Forest Tree Height Research Articles

Total belowground carbon flux in subalpine forests is related to leaf area index, soil nitrogen, and tree height

AbstractIn forests, total belowground carbon (C) flux (TBCF) is a large component of the C budget and represents a critical pathway for delivery of plant C to soil. Reducing uncertainty around regional estimates of forest C cycling may be aided by incorporating knowledge of controls over soil respiration and TBCF. Photosynthesis, and presumably TBCF, declines with advancing tree size and age, and photosynthesis increases yet C partitioning to TBCF decreases in response to high soil fertility. We hypothesized that these causal relationships would result in predictable patterns of TBCF, and partitioning of C to TBCF, with natural variability in leaf area index (LAI), soil nitrogen (N), and tree height in subalpine forests in the Rocky Mountains, USA. Using three consecutive years of soil respiration data collected from 22 0.38‐ha locations across three 1‐km2 subalpine forested landscapes, we tested three hypotheses: (1) annual soil respiration and TBCF will show a hump‐shaped relationship with LAI; (2) variability in TBCF unexplained by LAI will be related to soil nitrogen (N); and (3) partitioning of C to TBCF (relative to woody growth) will decline with increasing soil N and tree height. We found partial support for Hypothesis 1 and full support for Hypotheses 2 and 3. TBCF, but not soil respiration, was explained by LAI and soil N patterns (r2 = 0.49), and the ratio of annual TBCF to TBCF plus aboveground net primary productivity (ANPP) was related to soil N and tree height (r2 = 0.72). Thus, forest C partitioning to TBCF can vary even within the same forest type and region, and approaches that assume a constant fraction of TBCF relative to ANPP may be missing some of this variability. These relationships can aid with estimates of forest soil respiration and TBCF across landscapes, using spatially explicit forest data such as national inventories or remotely sensed data products.

Abiotic Controls on Macroscale Variations of Humid Tropical Forest Height

Spatial variation of tropical forest tree height is a key indicator of ecological processes associated with forest growth and carbon dynamics. Here we examine the macroscale variations of tree height of humid tropical forests across three continents and quantify the climate and edaphic controls on these variations. Forest tree heights are systematically sampled across global humid tropical forests with more than 2.5 million measurements from Geoscience Laser Altimeter System (GLAS) satellite observations (2004–2008). We used top canopy height (TCH) of GLAS footprints to grid the statistical mean and variance and the 90 percentile height of samples at 0.5 degrees to capture the regional variability of average and large trees globally. We used the spatial regression method (spatial eigenvector mapping-SEVM) to evaluate the contributions of climate, soil and topography in explaining and predicting the regional variations of forest height. Statistical models suggest that climate, soil, topography, and spatial contextual information together can explain more than 60% of the observed forest height variation, while climate and soil jointly explain 30% of the height variations. Soil basics, including physical compositions such as clay and sand contents, chemical properties such as PH values and cation-exchange capacity, as well as biological variables such as the depth of organic matter, all present independent but statistically significant relationships to forest height across three continents. We found significant relations between the precipitation and tree height with shorter trees on the average in areas of higher annual water stress, and large trees occurring in areas with low stress and higher annual precipitation but with significant differences across the continents. Our results confirm other landscape and regional studies by showing that soil fertility, topography and climate may jointly control a significant variation of forest height and influencing patterns of aboveground biomass stocks and dynamics. Other factors such as biotic and disturbance regimes, not included in this study, may have less influence on regional variations but strongly mediate landscape and small-scale forest structure and dynamics.

Short-term response of Cladonia lichen communities to logging and fire in boreal forests

Fire is the major disturbance agent in boreal forests that initiates forest regeneration and succession, and plays a major role in determining the composition of terricolous lichen communities. In recent decades however, logging has become an important disturbance agent in boreal forests. In this context, growing concerns about logging effects on endangered species such as woodland caribou (Rangifer tarandus caribou) has emerged and drawn attention on how reindeer lichens (i.e. Cladonia arbuscula, Cladonia mitis, Cladonia rangiferina, Cladonia stellaris, and Cladonia stygia) respond to logging and fire given their importance as winter forage for caribou. We compared critical lichen habitat factors (i.e., forest floor thickness, tree height, and canopy closure) between fire and logged sites and evaluated how Cladonia lichen species richness, biomass, and ground cover were related to these habitat factors in the first decades following disturbance. We found no significant differences in habitat factors and no significant differences in lichen species richness or ground cover between logged and fire sites. However, Cladonia lichen biomass was significantly higher following logging. These results support the hypothesis that Cladonia lichens can persist following logging and suggest that forestry practices that include in their toolbox winter harvesting or machinery traffic restricted to specific trails are likely to preserve undisturbed forest floor habitat conditions with source populations of lichens.

