Forest Structural Attributes Research Articles

Characterizing boreal forest wildfire with multi-temporal Landsat and LIDAR data

Wildfire is an important disturbance agent in Canada's boreal forest. Optical remotely sensed imagery (e.g., Landsat TM/ETM+), is well suited for capturing horizontally distributed forest conditions, structure, and change, while Light Detection and Ranging (LIDAR) data are more appropriate for capturing vertically distributed elements of forest structure and change. The integration of optical remotely sensed imagery and LIDAR data provides improved opportunities to characterize post-fire conditions. The objective of this study is to compare changes in forest structure, as measured with a discrete return profiling LIDAR, to post-fire conditions, as measured with remotely sensed data. Our research is focused on a boreal forest fire that occurred in May 2002 in Alberta, Canada. The Normalized Burn Ratio (NBR), the differenced NBR (dNBR), and the relative dNBR (RdNBR) were calculated from two dates of Landsat data (August 2001 and September 2002). Forest structural attributes were derived from two spatially coincident discrete return LIDAR profiles acquired in September 1997 and 2002 respectively. Image segmentation was used to produce homogeneous spatial patches analogous to forest stands, with analysis conducted at this patch level. In this study area, which was relatively homogenous and dominated by open forest, no statistically significant relationships were found between pre-fire forest structure and post-fire conditions ( r < 0.5; p > 0.05). Post-fire forest structure and absolute and relative changes in forest structure were strongly correlated to post-fire conditions ( r ranging from − 0.507 to 0.712; p < 0.0001). Measures of vegetation fill (VF) (LIDAR capture of cross-sectional vegetation amount), post-fire and absolute change in crown closure (CC), and relative change in average canopy height, were most useful for characterizing post-fire conditions. Forest structural attributes generated from the post-fire LIDAR data were most strongly correlated to post-fire NBR, while dNBR and RdNBR had stronger correlations with absolute and relative changes in the forest structural attributes. Absolute and relative changes in VF and changes in CC had the strongest positive correlations with respect to dNBR and RdNBR, ranging from 0.514 to 0.715 ( p < 0.05). Measures of average inter-tree distance and volume were not strongly correlated to post-fire NBR, dNBR, or RdNBR. No marked differences were found in the strength or significance of correlations between post-fire structure and the post-fire NBR, dNBR, RdNBR, indicating that for the conditions present in this study area all three burn severity indices captured post-fire conditions in a similar manner. Finally, the relationship between post-fire forest structure and post-fire condition was strongest for dense forests (> 60% crown closure) compared to open (26–60%) and sparse forests (10–25%). Forest structure information provided by LIDAR is useful for characterizing post-fire conditions and burn induced structural change, and will complement other attributes such as vegetation type and moisture, topography, and long-term weather patterns, all of which will also influence variations in post-fire conditions.

Mapping beech (Fagus sylvatica L.) forest structure with airborne hyperspectral imagery

Estimating forest structural attributes using multispectral remote sensing is challenging because of the saturation of multispectral indices at high canopy cover. The objective of this study was to assess the utility of hyperspectral data in estimating and mapping forest structural parameters including mean diameter-at-breast height (DBH), mean tree height and tree density of a closed canopy beech forest (Fagus sylvatica L.). Airborne HyMap images and data on forest structural attributes were collected from the Majella National Park, Italy in July 2004. The predictive performances of vegetation indices (VI) derived from all possible two-band combinations (VI(i,j)=(Ri−Rj)/(Ri+Rj), where Ri and Rj=reflectance in any two bands) were evaluated using calibration (n=33) and test (n=20) data sets. The potential of partial least squares (PLS) regression, a multivariate technique involving several bands was also assessed. New VIs based on the contrast between reflectance in the red-edge shoulder (756–820nm) and the water absorption feature centred at 1200nm (1172–1320nm) were found to show higher correlations with the forest structural parameters than standard VIs derived from NIR and visible reflectance (i.e. the normalised difference vegetation index, NDVI). PLS regression showed a slight improvement in estimating the beech forest structural attributes (prediction errors of 27.6%, 32.6% and 46.4% for mean DBH, height and tree density, respectively) compared to VIs using linear regression models (prediction errors of 27.8%, 35.8% and 48.3% for mean DBH, height and tree density, respectively). Mean DBH was the best predicted variable among the stand parameters (calibration R2=0.62 for an exponential model fit and standard error of prediction=5.12cm, i.e. 25% of the mean). The predicted map of mean DBH revealed high heterogeneity in the beech forest structure in the study area. The spatial variability of mean DBH occurs at less than 450m. The DBH map could be useful to forest management in many ways, e.g. thinning of coppice to promote diameter growth, to assess the effects of management on forest structure or to detect changes in the forest structure caused by anthropogenic and natural factors.

Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA

Quantifying forest structure is important for sustainable forest management, as it relates to a wide variety of ecosystem processes and services. Lidar data have proven particularly useful for measuring or estimating a suite of forest structural attributes such as canopy height, basal area, and LAI. However, the potential of this technology to characterize forest succession remains largely untested. The objective of this study was to evaluate the use of lidar data for characterizing forest successional stages across a structurally diverse, mixed-species forest in Northern Idaho. We used a variety of lidar-derived metrics in conjunction with an algorithmic modeling procedure (Random Forests) to classify six stages of three-dimensional forest development and achieved an overall accuracy > 95%. The algorithmic model presented herein developed ecologically meaningful classifications based upon lidar metrics quantifying mean vegetation height and canopy cover, among others. This study highlights the utility of lidar data for accurately classifying forest succession in complex, mixed coniferous forests; but further research should be conducted to classify forest successional stages across different forests types. The techniques presented herein can be easily applied to other areas. Furthermore, the final classification map represents a significant advancement for forest succession modeling and wildlife habitat assessment.

Hyperspectral remote detection of niche partitioning among canopy trees driven by blowdown gap disturbances in the Central Amazon

Advanced recruitment and neutral processes play important roles in determining tree species composition in tropical forest canopy gaps, with few gaps experiencing clear secondary successional processes. However, most studies are limited to the relatively limited spatial scales provided by forest inventory plots, and investigations over the entire range of gap size are needed to better understand how ecological processes vary with tree mortality events. This study employed a landscape approach to test the hypothesis that tree species composition and forest structural attributes differ between large blowdown gaps and relatively undisturbed primary forest. Spectral mixture analysis on hyperspectral satellite imagery was employed to direct field sampling to widely distributed sites, and blowdown plots were compared with undisturbed primary forest plots. Tree species composition and forest structural attributes differed markedly between gap and non-gap sites, providing evidence of niche partitioning in response to disturbance across the region. Large gaps were dominated by classic Neotropical pioneer genera such as Cecropia and Vismia, and average tree size was significantly smaller. Mean wood density of trees recovering in large gaps (0.55 g cm(-3)) was significantly lower than in primary forest plots (0.71 g cm(-3)), a difference similar to that found when comparing less dynamic (i.e., tree recruitment, growth, and mortality) Central Amazon forests with more dynamic Western Amazon forests. Based on results, we hypothesize that the importance of neutral processes weaken, and niche processes strengthen, in determining community assembly along a gradient in gap size and tree mortality intensity. Over evolutionary time scales, pervasive dispersal among colonizers could result in the loss of tree diversity in the pioneer guild through competitive exclusion. Results also underscore the importance of considering disturbance processes across the landscape when addressing forest carbon balance.

Estimating plot-level forest structural attributes using high spectral resolution ASTER satellite data in even-aged Eucalyptus plantations in southern KwaZulu-Natal, South Africa

This study assessed the suitability of both visible and shortwave infrared of ASTER reflectance bands and various vegetation indices for estimating forest structural attributes of Eucalyptus species. The study was conducted in even-aged monoculture plantations of E. grandis and E. nitens in the southern KwaZulu-Natal Midlands of South Africa. Empirical relationships between forest structural attributes, i.e. stems per hectare (SPHA), diameter at breast height (DBH), mean tree height (MTH), basal area and volume, and ASTER data were derived using correlation and canonical correlation analysis (CCA). The results indicated weak relationships between the studied forest structural attributes and ASTER data. In the younger plantation stands (4–6 years) the adjusted R 2 values from CCA regression for SPHA, DBH, MTH, basal area and volume were 54.2, 63.5, 33.8, 25.4 and 30.3, respectively. The adjusted R 2 values in the mature stands (7–9 years) were distinctly weaker with values of 50.7, 55.8, 25.1, 20.2 and 27.3 for SPHA, DBH, MTH, basal area and volume, respectively. The results imply that ASTER satellite data are not applicable to forest structural attribute estimation in commercially managed forest stands.

