Using Publicly Available Forest Inventory Data in Climate-Based Models of Tree Species Distribution: Examining Effects of True Versus Altered Location Coordinates. Gibson, J., Moisen, G., Frescino, T., & Edwards, T. C. Ecosystems, 17(1):43–53, 2014. doi abstract bibtex Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J. osteosperma) and two piñons (Pinus edulis, P. monophylla), were analyzed. The presence-absence models based on current climatic variables were generated over a series of species-specific modeling extents using Random Forests and applied to forecast climatic conditions. The distributions of predictor variables sampled with public coordinates were compared to those sampled with true coordinates using t tests with a Bonferroni adjustment for multiple comparisons. Public- and true-based models were compared using metrics of classification accuracy. The modeled current and forecast distributions were compared in terms of their overall areal agreement and their geographic mean centroids. Comparison of the underlying distributions of predictor variables sampled with true versus public coordinates did not indicate a significant difference for any species at any extent. Both the public- and true-based models had comparable classification accuracies across extent for each species, with the exception of one species, J. occidentalis. True-based models produced geographic distributions with smaller areas under current and future scenarios. The greatest areal difference occurred in the species with the lowest modeled accuracies (J. occidentalis), and had a forecast distribution which diverged severely. The other species had forecast distributions with similar magnitudes of modeled distribution shifts.
@article{gibsonUsingPubliclyAvailable2014,
title = {Using {{Publicly Available Forest Inventory Data}} in {{Climate}}-{{Based Models}} of {{Tree Species Distribution}}: {{Examining Effects}} of {{True Versus Altered Location Coordinates}}},
author = {Gibson, Jacob and Moisen, Gretchen and Frescino, Tracey and Edwards, Thomas C.},
year = {2014},
volume = {17},
pages = {43--53},
issn = {1435-0629},
doi = {10.1007/s10021-013-9703-y},
abstract = {Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J. osteosperma) and two pi\~nons (Pinus edulis, P. monophylla), were analyzed. The presence-absence models based on current climatic variables were generated over a series of species-specific modeling extents using Random Forests and applied to forecast climatic conditions. The distributions of predictor variables sampled with public coordinates were compared to those sampled with true coordinates using t tests with a Bonferroni adjustment for multiple comparisons. Public- and true-based models were compared using metrics of classification accuracy. The modeled current and forecast distributions were compared in terms of their overall areal agreement and their geographic mean centroids. Comparison of the underlying distributions of predictor variables sampled with true versus public coordinates did not indicate a significant difference for any species at any extent. Both the public- and true-based models had comparable classification accuracies across extent for each species, with the exception of one species, J. occidentalis. True-based models produced geographic distributions with smaller areas under current and future scenarios. The greatest areal difference occurred in the species with the lowest modeled accuracies (J. occidentalis), and had a forecast distribution which diverged severely. The other species had forecast distributions with similar magnitudes of modeled distribution shifts.},
journal = {Ecosystems},
keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13108765,climate,data-uncertainty,forest-resources,habitat-suitability,modelling-uncertainty,species-distribution,united-states},
lccn = {INRMM-MiD:c-13108765},
number = {1}
}
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C."],"year":2014,"bibtype":"article","biburl":"https://sharefast.me/php/download.php?id=zOUKvA&token=29","bibdata":{"bibtype":"article","type":"article","title":"Using Publicly Available Forest Inventory Data in Climate-Based Models of Tree Species Distribution: Examining Effects of True Versus Altered Location Coordinates","author":[{"propositions":[],"lastnames":["Gibson"],"firstnames":["Jacob"],"suffixes":[]},{"propositions":[],"lastnames":["Moisen"],"firstnames":["Gretchen"],"suffixes":[]},{"propositions":[],"lastnames":["Frescino"],"firstnames":["Tracey"],"suffixes":[]},{"propositions":[],"lastnames":["Edwards"],"firstnames":["Thomas","C."],"suffixes":[]}],"year":"2014","volume":"17","pages":"43–53","issn":"1435-0629","doi":"10.1007/s10021-013-9703-y","abstract":"Species distribution models (SDMs) were built with US Forest Inventory and Analysis (FIA) publicly available plot coordinates, which are altered for plot security purposes, and compared with SDMs built with true plot coordinates. Six species endemic to the western US, including four junipers (Juniperus deppeana var. deppeana, J. monosperma, J. occidentalis, J. osteosperma) and two piñons (Pinus edulis, P. monophylla), were analyzed. The presence-absence models based on current climatic variables were generated over a series of species-specific modeling extents using Random Forests and applied to forecast climatic conditions. The distributions of predictor variables sampled with public coordinates were compared to those sampled with true coordinates using t tests with a Bonferroni adjustment for multiple comparisons. Public- and true-based models were compared using metrics of classification accuracy. The modeled current and forecast distributions were compared in terms of their overall areal agreement and their geographic mean centroids. 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