Spatial and temporal variability of natural regeneration in a temperate old-growth forest

? The natural regeneration of shade-tolerant tree species is characterized by large spatial heterogeneity and temporal variability. The mechanisms producing those patterns are still poorly understood and the knowledge of long-term fluctuations in regeneration processes is very limited.

? We used data from long-term study plots in an old-growth stand dominated by European beech and silver fir to address three questions: (1) Is a tendency towards clumping in seedlings associated with a particular spatial scale? (2) Are the spatial patterns in seedlings constant over time? (3) Is the distribution of seedlings related to light intensity?

? Over the study period the seedling density varied from 2.5 to 6 ind./m². Stronger fluctuations occurred at a fine scale. Seedlings were clumped at distances ranging from a few centimeters to a few meters. The distribution of places with high seedling densities was relatively constant over time, especially in beech. Positive but weak rank correlations were found between light intensity and densities of beech and fir seedlings.

? Despite large fluctuations in seedlings densities, caused by mast-seeding, a permanent seedling bank was maintained. Very pronounced clumping of tree seedlings found in this study was only partially explained by differences in light intensity.

     

Fine-scale species co-occurrence patterns in an old-growth temperate forest

The pattern of species co-occurrence is instrumental for understanding community assembly rules. In this paper, we analyzed the co-occurrence of tree species in a 25-ha old-growth temperate forest plot in Northeastern China. The analysis was conducted at seven scales from 5 m × 5 m up to 100 m × 100 m in order to determine the patterns of co-occurrence at different spatial scales. Our analyses were conducted for all species, species with larger abundances, species with larger sizes, and five phylogenetic-based species groups. Our results showed that at smaller scales, the co-occurrence patterns of all species, species with larger abundances, and species with larger sizes were significantly higher than expected by chance, suggesting that strong interspecies competition exists in the community. At larger scales, there was no significant difference compared to randomized matrices. The result indicated that plant assembly rules are only found at small spatial scales. However, when co-occurrence metrics were restricted to phylogenetic groups, we could not find any clear evidence of interspecific competition within these groups. In conclusion, we found that competition is an important assembly rule at small scales in governing tree communities of our temperate forest, although it is not the only process involved. The importance of other processes should also be taken into account to explain species co-occurrence patterns.     

A two-scale approach for estimating forest aboveground biomass with optical remote sensing images in a subtropical forest of Nepal

Forests account for 80% of the total carbon exchange between the atmosphere and terrestrial ecosystems. Thus, to better manage our responses to global warming, it is important to monitor and assess forest aboveground carbon and forest aboveground biomass(FAGB). Different levels of detail are needed to estimate FAGB at local, regional and national scales. Multi-scale remote sensing analysis from high, medium and coarse spatial resolution data, along with field sampling, is one approach often used. However, the methods developed are still time consuming, expensive, and inconvenient for systematic monitoring, especially for developing countries,as they require vast numbers of field samples for upscaling.Here, we recommend a convenient two-scale approach to estimate FAGB that was tested in our study sites. The study was conducted in the Chitwan district of Nepal using GeoEye-1(0.5 m), Landsat(30 m) and Google Earth very high resolution(GEVHR) Quickbird(0.65 m) images. For the local scale(Kayerkhola watershed), tree crowns of the area were delineated by the object-based image analysis technique on GeoEye images. An overall accuracy of 83%was obtained in the delineation of tree canopy cover(TCC)per plot. A TCC vs. FAGB model was developed based on the TCC estimations from GeoEye and FAGB measurements from field sample plots. A coefficient of determination(R~2) of 0.76 was obtained in the modelling, and a value of 0.83 was obtained in the validation of the model.To upscale FAGB to the entire district, open source GEVHR images were used as virtual field plots. We delineated their TCC values and then calculated FAGB based on a TCC versus FAGB model. Using the multivariate adaptive regression splines machine learning algorithm, we developed a model from the relationship between the FAGB of GEVHR virtual plots with predictor parameters from Landsat 8 bands and vegetation indices. The model was then used to extrapolate FAGB to the entire district. This approach considerably reduced the need for field data and commercial very high resolution imagery while achieving two-scale forest information and FAGB estimates at high resolution(30 m) and accuracy(R2= 0.76 and 0.7) with minimal error(RMSE = 64 and38 tons ha-1) at local and regional scales. This methodology is a promising technique for cost-effective FAGB and carbon estimations and can be replicated with limited resources and time. The method is especially applicable for developing countries that have low budgets for carbon estimations, and it is also applicable to the Reducing Emissions from Deforestation and Forest Degradation(REDD ?) monitoring reporting and verification processes.     