Mapping land cover and estimating forest structure using satellite imagery and coarse resolution lidar in the Virgin Islands

Current information on land cover, forest type and forest structure for the Virgin Islands is critical to land managers and researchers for accurate forest inventory and ecological monitoring. In this study, we use cloud free image mosaics of panchromatic sharpened Landsat ETM+ images and decision tree classification software to map land cover and forest type for the Virgin Islands, illustrating a low cost, repeatable mapping approach. Also, we test if coarse-resolution discrete lidar data that are often collected in conjunction with digital orthophotos are useful for mapping forest structural attributes. This approach addresses the factors that affect vegetation distribution and structure by testing if environmental variables can improve regression models of forest height and biomass derived from lidar data. The overall accuracy of the 29 forest and non-forest classes is 72%, while most the forest types are classified with greater than 70% accuracy. Due to the large point spacing of this lidar dataset, it is most appropriate for height measurements of dominant and co-dominant trees (R2 = 72%) due to its inability to accurately represent forest understory. Above ground biomass per hectare is estimated by its direct relationship with plot canopy height (R2 = 0.72%).

Forest structure, productivity and soil properties in a subtropical evergreen broad-leaved forest in Okinawa, Japan

Structure, species composition, and soil properties of a subtropical evergreen broad-leaved forest in Okinawa, Japan, were examined by establishment of plots at thirty sites. The forest was characterized by a relatively low canopy and a large number of small-diameter trees. Mean canopy height for this forest was 10 m and stands contained an average of 5400 stems·ha−1 (≧3.0 cm DBH); 64% of those stems were smaller than 10 cm DBH. The total basal area was 54.4 m 2·ha−1, of which Castanopsis sieboldii contributed 48%. The forest showed high species diversity of trees. 80 tree species (≧ 3.0 cm DBH) from 31 families was identified in the thirty sampling plots. C. sieboldii and Schima wallichii were the dominant and subdominant species in terms of importance value. The mean tree species diversity indices for the plots were, 3.36 for Diversity index (H′), 0.71 for Equitability index (J′) and 4.72 for Species richness index (S′), all of which strongly declined with the increase of importance value of the dominant, C. sieboldii. Measures of soil nutrients indicated low fertility, extreme heterogeneity and possible Al toxicity. Regression analysis showed that stem density and the dominant tree height were significantly correlated with soil pH. There was a significant positive relationship between species diversity index and soil exchangeable K+, Ca2+, and Ca2+/Al3+ ratio (all p values <0.001) and a negative relationship with N, C and P. The results suggest that soil property is a major factor influencing forest composition and structure within the subtropical forest in Okinawa.

Scaling-based forest structural change detection using an inverted geometric-optical model in the Three Gorges region of China

We use the Li-Strahler geometric-optical model combined with a scaling-based approach to detect forest structural changes in the Three Gorges region of China. The physical-based Li-Strahler model can be inverted to retrieve forest structural properties. One of the main input variables for the inverted model is the fractional component of sunlit background, which is calculated by using pure reflectance spectra (endmembers) of surface components. In this study, we extract these endmembers from moderate spatial resolution MODIS data using two scaling-based methods (namely, a regional based linear unmixing and a purest-pixel approach) relying on corresponding high spatial resolution Landsat TM images. Then, the forest structural property crown closure (CC) is estimated by inverting the Li-Strahler model based on the extracted endmembers. Changes in CC are mapped using MODIS mosaics dated 2002 and 2004 for the whole Three Gorges region. Validation of the estimated CC using 25 sample sites indicates that the regional scaling-based endmembers extracted using linear unmixing are more suitable to be used in combination with the inverted Li-Strahler model for monitoring the forest CC than the purest-pixel approach, and results in significantly better estimates in both years ( R 2 2002 = 0.614, RMSE 2002 = 6%, R 2 2004 = 0.631 and RMSE 2004 = 5.2%). A change detection map of the model derived CC in 2002 and 2004 shows a decrease in CC in the eastern counties of the Three Gorges region located close to the Three Gorges Dam. An increase in CC has been observed in other counties of the Three Gorges region, implying a preliminary positive feedback on certain policy measures taken safeguarding forest structure.