Bioclimatic envelope models predict a decrease in tropical forest carbon stocks with climate change in Madagascar

Summary Recent studies have underlined the importance of climatic variables in determining tree height and biomass in tropical forests. Nonetheless, the effects of climate on tropical forest carbon stocks remain uncertain. In particular, the application of process‐based dynamic global vegetation models has led to contrasting conclusions regarding the potential impact of climate change on tropical forest carbon storage. Using a correlative approach based on a bioclimatic envelope model and data from 1771 forest plots inventoried during the period 1996–2013 in Madagascar over a large climatic gradient, we show that temperature seasonality, annual precipitation and mean annual temperature are key variables in determining forest above‐ground carbon density. Taking into account the explicative climate variables, we obtained an accurate (R2 = 70% and RMSE = 40 Mg ha−1) forest carbon map for Madagascar at 250 m resolution for the year 2010. This national map was more accurate than previously published global carbon maps (R2 ≤ 26% and RMSE ≥ 63 Mg ha−1). Combining our model with the climatic projections for Madagascar from 7 IPCC CMIP5 global climate models following the RCP 8.5, we forecast an average forest carbon stock loss of 17% (range: 7–24%) by the year 2080. For comparison, a spatially homogeneous deforestation of 0.5% per year on the same period would lead to a loss of 30% of the forest carbon stock. Synthesis. Our study shows that climate change is likely to induce a decrease in tropical forest carbon stocks. This loss could be due to a decrease in the average tree size and to shifts in tree species distribution, with the selection of small‐statured species. In Madagascar, climate‐induced carbon emissions might be, at least, of the same order of magnitude as emissions associated with anthropogenic deforestation.

Allometric scaling theory-based maximum forest tree height and biomass estimation in the Three Gorges reservoir region using multi-source remote-sensing data

ABSTRACTMost terrestrial carbon is stored in forest biomass, which plays an important role in local, regional, and global climate change. Monitoring of forests and their status, and accurate estimation of forest biomass are important in mitigating the impacts of climate change. Empirical models developed using remote-sensing and field-measured forest data are commonly used to estimate forest biomass. In the present study, we used a mechanistic model to estimate height and biomass in the Three Gorges reservoir region (China) based on the allometric scale and resource limits (ASRL) model. The forests in the Three Gorges reservoir region are important and unique in view of the vertical distribution of vegetation and mixed needleleaf. Detailed information about the forest in this region is available from the Geoscience Laser Altimeter System (GLAS) and field measurements from 714 forest plots. The ASRL model parameters were adjusted using GLAS-derived forest tree height to reduce the deviation between modelled and observed forest height. The predicted maximum forest tree height from the optimized ASRL model was compared to measured tree heights, and a good correlation (R2 = 0.566) was found. The allometric scale function between forest height and diameter at breast height (DBH) is developed and the maximum forest tree height from the optimized ASRL model transferred to DBH. Moreover, the forest biomass was estimated from DBH according to the allometric scale function that was determined using DBH and biomass data. The results of maximum forest biomass using the ASRL model and the allometric scale function show a good accuracy (R2 = 0.887) in the Three Gorges reservoir region. Here, we present the forest biomass estimation approach following allometric theory for accurate estimation of maximum forest tree height and biomass. The proposed approach can be applied to forest species in all types of environmental conditions.

