Abstract We provide a map and shapefile of the 57 biogeographic provinces of the Neotropical region. Recognition of these provinces is based on their endemic species, but their delimitation on the map is based on ecoregions combining climatic, geological, and biotic criteria. These provinces belong to the Antillean, Brazilian and Chacoan subregions, and the Mexican and South American transition zones. We provide a vector file of the biogeographical regionalization by converting the map into a polygon shapefile and a raster file with all provinces.

Abstract: Hierarchical intensity analysis of land cover/use change is a quantitative framework of nested spatial analyses that allows the estimation of changes using a change matrix at three levels of order: time interval, category, and transition. The intention of this article is to present the advantages of this framework in analyzing the dynamics of land use/ cover change using the change matrix, which has been commonly used for this purpose. However, even though the change matrix identifies some key patterns, it does not indicate whether the observed patterns have derived from processes that are systematically more or less intense than a random or uniform process. Among the most important considerations in intensity of change analysis is the use of a hierarchical order that starts at the time interval level, then takes into account the level of categories and culminates at level of transitions. Thus, the areas of each category at the start and end times serve to establish a uniform basis for the comparison between the expected and observed changes. In this way it is possible to define more clearly the patterns of change between time intervals and identifying potential drivers of the process. We present apply this analysis for two time periods (2000-2004 and 2004-2008) in the Biosphere Reserve Sierra de Manantlán (BRSM), a highly heterogeneous area in terms of vegetation type and land use, which was declared as a reserve in the last decade of the twentieth century. We used the cartography from INEGI at a 1:50,000 scale, updated by means of a Landsat ETM+ image for the year 2000, and SPOT 5 images for 2004 and 2008. Our analysis has allowed us to determine the time interval in which the general annual change rate was higher; which categories were most active and which latent; which categories were targets of active transitions; and if the pattern of change remained stable through time. We observed a fast annual rate of change between 2000 and 2004, with an absolute change of 70.936 hectares in comparison to the period 2004-2008, which showed a slower rate of change, of 2,194 ha in absolute terms. These results show a deceleration in the overall process of transformation of land use, which could be related to the publication and implementation of the BRSM management plan in 2000, which may have restricted land-use change in the core zones. At the category level, we found high rates of deforestation of tropical forests to agricultural and livestock production uses, and latency in temperate forests with a slower intensity of transition towards these uses. In this regard, the temperate forests are latent coverages that do not fall in the change intensively in the overall dynamics of change and could mean they are in a state of minor disturbance. However, there might be a degradation process, since in the case of introduction of cattle, this grazing free mainly in the rainy season directly affecting the temperate forest understory. In terms of change rate, the tropical forests had an estimated -1% per year rate. In contrast, forests showed lower rates of change of -0.5% per year. The land uses change rates such as irrigated agriculture, induced pasture, urban areas and iron mine were above 1% per year, indicating an increase in its surface in both periods. An intensive process of change observed in both periods at the category level is the loss of tropical dry forest. The areas of higher change are located in the buffer and influence zones, where the management plan does not regulate land use. In particular, long-established livestock production activity in the region appears as the driving factor of deforestation, affecting both tropical and temperate forests though at different rates. Finally, the cartography derived from the analysis of intensity of change is a contribution for decision-making concerning the management of the BRSM with emphasis in the buffer zone.

Resumen: El análisis jerárquico de intensidad de cambio de cobertura/uso de suelo es un marco cuantitativo de análisis espacial anidado que permite estimar los cambios en tres niveles de orden, intervalo de tiempo, categoría y transición, a partir de una matriz de cambio. Se presenta su aplicación para dos periodos de tiempo 2000-2004 y 2004-2008 en la Reserva de la Biosfera Sierra de Manantlán, área de estudio altamente heterogénea en términos de los tipos de vegetación y usos del suelo. Se usó cartografía del INEGI a escala 1:50 000 actualizada mediante una imagen Landsat ETM+ del 2000 e imágenes SPOT para 2004 y 2008. El análisis permitió conocer en qué intervalo de tiempo la tasa anual general de cambio es más rápida, cuáles son las categorías más activas y cuáles son latentes; cuáles son las categorías objetivo para las transiciones activas, y si el patrón de cambio es estable en el tiempo. Se observó una mayor tasa anual de cambio entre 2000 y 2004 en comparación con el periodo 2004-2008. A nivel de categorías, se encontraron altas tasas de deforestación de las selvas tropicales hacia usos agropecuarios, y latencia en bosques templados con baja intensidad de transición hacia usos agropecuarios. En particular la actividad ganadera arraigada en la región aparece como factor promotor del proceso de deforestación, que en la praxis sobre el terreno se expresa diferencialmente en selvas y bosques.