Spatial and temporal patterns in structure,regeneration, and mortality of an old-growth ponderosa pine forest in the Colorado Front Range

Effective management and restoration of ponderosa pine forests requires an understanding of the heterogeneity of contemporary and historical stand structures. We assessed spatial and temporal patterns of tree establishment, mortality and size structure over a 30-year period in an old-growth ponderosa pine stand in the mid-montane zone of the Colorado Front Range. We analyzed spatial patterns and spatial associations using Ripley's K(t) and K₁₂(t) and then modeled the patterns using point process models. Forest age structure was estimated by aging a sub-sample of trees in the stand. Climate appeared to play a significant role in the coarse-scale temporal pattern of regeneration events. Stand structure (distribution of patches, light availability, and seed trees) influenced the spatial and temporal pattern of more recent regeneration events. Patchy regeneration resulted in spatial independence and some segregation of size classes. Older trees in the stand (40–55 cm dbh) exhibited some regularity in their spatial distribution at short distances indicating that patterns of mortality had been historically patchy. Contemporary patterns of mortality were mostly patchy, and mountain pine beetles caused a significant amount of mortality in the 1970s and 1980s. Both establishment and mortality retained spatial patterns that were somewhat consistent with pre-settlement forests, despite changes in driving processes.     

Surface temperature change of spruce forest as a result of bark beetle attack: remote sensing and GIS approach

In the 1990s, a bark beetle (Ips typographus [L.]) infection caused the decay of spruce forest (Picea abies [L.] Karst.) in the central part of the Šumava Mountains, the Czech Republic, bordering the Bavarian Forest National Park, Germany, where the bark beetle infection started in the late 1980s. Some areas were left without human intervention and, consequently, the trees around these areas were removed to stop further bark beetle outbreak. The objective of our study was the assessment of surface temperature (ST) change in spruce forest decayed under bark beetle and following clear-cutting. The change detection of ST is based on the comparison of modelled values and thermal satellite data. For this purpose, Landsat scenes from July 11th, 1987 and July 28th, 2002 were used. The models describe the dependence of ST of living spruce forest on topography. The topography effect is based on the Altitude and Hillshade index, which expresses the influence of Aspect and Slope on the relief illumination. Then the modelled ST values were extrapolated for decayed spruce forest and clear-cut areas. In order to increase model accuracy, the forest edge zones (90 m wide) were removed because of their different energy balance; then explained variability value (R ²) increased from 0.37 to 0.55. The results of comparing modelled values with satellite ST in the decayed spruce forest and clear-cut areas show an average increase of ST by 5.2 and 3.5°C, respectively. The thermal satellite data from 1987 were used for model validation. This showed that the accuracy of ST modelling using topography was sufficient, because the difference between the modelled ST with and without decayed spruce forest and clear-cut areas was at most only 0.4°C.     

遥感在森林生物量监测的应用

森林生物量研究对监测生态系统有着重要作用,随着遥感技术的发展,动态地估测大区域乃至全球的森林生物量成为可能.文章就遥感数据源和估测方法,分析总结了传统方法和遥感方法的森林生物量估测.     

Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches

New Forests - With the demand for, and scale of, ecological restoration increasing globally, effectiveness monitoring remains a significant challenge. For forest restoration, structural complexity...     

Aboveground biomass assessment in Colombia: A remote sensing approach

This paper presents a method to increase the level of detail of aboveground biomass estimates at a regional scale. Methods are based on empirical relationships while materials are based on MODIS products and field measurements; the area covers from 4° south up to 12° north of the Equator with a total of 1,139,012 km² corresponding to the continental area of Colombia. Vegetation was classified in three broad classes: grasslands, secondary forests and primary forests which have been proved to enhance biomass estimates. MOD44 vegetation continuous fields (VCFs) was used as an explanatory variable for primary and secondary forests following an exponential relationship, while MOD13A1 enhanced vegetation index (EVI) was used as explanatory variable for grasslands following a linear relationship; biomass for this vegetation class was estimated every 16 days given its large variation throughout the year. EVI–biomass relationships were established from 2001 to 2006. Vegetation maps were used to separate primary forests from secondary forest, since the latter has shown lower biomass levels. Confidence intervals of the exponential regression are larger as the biomass values increases, for this reason the uncertainty is quite high ranging from 3.7 to 25.2 millions of Mg with a mean of 16.2 million of Mg. Despite the uncertainty our biomass results are within the estimates of previous studies.     