Legacy of Charcoaling in a Western Highland Rim Forest in Tennessee

ABSTRACT Forests of the Western Highland Rim were heavily influenced by the iron industry during the 19th and 20th centuries. The production of iron required large amounts of charcoal. Timber was cut, burned in hearths to produce charcoal and then the charcoal was transported to local furnaces and forges. The goal of our study was to document the lasting effects of charcoal production on soil characteristics, species composition and stand structure for a forest on the Western Highland Rim in Tennessee. Fires used in hearths to produce charcoal were intense, spatially concentrated events that modified soil characteristics differently than typical surface fires. We hypothesized there would still be a footprint of the charcoal making process evidenced by systematic differences in forest composition and structural attributes that could be related to soil properties. Results show there were significant differences in some soil traits between charcoal hearths and surrounding sites. However, differing soil condi...

Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

ABSTRACTWe developed an automated tree crown analysis algorithm using 1‐m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75° S, 48.37° W) in the eastern Amazon, and then compared with forest stand data at Tapajos National Forest (3.08° S, 54.94° W) in the central Amazon. The average remotely sensed crown width (mean ± SE) was 12.7 ± 0.1 m (range: 2.0–34.0 m) and frequency of trees was 76.6 trees/ha at Cauaxi. At Tapajos, remotely sensed crown width was 13.1 ± 0.1 m (range: 2.0–38.0 m) and frequency of trees was 76.4 trees/ha. At both Cauaxi and Tapajos, the remotely sensed average crown widths were within 3 percent of the crown widths derived from field measurements, although crown distributions showed significant differences between field‐measured and automated methods. We used the remote sensing algorithm to estimate crown dimensions and forest structural properties in 51 forest stands (1 km2) throughout the Brazilian Amazon. The estimated crown widths, tree diameters (dbh), and stem frequencies differed widely among sites, while estimated biomass was similar among most sites. Sources of observed errors included an inability to detect understory crowns and to separate adjacent, intermingled crowns. Nonetheless, our technique can serve to provide information about structural characteristics of large areas of unsurveyed forest throughout Amazonia.

Regenerating boreal forest structure estimation using SPOT‐5 pan‐sharpened imagery

Forested stand structure is an important target variable within the fields of wildlife ecology. Remote sensing has often been suggested as a viable alternative to time consuming field and aerial investigations to determine forest structural attributes. In this study, 44 stands of recently harvested, regenerating, and old growth forest within the Foothills Model Forest in west‐central Alberta were selected to test the ability of pan‐sharpened SPOT‐5 spectral response to classify stand structure. For each stand, a Structural Complexity Index (SCI) was calculated from field data using principal components analysis. To complement the spectral response data set and further increase accuracy, the normalized difference moisture index (NDMI) and three window sizes (5×5, 11×11, and 25×25) of first‐ (mean and standard deviation) and second‐order (homogeneity, entropy, contrast, and correlation) textural measures were calculated over the pan‐sharpened image. Stepwise multivariate regression analysis was used to determine the best explanatory model of the SCI using the spectral and textural data. The NDMI, first‐order standard deviation and second‐order correlation texture measures were better able to explain differences in SCI among the 44 forest stands (r2 = 0.79). The most appropriate window size for the texture measures was 5×5 indicating that this is a measure only detectable at a very high spatial resolution. The resulting classified SCI values were comparable to the actual field level SCI (r2 = 0.74, p = 0.01) and were limited by the strong variability within stands. Future research may find this measure useful either as a separate parameter or as an indicator of forest age for use in wildlife habitat modelling.

A LiDAR-derived canopy density model for tree stem and crown mapping in Australian forests