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

Tree height is one of the more fundamental measurements in forest inventories. In addition to classical field measurements, tree height may be estimated by remote sensing methods, such as by photogrammetric measurements of aerial images. Since it has been found and generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests, the usefulness of photogrammetric-based forest inventory in many countries remains a controversial issue. Therefore, this paper focuses on investigating the possibility of applying digital photogrammetric method to estimate mean stand height. Photogrammetric stereo-measurements of tree height were conducted on colour infrared images of high spatial resolution (ground sample distance – GSD – of 30 cm and 10 cm) using a digital photogrammetric workstation. The height of each tree within 183 sample plots (14 subcompartments) were calculated as the difference between the tree top elevations determined with the aerial images and the corresponding tree bottom elevations determined from the digital terrain model. To compare the photogrammetric- and field-estimated mean stand heights, the mean plot heights were calculated for both photogrammetric and field estimates of tree heights. Repeated measurements using ANOVA testing did not reveal a statistically significant difference (p > 0.05) between the field-estimated and photogrammetric-estimated mean stand heights using the 30 cm and 10 cm GSD digital aerial images. Deviations of the mean stand heights estimated using the images of both spatial resolutions were similar to the field-estimated heights. Using the 30 cm images the deviations of the photogrammetrically estimated mean stand height amounted to 0.35 m (1.59%) on average, whereas using the 10 cm images the deviations amounted to 0.31 m (1.41%) compared to the field estimation. Therefore, it can be concluded that the 30 cm GSD aerial images allow for the photogrammetric measurement of mean stand heights with accuracy similar to 10 cm GSD aerial images. In addition, 30 cm GSD aerial images are more favourable financially since the same area of interest could be covered with a considerably smaller number of images than of the 10 cm GSD aerial images.

Three-Baseline InSAR Estimation of Forest Height

In this letter we propose a three-baseline approach to the extraction of forest tree height from synthetic aperture radar data. Three polarimetric–interferometric pairs are used to constrain a physical model that relates forest parameters to multiple repeat-pass coherence observations. The observations may be performed by a dual, compact or full polarimetric radar, and may be affected by distinct levels of temporal decorrelation. Here, we present the theoretical framework based on the random-motion-over-ground model, and describe an algorithm to extract tree height from the data. The performance of the algorithm is illustrated with L-band airborne data collected by the German Aerospace Center in the frame of the BIOSAR2008 campaign. The proposed method provides height estimates in good agreement with lidar measurements and can be applied to data to be collected by forthcoming polarimetric–interferometric spaceborne missions.

Impacts of Ionospheric Scintillation on the BIOMASS P-Band Satellite SAR

The European Space Agency is conducting studies for a low-earth orbiting polarimetric synthetic aperture radar called BIOMASS to provide global measurements of forest biomass and tree height. Phase scintillation across the synthetic aperture caused by ionospheric irregularities can degrade the impulse response function (IRF) and cause squinting, and its temporal variation can cause decorrelation in repeat-pass interferometry. These effects are simulated for a range of conditions for the baseline BIOMASS system configuration using the Wideband model of scintillation, which predicts that for a dawn-dusk orbit, impacts of scintillation over forest regions are negligible under all conditions except at high latitudes in the North American sector under high sunspot activity. In this sector, single-look IRFs have mean integrated sidelobe ratios (ISLRs) and peak sidelobe ratios (PSLRs) better than 0 and -5 dB, respectively, at 90% confidence interval under median solar activity up to the northern tree line ( ~ 70° geomagnetic). Degradation in the mean 3-dB resolution of up to 10% is predicted, with mean absolute azimuth shifts of the IRF peak of up to 2 m, which increases to 5 m at high sunspot number. Similar values are found for the dawn and dusk sides, and seasonal variations are negligible for latitudes below the tree line. Repeat-pass interferometric image pairs maintain coherence up to 50 ° N under median sunspot conditions. Four-look processing improves the ISLR and PSLR by several decibels, but causes significant degradation of the 3-dB resolution due to incoherent averaging of images with different random azimuth shifts.

Can the structure of a riparian forest remnant influence stream water quality? A tropical case study

In rural areas, riparian forest remnants can be very important for the maintenance and improvement of stream water quality. We evaluated if a forest remnant influenced stream water quality, and if these results were influenced by forest structure. We sampled reaches from 140 m upstream of the remnant edge until 600 m within the forest remnant. Electric conductivity (EC) and ammonium concentrations decreased as the stream flowed through the remnant, whereas dissolved oxygen, total phosphorus (P), total dissolved P, organic P, and silicate concentrations increased along the remnant. Variation in forest structure was due to a gradient in forest stratification versus tree height and diameter at breast height, and a gradient in tree density versus basal area. More stratified parts of the forest, with smaller trees, resulted in lower EC values and concentrations of total nitrogen and nitrite, whereas higher density of trees resulted in lower levels of total and dissolved P, creating heterogeneity at very local scales. The overall mean influence of this riparian forest remnant improved stream water quality, suggesting that forest remnants have local effects that can be important when managing stream water quality at larger spatial scales.

