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)
2023-10-18T12:00:00.000-05:00
dataset
SNIB-JM036-CSV.zip
UTF-8
CSV
http://www.snib.mx/proyectos/JM036/SNIB-JM036-CSV.zip
SNIB-JM036-BD.zip
UTF-8
MDB
MicrosoftAccess2007
http://www.snib.mx/proyectos/JM036/SNIB-JM036-BD.zip
NO APLICA
SNIB-JM036-JM0361406F_SIB2015.10.21-ND
NO APLICA;NO APLICA;United States Forest Service, United States Department of Agriculture;USFS-USDA
NO APLICA
SNIB-JM036-JM0361406F_SIB2015.10.21-ND
NO APLICA;NO APLICA;Comisión Nacional Forestal;CONAFOR
Ejemplar
1
1889