The retrieval of tree and forest structural attributes from Light Detection and Ranging (LiDAR) data has focused largely on utilising canopy height models, but these have proved only partially useful for mapping and attributing stems in complex, multi-layered forests. As a complementary approach, this paper presents a new index, termed the Height-Scaled Crown Openness Index (HSCOI), which provides a quantitative measure of the relative penetration of LiDAR pulses into the canopy. The HSCOI was developed from small footprint discrete return LiDAR data acquired over mixed species woodlands and open forests near Injune, Queensland, Australia, and allowed individual trees to be located (including those in the sub-canopy) and attributed with height using relationships ( r 2 = 0.81, RMSE = 1.85 m, n = 115; 4 outliers removed) established with field data. A threshold contour of the HSCOI surface that encompassed ∼ 90% of LiDAR vegetation returns also facilitated mapping of forest areas, delineation of tree crowns and clusters, and estimation of canopy cover. At a stand level, tree density compared well with field measurements ( r 2 = 0.82, RMSE = 133 stems ha − 1 , n = 30), with the most consistent results observed for stem densities ≤ 700 stems ha − 1 . By combining information extracted from both the HSCOI and the canopy height model, predominant stem height ( r 2 = 0.91, RMSE = 0.77 m, n = 30), crown cover ( r 2 = 0.78, RMSE = 9.25%, n = 30), and Foliage & Branch Projective Cover (FBPC; r 2 = 0.89, RMSE = 5.49%, n = 30) were estimated to levels sufficient for inventory of woodland and open forest structural types. When the approach was applied to forests in north east Victoria, stem density and crown cover were reliably estimated for forests with a structure similar to those observed in Queensland, but less so for forests of greater height and canopy closure.

MATURE AND OLD-GROWTH RIPARIAN FORESTS: STRUCTURE, DYNAMICS, AND EFFECTS ON ADIRONDACK STREAM HABITATS

Riparian forests regulate linkages between terrestrial and aquatic ecosystems, yet relationships among riparian forest development, stand structure, and stream habitats are poorly understood in many temperate deciduous forest systems. Our research has (1) described structural attributes associated with old-growth riparian forests and (2) assessed linkages between these characteristics and in-stream habitat structure. The 19 study sites were located along predominantly first- and second-order streams in northern hardwood-conifer forests in the Adirondack Mountains of New York (U.S.A.). Sites were classified as mature forest (6 sites), mature with remnant old-growth trees (3 sites), and old-growth (10 sites). Forest-structure attributes were measured over stream channels and at varying distances from each bank. In-stream habitat features such as large woody debris (LWD), pools, and boulders were measured in each stream reach. Forest structure was examined in relation to stand age using multivariate techniques, ANOVA, and linear regression. We investigated linkages between forest structure and stream characteristics using similar methods, preceded by information-theoretic modeling (AIC). Old-growth riparian forest structure is more complex than that found in mature forests and exhibits significantly greater accumulations of aboveground tree biomass, both living and dead. In-stream LWD volumes were significantly (alpha = 0.05) greater at old-growth sites (200 m3/ha) compared to mature sites (34 m3/ha) and were strongly related to the basal area of adjacent forests. In-stream large-log densities correlated strongly with debris-dam densities. AIC models that included large-log density, debris-dam density, boulder density, and bankfull width had the most support for predicting pool density. There were higher proportions of LWD-formed pools relative to boulder-formed pools at old-growth sites as compared to mature sites. Old-growth riparian forests provide in-stream habitat features that have not been widely recognized in eastern North America, representing a potential benefit from late-successional riparian forest management and conservation. Riparian management practices (including buffer delineation and restorative silvicultural approaches) that emphasize development and maintenance of late-successional characteristics are recommended where the associated in-stream effects are desired.

Influence of Forest Vegetation Structure on Avian Community Composition in West-Central Idaho

Abstract Locally derived information is needed if management guidelines intended to improve wildlife habitat are to be relevant, reliable, and applicable. Within the Intermountain West, few studies have examined habitat relationships of forest songbirds in mixed-conifer forests. During 1996–1997, we studied breeding bird communities in a mixed-conifer forest in west-central Idaho, USA, to describe how relative avian abundance was related to forest structure. Our study objectives were to 1) describe bird use of 3 distinct forest age-classes, 2) identify groups of species that expressed similar relationships with forest structural attributes, and 3) model species-specific bird–habitat relationships. We sampled 46 study sites (forest stands) classified into 1 of 3 common “vegetation growth stages” (seral stages): 1) shrub/seedling/sapling (n = 15 stands), 2) small tree (n = 16 stands), and 3) old growth (n = 15 stands). In each stand we surveyed breeding birds using fixed-radius point counts and measured for...