EUFODOS: European Forest Downstream Services – Improved Information on Forest Structure and Damage

Abstract. Forests play a key role in the European economy and environment. This role incorporates ecological functions which can be affected by the occurrence of insect infestations, forest fire, heavy snowfall or windfall events. Local or Regional Authorities (LRAs) thus require detailed information on the degradation status of their forests to be able to take appropriate measures for their forest management plans. In the EUFODOS project, state-of-the-art satellite and laser scanning technologies are used to provide forest authorities with cost-effective and comprehensive information on forest structure and damage. One of the six test sites is located in the Austrian province of Styria where regional forest authorities have expressed a strong need for detailed forest parameters in protective forest. As airborne laser-scanning data is available, it will be utilized to derive detailed forest parameters such as the upper forest border line, tree height, growth classes, forest density, vertical structure or volume. At the current project status, the results of (i) the forest border line, (ii) the segmentation of forest stands and (iii) the tree top detection are available and presented including accuracy assessment and interim results are shown for timber volume estimations. The final results show that the forest border can be mapped operationally with an overall accuracy of almost 99% from LiDAR data. For the segmentation of forest stands, a comparison of the automatically derived result with visual-manual delineation showed in general a more detailed segmentation result, but for all visual-manual segments a congruence of 87% within a 4 m buffer. Tree top detections were compared to stem numbers estimated based on angle-count samplings in a field campaign, which led to a correlation coefficient (R) of 0.79.

A CASE STUDY OF A FOREST CARBON STOCK MONITORING SYSTEM FOR REDD+ IN LAO P.D.R.

Abstract. Various technical studies for building forest monitoring system for MRV system of REDD+ has been implemented utilizing satellite remote sensing technology and ground survey upon configuring two pilot study areas, at whole Louangphabang (LPB) province (approximately 20,000 km2) and in Bolikhmxai(BLK) province (approximately 4,400 km2) in Lao PDR. Multi-temporal land use/cover data were prepared for making analyses of deforestation and forest degradation caused by various driving factors, and to establish reference scenario for REDD+. In addition to ordinary method of forest carbon stock estimation based on the forest plot surveys, land use/cover maps and IPCC's emission factors (GOFC-GOLD, 2010), improved methods were studied introducing a concept of biomass classing derived from multispectral data and tree height measurement utilizing ALOS/PRIS stereo images, in order to reduce difficulty of field surveys at high altitude and steep mountain forest, especially in natural forest areas. First, multi-temporal land use/cover maps were prepared for two pilot study areas for analyzing deforestation and forest degradation of the subjected area. Then, the biomass level of "Current Forest" area of the land use/cover maps were classified into three classes as high, medium, and low applying spectral analyses of LANDSAT/TM and SPOT images, and based on visual interpretation results of pan-sharpened ALOS/AVNIR2 images in addition to limited number of field surveys as references. Matching accuracies were around 60% at this stage of study (This number improved to 85% at the later stage). Based on the field survey data, the forest carbon stock vs. tree height model was established, and furthermore it was related to the forest biomass classes. ALOS/PRISM images were used to measure heights at about 1,500 forest stands selected at 2 – 4 km grid intervals. Accuracy analyses showed that the standard deviation of the tree height measurement errors was approximately 4 – 5 m, but the mean value of the measured data were within 1– 2 m comparing to the field survey data. Finally, wall-to-wall, above-ground forest carbon stock estimation maps which would be useful for forest management and REDD+ were prepared. As a conclusion, it can be said that 3D measurement, in addition to multi-spectral information, of the forest provides useful information for monitoring forest carbon stock for REDD+ although further refinement of technologies is to be needed. And, the results and experiences obtained from the studies will provide useful data for establishing actual MRVsystem.

