http://www.snib.mx/iptconabio/resource?r=SNIB-JM036 Modelaje de la Distribución geográfica de Pinus pseudostrobus y P. leiophylla Cuauhtémoc Sáenz Romero Universidad Michoacana de San Nicolás de HidalgoInstituto de Investigaciones Agropecuarias y Forestales, Unidad San Juanito Itzícuaro Responsable
Morelia Michoacán 58330 MX
Tel (443) 334-0475, Ext. 118, Fax ext 200
CONABIO Comisión nacional para el conocimiento y uso de la biodiversidad Comisión Nacional para el Conocimiento y Uso de la Biodiversidad Dirección General de Sistemas
Liga Periférico-Insurgentes Sur No. 4903, Col. Parques del Pedregal MÉXICO Tlalpan 14010 MX
50045000 patricia.ramos@conabio.gob.mx https://www.gob.mx/conabio
2018-08-20 spa The objective of the proposal is to model the geographic distribution of Pinus psedostrobus and P. leiophylla, by predicting the distribution of their suitable habitat from climate variables. Both species are very important on their ecological role as components of the pine-oak and coniferous forest in México. Pinus psedostrobus is one of the most economically important species in the Neovolcanic Axis (named also Trans-Mexican Volcanic Belt) for its good wood quality, relatively fast growth rate and straight stem. P. leiophylla is usually heavily tapped for resin production and its distribution reaches southern USA, making it a subject for bi-national interest due to its potential to colonize USA grassland-forest transition areas under climatic change scenarios. We will use presence/absence data from (a previously screened for errors) Mexican National Forest Inventory and climatic variables estimated by a spline climate model. Presence or absence in the contemporary climate will be predicted from climate variables obtained for each observation from spline climate surfaces available for Mexico and the rest of North America. A climate profile for each species will be constructed by selecting 5 to 8 of the most relevant climatic variables from 36 climatic variables using the Random Forests algorithm in R. Relevant climate variables are selected according to importance values calculated by the statistical software and according to the errors of prediction of the classification tree. The best fitting models will be used to predict the suitability of the climate for the species on maps gridded at 1 km2 , and distribution maps will be constructed with ArcMap. As an extra product, we will predict the distribution of their suitable habitat for the years 2030, 2060 and 2090, using combinations of three General Circulation Models and two emission scenarios (low and elevated emissions). We considered that management plans for both biological conservation and commercial use must consider actions to accommodate the climatic change, such as assisted migration or assisted colonization. Reino: 1 Filo: 1 Clase: 1 Orden: 1 Familia: 1 Género: 1 Especie: 2 Occurrence GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type.xml Specimen GBIF Dataset Subtype Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_subtype.xml Plantas N/A This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License. http://www.snib.mx/proyectos/cgi-bin/datos2.cgi?Letras=JM&Numero=36 País: ESTADOS UNIDOS DE AMERICA (ARIZONA, NEW MEXICO) País: MEXICO (CHIAPAS, CHIHUAHUA, COAHUILA DE ZARAGOZA, DISTRITO FEDERAL, DURANGO, GUANAJUATO, GUERRERO, HIDALGO, JALISCO, MEXICO, MICHOACAN DE OCAMPO, MORELOS, NAYARIT, NUEVO LEON, OAXACA, PUEBLA, QUERETARO DE ARTEAGA, SAN LUIS POTOSI, SINALOA, SONORA, TAMAULIPAS, TLAXCALA, VERACRUZ DE IGNACIO DE LA LLAVE, ZACATECAS) -110.92 -92.14 34.32 15.45 Reino: Plantae Filo: Tracheophyta Clase: Equisetopsida Orden: Pinales Familia: Pinaceae kingdom Plantae phylum Tracheophyta class Equisetopsida order Pinales family Pinaceae genus Pinus species Pinus pseudostrobus canish, chalmaite, chamaite, mocochtaj, montezumae, ocote, ocote blanco, ocote liso, oeste, pacinto, pinabete, pino, pino amarillo, pino blanco, pino cantzimbo, pino chamaite, pino de cono chico, pino de hoja fina, pino lacio, pino liso, pino ortiguillo, pino real, tuusha species Pinus leiophylla manzanita, ocote, ocote chino, palo otomite, pino, pino blanco, pino chamonque, pino chino, pino negro, pino prieto, pino saguaco notPlanned Sonia Alejandra Careaga Olvera Comisión Nacional para el Conocimiento y Uso de la Biodiversidad Subcoordinadora en Información y Análisis
Liga Periférico-Insurgentes Sur No. 4903, Col. Parques del Pedregal México Tlalpan 14010 MX
50045000 scareaga@conabio.gob.mx https://www.gob.mx/conabio
Modelaje de la Distribución geográfica de Pinus pseudostrobus y P. leiophylla Cuauhtémoc Sáenz Romero Content Provider Gerald E. Rehfeldt Principal Investigator The objective of the proposal is to model the geographic distribution of Pinus psedostrobus and P. leiophylla, by predicting the distribution of their suitable habitat from climate variables. Both species are very important on their ecological role as components of the pine-oak and coniferous forest in México. Pinus psedostrobus is one of the most economically important species in the Neovolcanic Axis (named also Trans-Mexican Volcanic Belt) for its good wood quality, relatively fast growth rate and straight stem. P. leiophylla is usually heavily tapped for resin production and its distribution reaches southern USA, making it a subject for bi-national interest due to its potential to colonize USA grassland-forest transition areas under climatic change scenarios. We will use presence/absence data from (a previously screened for errors) Mexican National Forest Inventory and climatic variables estimated by a spline climate model. Presence or absence in the contemporary climate will be predicted from climate variables obtained for each observation from spline climate surfaces available for Mexico and the rest of North America. A climate profile for each species will be constructed by selecting 5 to 8 of the most relevant climatic variables from 36 climatic variables using the Random Forests algorithm in R. Relevant climate variables are selected according to importance values calculated by the statistical software and according to the errors of prediction of the classification tree. The best fitting models will be used to predict the suitability of the climate for the species on maps gridded at 1 km2 , and distribution maps will be constructed with ArcMap. As an extra product, we will predict the distribution of their suitable habitat for the years 2030, 2060 and 2090, using combinations of three General Circulation Models and two emission scenarios (low and elevated emissions). We considered that management plans for both biological conservation and commercial use must consider actions to accommodate the climatic change, such as assisted migration or assisted colonization. Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) Plantas Sin flores; gimnospermas coníferas (pinos)
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