长白山自然保护区阔叶红松林林隙更新状况

该以长白山大面积分布的阔叶红松林林隙为研究对象．系统调查了林隙形成木和林隙填充的特征，并对其主要树种的更新环境进行研究。结果表明，长白山阔叶红松林林隙多数是由1．4株形成木形成的，林隙形成木主要是红松、水曲柳、蒙古栎和紫椴；林隙填充中，紫椴和色木槭的数量最多，红松所占比例较小。不同大小林隙内填充的数量也不同，近似呈一个偏左的正态分布。现有的红松幼树一般都分布在林隙内或林隙边缘，更新环境良好。     

Tree mortality and habitat shifts in the regeneration trajectory underneath canopy of an old-growth subalpine forest

To better understand tree regeneration trajectories and the resultant coexistence of Abies with co-dominants, Picea jezoensis var. hondoensis, Tsuga diversifolia and Betula ermanii, in an old-growth subalpine forest, we investigated spatial mortality patterns during the regeneration of Abies mariesii and A. veitchii, which are abundant in the understory reflecting their shade tolerance. Regeneration of these Abies spp. from shaded understory to canopy status is affected by other canopy co-dominants. Snags of understory Abies spp. were common, suggesting that the primary mortality agent is suppression by the overstory. Although live, small Abies trees in the understory were positively associated with a Picea canopy, the long-term survival was reduced among Abies trees close to the canopy, suggesting that shading by large Picea in the overstory negatively affects understory Abies plants. The existence of shade-intolerant canopy co-dominants such as Picea and also Tsuga, which are larger and longer lived than the shade-tolerant Abies, may play an important role in preventing the Abies spp. from competitively displacing these other tree species, which are much rarer in the understory, though common in the canopy. Moreover, in spite of the fact that Betula canopies fostered recruitment and growth of Abies saplings, Abies showed no association with Betula canopy and their survival at later-stage was rather reduced near or beneath Betula canopies at the subsequent understory small tree stage. Based on spatially significant events related to tree death, this study detected such “habitat shifts” in the trajectory of tree regeneration. Accordingly, it can be concluded that careful consideration of the regeneration habitat is required for a fuller understanding of ecological processes in spatially complex old-growth forest systems.     

卫星遥感数据在森林采伐监测中的应用

分别采用SPOT5、TM5影像前后两期多光谱遥感影像的波谱特征变化,检测森林资源变化信息,确定变化类型,以计算机自动识别对森林资源变化(减少)的区域(伐区)进行信息提取,并在此基础上进行室内人工预判读;结合采伐证、伐区作业设计、二类调查材料,进行补充判读,得出森林采伐图斑。古丈TM5(30 m分辨率)的面积正判率为96.3%;古丈SPOT5(10 m分辨率)的面积正判率为96.9%。实证分析表明,使用中、高分辨率卫星遥感数据能对森林采伐进行监测,结合辅助材料后能显著提高森林采伐监测精度。     

Spatial partitioning of biomass and diversity in a lowland Bolivian forest: Linking field and remote sensing measurements

Large-scale inventories of forest biomass and structure are necessary for both understanding carbon dynamics and conserving biodiversity. High-resolution satellite imagery is starting to enable structural analysis of tropical forests over large areas, but we lack an understanding of how tropical forest biomass links to remote sensing. We quantified the spatial distribution of biomass and tree species diversity over 4 ha in a Bolivian lowland moist tropical forest, and then linked our field measurements to high-resolution Quickbird satellite imagery. Our field measurements showed that emergent and canopy dominant trees, being those directly visible from nadir remote sensors, comprised the highest diversity of tree species, represented 86% of all tree species found in our study plots, and contained the majority of forest biomass. Emergent trees obscured 1–15 trees with trunk diameters (at 1.3 m, diameter at breast height (DBH)) ≥20 cm, thus hiding 30–50% of forest biomass from nadir viewing. Allometric equations were developed to link remotely visible crown features to stand parameters, showing that the maximum tree crown length explains 50–70% of the individual tree biomass. We then developed correction equations to derive aboveground forest biomass, basal area, and tree density from tree crowns visible to nadir satellites. We applied an automated tree crown delineation procedure to a high-resolution panchromatic Quickbird image of our study area, which showed promise for identification of forest biomass at community scales, but which also highlighted the difficulties of remotely sensing forest structure at the individual tree level.     