Estimating structural properties of riparian forests with airborne lidar data

Riparian forest zones adjacent to surface water such as streams, lakes, reservoirs and wetlands maintain significant forest ecosystem functions including nutrient cycling, vegetative communities, water quality, fish and wildlife habitat and landscape aesthetics. In order to support the sustainable management of riparian forests, riparian zones should first be carefully delineated and then structural properties of riparian vegetation, especially forest trees, should be accurately measured. Geographical information system (GIS) techniques have been previously implemented to determine riparian zones quickly and reliably. However, basic measurements of forest structures in riparian areas have relied heavily on field-based surveys, which can be extremely time consuming in large areas. In this study, riparian forest zones were initially located using GIS techniques and then airborne lidar (light detection and ranging) data were used to determine and analyse structural properties (i.e. tree height, crown diameter, canopy closure and vegetation density) of a sample riparian forest. Lidar-derived tree height and crown diameter measurements of sample trees were compared with field-based measurements. Results indicated that 77.92% of the riparian area in the study area was covered by forest. Based on lidar-derived data, the average tree height, total crown width, canopy closure (above 3 m) and vegetation density (3–15 m) were found to be 74.72 m, 16.82 m, 71.15% and 26.05%, respectively. Although we found differences between measurement methods, lidar-derived riparian tree measurements were highly correlated with field measurements for tree height (R 2 = 88%) and crown width (R 2 = 92%). Differences between measurement methods were likely a result of difficulties associated with field measurements in the dense vegetation that is often associated with forested riparian areas.

Estimation of mean tree height using small-footprint airborne LiDAR without a digital terrain model

In order to estimate mean tree height using small-footprint airborne light detection and ranging (LiDAR) data, a digital terrain model (DTM), which is a continuous elevation model of the ground surface, is usually required. However, generating accurate DTMs in mountainous forests using only the LiDAR data is laborious and time consuming, because it requires human-assisted methods, especially in the forests with poor laser penetration rates. Based on our previous finding that a hypothetical continuous surface model passing through the predominant tree tops (hereafter, called the “top surface model” or TSM) might be nearly parallel to a DTM, we assumed that the vertical difference between the TSM and the ground return was the mean tree height. According to this assumption, we propose a new methodology that does not require a DTM to estimate mean tree height. This method completely, automatically, and directly estimates mean tree height (MTHE) from the LiDAR data without requiring a regression analysis using reference data. From the relationships between the MTHE and the observed mean tree height (MTHO) in different hinoki cypress forests, we demonstrate that this method effectively estimates the mean tree height with nearly 1-m accuracy.

Habitat associations of old forest bird species in managed boreal forests characterized by forest inventory data

Conservation areas are important for many species associated with old forests, but most individuals still occur in commercially-used forest landscapes. We conducted three-visit 2 breeding bird surveys in a total of 37 study squares of 1 km , and used National Forest In- ventory data to evaluate habitat associations of birds linked with old forests in three geo- graphical regions: southern, eastern and northern Finland. All study squares were located within managed forests. Out of the total of 23 pre-selected old-forest species, 12 were re- corded in the study squares of all three study regions; the number of species varied be- tween 16 and 21 among the regions. The total abundance did not significantly vary among the regions, but the abundances of many single species varied significantly among the re- gions. Forest-patch size was the single most important factor, positively affecting the abundance of most of the species considered. Development class affected most species in the south and east, and species associated with mature and old forest stands in general. Tree height and stand age were included into the models more often than tree species and diameter. In general, forest patch size, developmental class, age and tree height were among the most important factors in explaining the abundance of old-forest bird species in commercially-used forests. These stand characteristics appeared particularly important for resident species and cavity nesters. Our results indicate that the responses of old-forest bird species to environmental variation in managed, forested landscapes are individualis- tic, and different factors may affect them in different regions. Variables included in the patch-level forest-inventory data well explained abundance variation of species associ- ated with old forests. Our results underscore the importance of integrating national forest- inventory and bird-survey data to obtain information about species habitat requirements and forest-sector related information about the effects of forestry on birds.

Current Status of Tree Height Estimation from Airborne LiDAR Data

Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.

