Item talk:Q64713
From geokb
{
"USGS Publications Warehouse": { "schema": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "USGS Numbered Series", "name": "Terrestrial ecosystems - Isobioclimates of the conterminous United States", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "sim3084", "url": "https://pubs.usgs.gov/publication/sim3084" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 97735 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.3133/sim3084", "url": "https://doi.org/10.3133/sim3084" } ], "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Scientific Investigations Map" } ], "datePublished": "2009", "dateModified": "2016-07-06", "abstract": "As part of an effort to map terrestrial ecosystems, the U.S. Geological Survey has generated isobioclimate classes to be used in creating maps depicting standardized, terrestrial ecosystem models for the conterminous United States, using an ecosystems classification developed by NatureServe . A biophysical stratification approach, developed for South America (Sayre and others, 2008) and now being implemented globally, was used to model the ecosystem distributions. Bioclimate regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and are therefore one of the key input layers in this biophysical stratification.\nThe Rivas-Mart\u00ednez methodology is based on the concept of establishing a quantifiable classification system which would closely relate the distribution of vegetation to climatic parameters and indices. This method first establishes bioclimatic indices calculated from various ranges of temperature and precipitation data, compares these indices to defined thresholds, and finally applies sets of decision rules to identify the climate classes. The climate classification is hierarchical with four levels: macrobioclimates, bioclimates, thermotypes, and ombrotypes. Thermotypes, which represent thermoclimatic belts, are identified using the positive annual temperature (Tp) thresholds or the compensated thermicity index (Itc) thresholds. Ombrotypes, which represent ombroclimatic belts, are based on the ombrothermic index (Io) which is calculated as a function of both the total positive precipitation and temperature . For this national implementation the source data used for establishing the bioclimatic indices was Daymet. Daymet temperature and precipitation data were developed from 18 years (1980\u20131997) of climatological records and is available at a spatial resolution of 1 kilometer . This implementation of the Rivas-Mart\u00ednez methodology resulted in the generation of four climate layers for the conterminous United States: macroclimates, bioclimates, thermotypes, and ombrotypes.\nHowever, the biophysical stratification approach used for the ecosystems modeling effort required a single climate layer that accurately reflected regional variation in wet/dry gradients and hot/cold gradients, with a manageable number of classes. Therefore, the data layers for thermotypes and ombrotypes were combined, yielding 127 unique thermotype-ombrotype combinations.The isobioclimates image shows ombrotypic regions (dry/wet gradients) for each thermotypic (warm/cold) region.\u00a0Additional information about this map and any of the data developed for the ecosystems modeling of the conterminous United States is available online at\u00a0http://rmgsc.cr.usgs.gov/ecosystems/.", "description": "Sheet: 45 x 35 inches", "publisher": { "@type": "Organization", "name": "U.S. Geological Survey" }, "author": [ { "@type": "Person", "name": "Cress, Jill J.", "givenName": "Jill J.", "familyName": "Cress" }, { "@type": "Person", "name": "Comer, Patrick", "givenName": "Patrick", "familyName": "Comer" }, { "@type": "Person", "name": "Warner, Harumi hwarner@usgs.gov", "givenName": "Harumi", "familyName": "Warner", "email": "hwarner@usgs.gov", "affiliation": [ { "@type": "Organization", "name": "NGTOC Denver", "url": "https://www.usgs.gov/national-geospatial-technical-operations-center" } ] }, { "@type": "Person", "name": "Sayre, Roger G. rsayre@usgs.gov", "givenName": "Roger G.", "familyName": "Sayre", "email": "rsayre@usgs.gov" } ], "funder": [ { "@type": "Organization", "name": "Rocky Mountain Geographic Science Center", "url": "https://www.usgs.gov/programs/national-geospatial-program" } ], "spatialCoverage": [ { "@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/4074035" }, { "@type": "Place", "geo": [ { "@type": "GeoShape", "additionalProperty": { "@type": "PropertyValue", "name": "GeoJSON", "value": { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": {}, "geometry": { "type": "Polygon", "coordinates": [ [ [ -97.18505859374999, 25.97779895546436 ], [ -97.42675781249999, 25.878994400196202 ], [ -98.2177734375, 26.115985925333536 ], [ -99.0966796875, 26.47057302237511 ], [ -99.580078125, 27.625140335093324 ], [ 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