The Mexican Mountain Component (MMC) includes six biogeographical provinces. In this manuscript, we propose to use endemic taxa as surrogates to prioritize for conservation areas of the MMC. We use the distribution of 24 endemic mammals to prioritize conservation sites in the MMC and to evaluate the current Mexican system of protected natural areas (PNA). We used species distribution models and the software ConsNet 2.0 to prioritize areas for conservation, evaluating two algorithms (the representation maximization problem, and the area minimization problem) and two different representation targets (10% and 25%) of the distributional area of endemic taxa. In addition, we considered the effects of including existing PNA and/or excluding areas with altered vegetation. The representation maximization problem including current PNA was ineffective for reaching conservation targets. Meanwhile, all area minimization problems allowed us to prioritize areas reaching the targets of surrogates. In particular, a strategy that considers area minimization problem using a target of 10% of the distribution of surrogates, including PNA and excluding the altered vegetation, was the most favorable for maintaining the distributional patterns of the endemic mammals. This solution proposes the protection of a total of 37,460 km2, covering areas with altitude above 2,400 m located mainly in the Sierra Madre Occidental, the Transmexican Volcanic Belt, and provinces of the Sierra Madre del Sur. A prioritization strategy based on the distribution of endemic mammals as surrogates can help to maintain the distributional patterns of endemism of the Mexican biota.

El Componente Mexicano de Montaña (CMM) ocupa los principales sistemas montañosos de México, incluyendo seis provincias biogeográficas. En este manuscrito, proponemos que los taxones endémicos pueden ser utilizados para priorizar áreas de conservación en el CMM. Se priorizaron sitios de conservación con base en la distribución de 24 mamíferos endémicos; seguidamente se evaluó el sistema de áreas naturales protegidas (ANP) de México, a través de la representación de los mamíferos endémicos. Se utilizaron modelos de distribución de especies y el software ConsNet 2.0 para priorizar áreas de conservación, empleando dos algoritmos: el problema de máxima representación y el problema de área mínima. Además, se utilizaron dos metas de representación: 10% y 25% del área de distribución de las especies endémicos. Además, se consideraron las ANP existentes y se excluyeron áreas de vegetación alterada para algunos ejercicios. El problema de representación máxima, incluyendo las ANP actuales, fue ineficaz para alcanzar las metas de conservación. Mientras, todos los problemas de área mínima permitieron priorizar áreas que alcanzan las metas de los subrogados. En particular, la estrategia que considera el problema de área mínima con un objetivo del 10% de la distribución de los subrogados (incluidas las ANP y excluyendo la vegetación alterada) puede ayudar a mantener los patrones de distribución de endemismo en la biota mexicana. Esta estrategia incluye 37,460 km2, cubriendo áreas por encima de los 2,400 metros y que se encuentran principalmente en la Sierra Madre Occidental, la Faja Volcánica Transmexicana, y las provincias de la Sierra Madre del Sur. Una estrategia basada en áreas priorizadas en función de los mamíferos endémicos como subrogados puede ayudar a mantener los patrones de distribución de endemismo de la biota mexicana.

We evaluated the relevance of threshold selection in species distribution models on the delimitation of areas of endemism, using as case study the North American mammals. We modeled 40 species of endemic mammals of the Nearctic region with Maxent, and transformed these models to binary maps using four different thresholds: minimum training presence, tenth percentile training presence, equal training sensitivity and specificity, and 0.5 logistic probability. We analyzed the binary maps with the optimality method in order to identify areas of endemism and compare our results regarding previous analyses. The majority of the species tend to have very low values for the minimum training presence, whereas most of the species have a value of the tenth percentile training presence around 0.5, and the equal training sensitivity and specificity was around 0.3. Only with the tenth percentile threshold we recovered three out of the four patterns of endemism identified in North America, and detected more endemic species. The best identification of areas of endemism was obtained using the tenth percentile training presence threshold, which seems to recover better the distributional area of the mammals analyzed.

Evaluamos la relevancia de la selección del umbral en los modelos de distribución de especies en la delimitación de las áreas de endemismo, usando como un caso de estudio a los mamíferos de América del Norte. Modelamos 40 especies de mamíferos endémicos de la región Neártica con Maxent, y transformamos esos modelos a mapas binarios usando cuatro umbrales diferentes: presencia mínima de entrenamiento, percentil diez de la presencia de entrenamiento, igual sensibilidad y especificidad de entrenamiento, y probabilidad logística de 0.5. Los mapas binarios los analizamos con el método de optimación con el objeto de identificar áreas de endemismo y comparar nuestros resultados con estudios previos. La mayoría de las especies mostró tendencias hacia valores muy bajos de la presencia mínima de entrenamiento, mientras que la mayoría tuvo un valor del percentil diez de la presencia de entrenamiento alrededor de 0.5, y de igual sensibilidad y especificidad de entrenamiento alrededor de 0.3. Únicamente con el percentil diez de la presencia de entrenamiento se recuperaron tres de los cuatro patrones de endemismo identificados para América del Norte y se detectaron más especies endémicas. La identificación de áreas de endemismo más eficiente se obtuvo usando el umbral del percentil diez de la presencia de entrenamiento, el cual parece recuperar mejor las áreas de distribución de los mamíferos analizados.