Evaluation of Trichospilus diatraeae (Hymenoptera: Eulophidae) as parasitoid of the eucalyptus defoliator Euselasia eucerus (Lepidoptera: Riodinidae)

Lepidopteran pests have occurred in eucalyptus plantations in Brazil since 1948, reaching high population levels, reducing tree growth and causing considerable losses in wood production. The control of defoliating caterpillars in eucalyptus forests is complex, mainly due to the large extent of forest plantations and tree height, necessitating the aerial application of chemical or biological insecticides. Due to this complexity, alternative control methods have been proposed, for instance biological control through the use of parasitoids. Trichospilus diatraeae Cherian & Margabandhu, 1942 is a gregarious pupal parasitoid that preferentially attacks species of the order Lepidoptera. This is the first report of T. diatraeae parasitizing pupae of the eucalyptus defoliator Euselasia eucerus Hewitson in Brazil. This parasitoid offers new perspectives for the biological control programmes of this species in eucalyptus plantations in Brazil.

Comparison between open-site and below-canopy climatic conditions in Switzerland for different types of forests over 10 years (1998−2007)

We compared below-canopy and open-site climatic conditions for 14 different forest sites in Switzerland and analysed the forest influence on local summer and winter climate according to the forest type (coniferous, mixed, deciduous), soil type, slope orientation, basal area and tree height. We compared below-canopy and open-field data for minimum, maximum and daily mean temperature, relative humidity, maximum and daily mean photosynthetically active radiation (PAR) and wind speed from 1998 to 2007. We found clear differences between below-canopy and open-field temperatures, humidity, wind speed and PAR and could relate them to the specific site conditions and forest type. The forest influence on PAR and maximum temperature is clearly determined by the forest type, whereas the influence on minimum temperature is affected by both forest type and slope orientation and impact on humidity depends on the soil type. The wind speed is most impacted by topography and slope orientation.

Genetic analysis of longitudinal height data using random regression

Genetic analysis of forest longitudinal height data using random regression (RR) has the potential to be attractive to tree breeders because of its advantages for selection at early ages. Our study provides an example of implementation of RR to forest tree height growth data. The data set comes from the Swedish Scots pine ( Pinus sylvestris L.) breeding program with a pedigree over three generations and consists of 899 trees with reconstructed phenotypic height records for 16 years. Legendre polynomials and B-splines were used as base functions in RR models. The restricted maximum likelihood method was employed to estimate (co)variance parameters. Results show that heritability increased with age, except for early ages (years 1 to 4). In general, slightly higher heritabilities were found for the RR model than for the single-trait and paired-trait analyses for most ages. Moreover, the heritabilities obtained with B-splines as the base function tended to be somewhat higher than those obtained with Legendre polynomials. The RR method provides a promising approach for estimating genetic parameters of longitudinal data that can be used in early selection. However, application to real data from other species and to simulated data is needed before general breeding recommendations can be established.

A STUDY ON FOREST BIOPHYSICAL PARAMETER IMPACT ON RADAR SIGNATURE AND EXTRACTION OF FOREST STOCK VOLUME BY MEANS OF RADARSAT-SAR

Based on the field survey data, this paper has analyzed the capability of Radarsat-SAR data on extracting the forest stock volume. The results obtained show that the Radarsat-SAR backscatter coefficient has a relatively good correlation with the forest stock volume, tree height and diameter at the breast height. Studies also show that the backscatter coefficient is much more affected by height than by diameter at the breast height. It is held that C band of SAR can be used to extract forest stem volume in a large plantation but is not suitable for forest survey.

Dispersal in a gradient of habitats: Activity by juvenile North American red squirrels (Tamiasciurus hudsonicus) in varying-age forest stands

Understanding the subtleties of the dispersal process, such as how dispersers investigate or avoid different habitat types, is critical to gaining insight into colonization rates and other population processes that occur across landscapes. In central British Columbia, Canada, I examined red squirrel (Tamiasciurus hudsonicus) dispersal activity in second-growth pine (Pinus contorta) stands of varying ages. The main objective of the study was to determine whether i) the dispersing animals directed more attention towards relatively older seral forest stands that more closely approximated their natal habitat (mature forest stands) or ii) they did not discriminate against younger forest stands, at least during the exploratory foray phase of dispersal. To counter the difficulty in monitoring dispersers over a large number of sites placed across the landscape, track counts were used to index dispersal activity. Dispersal activity became noticeably greater in pine stands once they reached 14–18 y of age, whereas younger stands showed relatively little activity. Average tree height and cone production in the second-growth forests increased with age, so both of these characteristics along with others (such as conspecific sign) constitute attributes of the stands that the animals potentially were keying into. To elucidate the relative importance of these potential cues will require further study.