{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:39:52Z","timestamp":1760243992294,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2009,8,17]],"date-time":"2009-08-17T00:00:00Z","timestamp":1250467200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In this paper we present a framework for modelling potential species distribution (PSD) of balsam fir [bF; Abies balsamea (L.) Mill.] as a function of landscape-level descriptions of: (i) growing degree days (GDD: a temperature related index), (ii) land-surface wetness, (iii) incident photosynthetically active radiation (PAR), and (iv) tree habitat suitability. GDD and land-surface wetness are derived primarily from remote sensing data acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite. PAR is calculated with an existing spatial model of solar radiation. Raster-based calculations of habitat suitability and PSD are obtained by multiplying normalized values of species environmental-response functions (one for each environmental variable) parameterized for balsam fir. As a demonstration of the procedure, we apply the calculations to a high bF-content area in northwest New Brunswick, Canada, at 250-m resolution. Location of medium-to-high habitat suitability values (i.e., &gt;0.50) and actual forests, with &gt;50% bF, matched on average 92% of the time.<\/jats:p>","DOI":"10.3390\/rs1030393","type":"journal-article","created":{"date-parts":[[2009,8,17]],"date-time":"2009-08-17T13:18:20Z","timestamp":1250515100000},"page":"393-407","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Potential Species Distribution of Balsam Fir Based on the Integration of Biophysical Variables Derived with Remote Sensing and Process-Based Methods"],"prefix":"10.3390","volume":"1","author":[{"given":"Quazi K.","family":"Hassan","sequence":"first","affiliation":[{"name":"Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr. NW, Calgary, Alberta, T2N 1N4, Canada"}]},{"given":"Charles P.-A.","family":"Bourque","sequence":"additional","affiliation":[{"name":"Faculty of Forestry and Environmental Management, University of New Brunswick, P.O. Box 44555, Fredericton, New Brunswick, E3B 6C2, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2009,8,17]]},"reference":[{"key":"ref_1","unstructured":"Smith, D.M., Larson, B.C., Kelty, M.J., and Ashton, P.M.S. (1997). The Practice of Silviculture: Applied Forest Ecology, John Willey & Sons. [9th ed.]."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/S0304-3800(02)00205-3","article-title":"Spatial prediction of species distribution: an interface between ecological theory and statistical modeling","volume":"157","author":"Austin","year":"2002","journal-title":"Ecol. 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