentra una gran riqueza fl orística y de endemismos, restringida a una pequeña extensión geográfi ca. Hasta la fecha no se sabe a ciencia cierta la ex- tensión real de este bioma en el país; por tal razón, el objetivo de este trabajo es delimitar su distribución utilizando como variables substitutas la distribución potencial de especies vegetales características de este bioma. Con base en el estudio de especímenes de herbario depositados en el Herbario Nacional de México, se generó una base de datos de 78 especies restringidas o casi restringidas al Bosque Húmedo de Montaña. Por otra parte, se usaron 56 covariables ambientales (26 de clima, nueve propiedades de suelos, nueve atributos topográfi cos y 14 datos de sensores remotos). Los modelos de distribución potencial fueron elaborados utilizando el programa Maxent. Las covariables que resultaron ser signifi cativas para la modelación de la distribución del Bosque Húmedo de Montaña fueron 23; entre las más importantes se encuentran el índice de vegetación normalizada del mes de mayo, la precipitación total anual y el contenido de carbono orgánico en el suelo. De acuerdo con el modelo, el Bosque Húmedo de Montaña en México representa 7% de su territorio y se encuentra en 25 de sus 32 entidades políticas; Chiapas, Guerrero, Michoacán y Oaxaca son los estados más importantes, pues en su territorio se ubica 74% de la superfi cie total del Bosque Húmedo de Montaña. Palabras Clave: datos de sensores remotos de MODIS, máxima entropía, propiedades de suelos. umid Mountain Forest (HMF) is found in areas with face area (Rzedowski, 1978; Villaseñor, 2010). This high Hhigh concentrations of moisture, especially between richness, found mostly in a relatively small surface in the 1,000 and 3,000 m elevation. Moisture results from the ex- mountain chains, is accompanied by high environmental istence of rainfall during most of the year, often also due heterogeneity (climate, soil, elevation) and a high degree of to the condensation of clouds or their persistence as fog at fragmentation throughout its distributional extent (Vázquez- ground level (Villaseñor, 2010). Mountain tropical compo- García, 1995; Ramírez-Marcial et al., 2001). nents mixed with other typically boreal plants and an abun- HMF (in Mexico mostly known as “bosque mesófi lo dance of climbing and epiphyte plants predominate in HMF. de montaña”, “bosque de neblina”, or “mountain cloud HMF is among the most important Mexican biomes forest”) occurs in all the Mexican mountain chains, from because it contains the richest fl oristic diversity per sur- southern Sonora and Tamaulipas to Chiapas (Challenger, 331 GUSTAVO CRUZ-CÁRDENAS ET AL. 1998; Villaseñor, 2010). This biome includes a broad set of Table 1. List of covariates used to model the Humid Mountain Forest diverse plant associations that differ in structure and compo- (HMF) potential distribution sition, as well as in degree of human disturbance, and/or de- Type Covariates gree of conservation (Rzedowski, 1996; Challenger, 1998; Climate bio1 (annual mean temperature), bio2 (mean Ramírez-Marcial et al., 2001; Luna-Vega et al., 2006). (WORLDCLIM) diurnal range (mean of monthly (max temp - min Recently, a revision of the fl oristic and taxonomic litera- temp))), bio3 (isothermality (bio2/bio7) * (100), ture of the Mexican HMF (Villaseñor, 2010), indicated the bio4 (temperature seasonality (standard deviation occurrence of 6,790 species, about 40% of which are re- *100)), bio5 (maximum temperature of warmest stricted or almost restricted to the biome. The importance month), bio6 (minimum temperature of coldest month), bio7 (temperature annual range (bio5- of HMF to the Mexican vascular fl ora, in addition to the bio6)), bio8 (mean temperature of wettest quarter), high species richness, is its high level of endemic to Mexi- bio9 (mean temperature of driest quarter), bio10 co species (34.8%). Moreover, this biome is found in only (mean temperature of warmest quarter), bio11 0.6% (Rzedowski, 1996) of the total surface of the country (mean temperature of coldest quarter), bio12 2 (annual precipitation), bio13 (precipitation of (11,719 km ), ranking its territory as that with the highest wettest month), bio14 (precipitation of driest density of species per surface area, with few conservation month), bio15 (precipitation seasonality strategies and high human population pressure. These lat- (coeffi cient of variation)), bio16 (precipitation of ter conditions cast doubts on the viability of strategies pro- wettest quarter), bio17 (precipitation of driest posed for the management and conservation of its natural quarter), bio18 (precipitation of warmest quarter), bio19 (precipitation of coldest quarter). capital, regardless of scale (national, regional, or local) In addition we calculated the precipitation and (Bubb, 1991; Ramírez-Marcial et al., 2001; Ramírez-Mar- the temperature of both the humid and dry cial, 2002). It is estimated that more than 50% of the origi- months, as well as the real annual evapotranspi- nal surface of HMF has been replaced with grasslands for ration, of the humid and dry months† cattle grazing, farming, or for coffee plantations (Cayuela et Topographic Altitude, slope, aspect (from 0° to 359°), runoff, al., 2006a). These changes in land use have caused a reduc- attributes convergence index, topographic humidity index, tion in the structural diversity of HMF, as well as a decrease (GTOPO web) terrain rugosity index (Riley et al., 1999), vector’s rugosity measure (Sappington et al., 2007), and in the water quality due to the increase of contaminants in anisotropic heating streams (Martínez et al., 2009). More than half of the pres- ent HMF surface in Mexico is classifi ed as a high priority Soil properties Organic matter, sodium absorption ratio, pH, (geostatistical electric conductivity, organic carbon, potassium, zone (Toledo-Aceves et al., 2011), that is, characterized by analysis by sodium, magnesium, and calcium a high forest quality but endangered by human activities. Cruz-Cárdenas et al. (2012) Floristic knowledge of the Mexican HMF is poor and the efforts to overcome such defi ciency scarce. Therefore, in- Remote sensig 14 vegetation indices (monthly average, humid formation in digital format about this biome is practically data and dry months average) from year 2009 (MODIS web) absent, especially information relevant for understanding geographical patterns either of the biome in general or their †The humid months go from May to October and the dry months from species. Geographical data matched with taxonomic identi- November to April; evapotranspiration was calculated based on Turc’s ties are fundamental to modeling and predicting potential model (1954), where ETRA = P / [0.9 + (P/L)2]1/2; P= total annual pre- cipitation (mm); L = 300 + 25T +0.05T3; and T = mean annual tem- species distributions (Phillips et al., 2006). Accordingly, the perature (°C). aim of this study was to determine the potential distribu- tion of HMF. To do this, we determined the environmental requirements of several species restricted to this biome and ma de México (Table 2). All records fulfi lled the following then extrapolated this data as a surrogate measurement for two requirements: (1) their taxonomic identifi cation was outlining its geographic extension. correct (annotated by a taxonomist specialist) and (2) they belong to species known to be restricted or almost restricted Materials and methods to HMF (Villaseñor, 2010), occurring only in one or more of the vegetation types included by Villaseñor (2010) as con- Environmental covariates. 56 covariates were used, each stituting HMF. with a 1 km2 pixel resolution;
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