In this paper we develop a method to estimate land-surface water content in amostly forest-dominated (humid) and topographically-varied region of eastern Canada. Theapproach is centered on a temperature-vegetation wetness index (TVWI) that uses standard 8-day MODIS-based image composites of land surface temperature (T_S) and surface reflectanceas primary input. In an attempt to improve estimates of TVWI in high elevation areas, terrain-induced variations in T_S are removed by applying grid, digital elevation model-basedcalculations of vertical atmospheric pressure to calculations of surface potential temperature(θS). Here, θ_S corrects T_S to the temperature value to what it would be at mean sea level (i.e.,~101.3 kPa) in a neutral atmosphere. The vegetation component of the TVWI uses 8-daycomposites of surface reflectance in the calculation of normalized difference vegetation index(NDVI) values. TVWI and corresponding wet and dry edges are based on an interpretation ofscatterplots generated by plotting θ_S as a function of NDVI. A comparison of spatially-averaged field measurements of volumetric soil water content (VSWC) and TVWI for the 2003-2005 period revealed that variation with time to both was similar in magnitudes. Growing season, point mean measurements of VSWC and TVWI were 31.0% and 28.8% for 2003, 28.6% and 29.4% for 2004, and 40.0% and 38.4% for 2005, respectively. An evaluation of the long-term spatial distribution of land-surface wetness generated with the new θ_S-NDVI function and a process-based model of soil water content showed a strong relationship (i.e., r² = 95.7%).

This paper presents a pre- and post-harvest comparison of stream temperatures collected in five neighbouring streams (sub-catchments) over a period of five years (1994-1998). The aim of the study was to determine whether land cover changes from clear cutting in areas outside forest buffer zones (applied to streams >0.5 m wide) might contribute to an increase in summer mean stream temperatures in buffered streams downslope by infusion of warmed surface and sub-surface water into the streams. Specific relationships were observed in all five forest streams investigated. To assist in the analysis, several spatially-relevant variables, such as land cover change, mid-summer potential solar radiation, flow accumulation, stream location and slope of the land were determined, in part, from existing aerial photographs, GIS-archived forest inventory data and a digital terrain model of the study area. Spatial calculations of insolation levels for July 15^th were used as an index of mid-summer solar heating across sub-catchments. Analysis indicated that prior to the 1995 harvest, differences in stream temperature could be attributed to (i) topographic position and catchment-to-sun orientation, (ii) the level of cutting that occurred in the upper catchment prior to the start of the study, and (iii) the average slope within harvested areas. Compared to the pre-harvest mean stream temperatures in 1994, mean temperatures in the three streams downslope from the 1995 harvest areas increased by 0.3 to 0.7°C (representing a 4-8% increase; p-value of normalised temperatures <<0.05). The greatest temperature change occurred in the stream that had the greatest proportion of its upper catchment harvested (16.8%), which also had the highest calculated potential solar loading ( ~2749 MJ per stream cell). From the analysis it was determined that the thinning applied to the forest buffer of that stream, with a basal area removal of ~28%, was insufficient to cause significant change in the observed stream temperature. Similar effects were observed following a second harvest in 1997. In general, increases in mean stream temperature coincided with forest harvesting activities outside forest buffers, where conditions promoting stream warming were greatest. In this study, no clear relationship existed between forest buffer strip width (ranging from 30-60 m) and the level of stream warming observed at the monitoring stations. Keywords: terrain attributes, solar radiation, land cover, forest buffers, New Brunswick regulations, spatial modelling, DEM, forest covertypes

Balsam fir (Abies balsamea (L.) Mill) was extensively sampled to investigate the effects of forest management practices, site location, within-crown position, tree component (i.e., stem, foliage, branches and roots), and tree social classes on biomass and carbon (C) partitioning at the individual tree level and across ecological regions. The sites were located in three ecologically distinct forest regions of west-central New Brunswick, Canada. There were no significant differences in %C content of trees across ecological regions or across tree social classes. However, at the individual tree level, significant differences were evident in biomass and C allocation between different parts of the tree, between treatment types (i.e., unmanaged and pre-commercially thinned stands) and between within-crown positions, indicating the need for separate estimates of biomass and C content of tree components to obtain more precise estimates of quantities at the stand level. Calculating stand C content based on constant allocation values, as is commonly done, produced errors of up to 15% compared with the values calculated in this study. Three allometric equations of biomass and C that account for partitioning among different parts of the tree were developed and compared: (1) a third-order polynomial, (2) a modified inverse polynomial and (3) a modified Weibull equation. Diameter at breast height (DBH) was used as the only explanatory variable to describe fresh biomass, dry biomass and C content. All regressions derived showed a high correlation with DBH, with most r² values > 0.95. A comparison of the equation results showed that the modified Weibull equation gave consistent results with the best overall fit and was the simplest of the three equations investigated. The regressions can be used to estimate forest biomass and tree C content at the stand level, given specific information on DBH.

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., >0.50) and actual forests, with >50% bF, matched on average 92% of the time.

Mapping landscape variation in tree species richness (SR) is essential to the long term management and conservation of forest ecosystems. The current study examines the prospect of mapping field assessments of SR in a high-elevation, deciduous forest in northern Iran as a function of 16 biophysical variables representative of the area’s unique physiography, including topography and coastal placement, biophysical environment, and forests. Basic to this study is the development of moderate-resolution biophysical surfaces and associated plot-estimates for 202 permanent sampling plots. The biophysical variables include: (i) three topographic variables generated directly from the area’s digital terrain model; (ii) four ecophysiologically-relevant variables derived from process models or from first principles; and (iii) seven variables of Landsat-8-acquired surface reflectance and two, of surface radiance. With symbolic regression, it was shown that only four of the 16 variables were needed to explain 85% of observed plot-level variation in SR (i.e., wind velocity, surface reflectance of blue light, and topographic wetness indices representative of soil water content), yielding mean-absolute and root-mean-squared error of 0.50 and 0.78, respectively. Overall, localised calculations of wind velocity and surface reflectance of blue light explained about 63% of observed variation in SR, with wind velocity accounting for 51% of that variation. The remaining 22% was explained by linear combinations of soil-water-related topographic indices and associated thresholds. In general, SR and diversity tended to be greatest for plots dominated by Carpinus betulus (involving ≥ 33% of all trees in a plot), than by Fagus orientalis (median difference of one species). This study provides a significant step towards describing landscape variation in SR as a function of modelled and satellite-based information and symbolic regression. Methods in this study are sufficiently general to be applicable to the characterisation of SR in other forested regions of the world, providing plot-scale data are available for model generation.