Improving the establishment submodel of a forest patch model to assess the long-term protective effect of mountain forests

Simulation models such as forest patch models can be used to forecast the development of forest structural attributes over time. However, predictions of such models with respect to the impact of forest dynamics on the long-term protective effect of mountain forests may be of limited accuracy where tree regeneration is simulated with little detail. For this reason, we improved the establishment submodel of the ForClim forest patch model by implementing a more detailed representation of tree regeneration. Our refined submodel included canopy shading and ungulate browsing, two important constraints to sapling growth in mountain forests. To compare the old and the new establishment submodel of ForClim, we simulated the successional dynamics of the Stotzigwald protection forest in the Swiss Alps over a 60-year period. This forest provides protection for an important traffic route, but currently contains an alarmingly low density of tree regeneration. The comparison yielded a significantly longer regeneration period for the new model version, bringing the simulations into closer agreement with the known slow stand dynamics of mountain forests. In addition, the new model version was applied to forecast the future ability of the Stotzigwald forest to buffer the valley below from rockfall disturbance. Two scenarios were simulated: (1) canopy shading but no browsing impact, and (2) canopy shading and high browsing impact. The simulated stand structures were then compared to stand structure targets for rockfall protection, in order to assess their long-term protective effects. Under both scenarios, the initial sparse level of tree regeneration affected the long-term protective effect of the forest, which considerably declined during the first 40 years. In the complete absence of browsing, the density of small trees increased slightly after 60 years, raising hope for an eventual recovery of the protective effect. In the scenario that included browsing, however, the density of small trees remained at very low levels. With our improved establishment submodel, we provide an enhanced tool for studying the impacts of structural dynamics on the long-term protective effect of mountain forests. For certain purposes, it is important that predictive models of forest dynamics adequately represent critical processes for tree regeneration, such as sapling responses to low light levels and high browsing pressure.

Rain Forest Islands in the Chilean Semiarid Region: Fog-dependency, Ecosystem Persistence and Tree Regeneration

Tree presence in semiarid ecosystems is generally constrained by insufficient annual rainfall. However, in semiarid Chile, rainforest patches dominated by Aextoxicon punctatum are unexpectedly found on coastal mountaintops (450–600 m) at 30°S, surrounded by a xerophytic vegetation matrix that receives only 147 mm of annual precipitation. It has been proposed that these forests persist as a result of fog-water inputs. If so, then because fog-water deposition is spatially heterogeneous and shows strong edge effects, the potential environmental gradient created by the direction of fog input should determine forest structure and tree regeneration patterns. To investigate this hypothesis, we measured fog inputs, forest structural attributes (age and size distribution, basal area, and coarse woody debris), and tree regeneration in three different habitats: the windward edges (WE), leeward edges (LE), and the interior (center) of rainforest patches varying in area from 0.2 to 22 ha. Mean fog-water input was estimated from passive collectors over 1 year in WE and LE of patches. Tree regeneration was greater in the WE and forest interior (FI) and decreased toward the LE of patches, following a marked pattern of decline in fog inputs. Older trees and coarse woody debris were concentrated in the FI and LE of patches. Tree regeneration and patch structure appear to be largely controlled by fog-input direction and edge effects. We propose that forest patches may be slowly growing toward the incoming fog edge, while dying at the opposite edge.

Seasonal fire effects on mixed-conifer forest structure and ponderosa pine resin properties

This study examined the effects of spring and fall restoration burning in an old-growth mixed-conifer – ponderosa pine (Pinus ponderosa Dougl. ex P. &amp; C. Laws.) forest in southern Oregon. Variables measured include fuel loads, forest structure indices, mortality of large ponderosa pines, and pine resin defenses. One year after treatment, reductions in surface fuel loads and changes to forest structure parameters suggested that burning treatments could meet restoration objectives, with fall burns being somewhat more effective than spring burns. However, mortality of pre settlement pines was significantly higher in fall burns than in spring burns, and both were higher than in unburned controls. Bark beetles (Coleoptera: Scolytidae) were important mortality agents within 2 years after burning. Resin defenses (pressure and flow) were variable over the 2 years of postburn study but showed no evidence of decrease in burned trees; rather, resin defenses were significantly higher in burned trees than in controls at several measurement dates. While increased beetle attacks have previously been documented following burning, there has been much less research on resin responses to fire. These findings suggest that current models of beetle–host interactions do not properly explain the effects of prescribed fire in ponderosa pine forests.

Controls and Reference Conditions in Forestry: The Role of Old-Growth and Retrospective Studies

Abstract Forest stands that experience only natural disturbance can serve as controls to provide a scientific basis for comparison with harvested forests to help determine when harvesting has been done in a sustainable manner. Primary stands can serve as references for silvicultural trials that attempt to mimic the primary forest structural attributes on shorter time scales of a few decades. At the landscape scale, retrospective techniques can be used to examine proportion and variation in proportion of stands among structural and successional stages expected under the natural disturbance regime. These analyses are referred to as range of natural variation and serve as landscape-scale reference conditions for comparison with the managed forest landscape.

Ecosystem structure, nutrient dynamics, and hydrologic relationships in tree islands of the southern Everglades, Florida, USA

Tree islands are an important structural component of many graminoid-dominated wetlands because they increase ecological complexity in the landscape. Tree island area has been drastically reduced with hydrologic modifications within the Everglades ecosystem, yet still little is known about the ecosystem ecology of Everglades tree islands. As part of an ongoing study to investigate the effects of hydrologic restoration on short hydroperiod marshes of the southern Everglades, we report an ecosystem characterization of seasonally flooded tree islands relative to locations described by variation in freshwater flow (i.e. locally enhanced freshwater flow by levee removal). We quantified: (1) forest structure, litterfall production, nutrient utilization, soil dynamics, and hydrologic properties of six tree islands and (2) soil and surface water physico-chemical properties of adjacent marshes. Tree islands efficiently utilized both phosphorus and nitrogen, but indices of nutrient-use efficiency indicated stronger P than N limitation. Tree islands were distinct in structure and biogeochemical properties from the surrounding marsh, maintaining higher organically bound P and N, but lower inorganic N. Annual variation resulting in increased hydroperiod and lower wet season water levels not only increased nitrogen use by tree species and decreased N:P values of the dominant plant species ( Chrysobalanus icaco), but also increased soil pH and decreased soil temperature. When compared with other forested wetlands, these Everglades tree islands were among the most nutrient efficient, likely a function of nutrient immobilization in soils and the calcium carbonate bedrock. Tree islands of our study area are defined by: (1) unique biogeochemical properties when compared with adjacent short hydroperiod marshes and other forested wetlands and (2) an intricate relationship with marsh hydrology. As such, they may play an important and disproportionate role in nutrient and carbon cycling in Everglades wetlands. With the loss of tree islands that has occurred with the degradation of the Everglades system, these landscape processes may have been altered. With this baseline dataset, we have established a long-term ecosystem-scale experiment to follow the ecosystem trajectory of seasonally flooded tree islands in response to hydrologic restoration of the southern Everglades.

Ecosystem Structure throughout the Brazilian Amazon from Landsat Observations and Automated Spectral Unmixing

Abstract The Brazilian Amazon forest and cerrado savanna encompasses a region of enormous ecological, climatic, and land-use variation. Satellite remote sensing is the only tractable means to measure the biophysical attributes of vegetation throughout this region, but coarse-resolution sensors cannot resolve the details of forest structure and land-cover change deemed critical to many land-use, ecological, and conservation-oriented studies. The Carnegie Landsat Analysis System (CLAS) was developed for studies of forest and savanna structural attributes using widely available Landsat Enhanced Thematic Mapper Plus (ETM+) satellite data and advanced methods in automated spectral mixture analysis. The methodology of the CLAS approach is presented along with a study of its sensitivity to atmospheric correction errors. CLAS is then applied to a mosaic of Landsat images spanning the years 1999–2001 as a proof of concept and capability for large-scale, very high resolution mapping of the Amazon and bordering cerrado savanna. A total of 197 images were analyzed for fractional photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare substrate covers using a probabilistic spectral mixture model. Results from areas without significant land use, clouds, cloud shadows, and water bodies were compiled by the Brazilian state and vegetation class to understand the baseline structural typology of forests and savannas using this new system. Conversion of the satellite-derived PV data to woody canopy gap fraction was made to highlight major differences by vegetation and ecosystem classes. The results indicate important differences in fractional photosynthetic cover and canopy gap fraction that can now be accounted for in future studies of land-cover change, ecological variability, and biogeochemical processes across the Amazon and bordering cerrado regions of Brazil.