Spatial patterns in different forest development stages of an intact old-growth Oriental beech forest in the Caspian region of Iran

Spatial patterns of trees are important structural characteristics that can provide insights into forest dynamics and may be related to the development stages of forests. The spatial patterns of three development stages (i.e., initial, optimal, and decay) of an intact old-growth beech (Fagus orientalis Lipsky) forest in the Caspian region of Iran were quantified within one-hectare permanent plots. All trees with a diameter at breast height of more than 7.5?cm were measured, stem-mapped, and then assigned to one of four diameter size classes (small, medium, large, and extra-large timbers). Spatial patterns of all trees and spatial associations among tree size classes were analyzed using Ripley’s K-function, and the spatial dependence of tree diameters was analyzed using variograms. Results showed that trees in the small size class exhibited an aggregated distribution in every development stage, which matched the overall spatial pattern of all trees in each stage. However, the degree of aggregation of all trees as well as association patterns among the size classes differed among the three development stages. Further, the average spatial dependence of tree diameters was 24, 14, and 19?m in the initial, optimal, and decay stages, respectively. Differences in spatial patterns among the development stages in this beech old-growth forest are consistent with the gap-dynamics paradigm and likely reflect different canopy disturbance events coupled with associated regeneration, release, and competition processes (e.g., shade-tolerance characteristics, seed dispersal limitation, and intraspecific competition).     

Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10~(15) g), with an average of 77.2 Mg ha~(-1), during the study period. Forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.     

Tree regeneration and seedling survival patterns in old-growth lowland tropical rainforest in Namdapha National Park, north-east India

The tree structure and regeneration was studied in the buffer zone area comprising lowland evergreen and semi-evergreen forests in the Namdapha National Park, one of the largest remaining tract of pristine rainforests in the Eastern Himalayan biodiversity hotspot in India. The investigations were conducted in the three forest stands, viz. Altingia-mixed species, Shorea-Dipterocarp, and Albizia forests that are most dominant forest types in the lowland areas of the park. A total of 98, 54 and 20 species have been recorded at tree stratrum, while 87, 44 and 15 species at regeneration stratum for three stands, respectively. The cumulative regenerating density (seedlings + saplings) was estimated 17,648, 16,110 and 768 individual ha⁻¹ for respective stands. It was interesting to note that of the total regenerating species, 44–47% species were new to different stands, which mainly comprised middle storey species. Low-dominant and rare species also contributed significantly in the regeneration of the forest stands. The expanding population structure of forest stands indicated higher survival of the mid- and the low-canopy species than the top-canopy species. The data revealed that the future composition of these stands will highly depended on the potential regenerative status of species in each of the stand and such information would be crucial for forest management. Since the park contributed significantly to the regional biodiversity by depicting species assemblages for both wet evergreen and semi-evergreen biomes, such last remnants of rainforest should be integrally protected from anthropogenic disturbances.     

Flux partitioning in an old-growth forest: seasonal and interannual dynamics

Turbulent fluxes of carbon, water and energy were measured at the Wind River Canopy Crane, Washington, USA from 1999 to 2004 with eddy-covariance instrumentation above (67 m) and below (2.5 m) the forest canopy. Here we present the decomposition of net ecosystem exchange of carbon (NEE) into gross primary productivity (GPP), ecosystem respiration (R(eco)) and tree canopy net CO(2) exchange (DeltaC) for an old-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco)-western hemlock (Tsuga heterophylla (Raf.) Sarg.) forest. Significant amounts of carbon were recycled within the canopy because carbon flux measured at the below-canopy level was always upward. Maximum fluxes reached 4-6 micromol m(-2) s(-1) of CO(2) into the canopy air space during the summer months, often equaling the net downward fluxes measured at the above-canopy level. Ecosystem respiration rates deviated from the expected exponential relationship with temperature during the summer months. An empirical ecosystem stress term was derived from soil water content and understory flux data and was added to the R(eco) model to account for attenuated respiration during the summer drought. This attenuation term was not needed in 1999, a wet La Ni?a year. Years in which climate approximated the historical mean, were within the normal range in both NEE and R(eco), but enhanced or suppressed R(eco) had a significant influence on the carbon balance of the entire stand. In years with low respiration the forest acts as a strong carbon sink (-217 g C m(-2) year(-1)), whereas years in which respiration is high can turn the ecosystem into a weak to moderate carbon source (+100 g C m(-2) year(-1)).     

LOSS ASSESSMENT OF BURNED FOREST USING REMOTE SENSING AND GEOGRAPHICAL INFORMATION TECHNIQUES

After forest fire,It is very needd to locate fire position and assess the loss of forestresources.In this paper,a method of burned forest assessment with satellite remote sensing dataand over-laying techniques is discussed and used in the assessment of the burned forest in Malinforest Farm after the large forest fire of May,1987.     

遥感技术在森林资源调查中可行性分析

选择有代表性的地类小班使用TM卫星遥感(RS)图像现地区划面积，同时使用GPS观测小班面积，计算TM图像区划面积和GPS定位观测小班面积绝对误差和相对误差。经试验，确定森林资源规划设计调查，采用TM遥感图像现地区划最小面积4．0hm^2，适宜最小比例尺为1：25000。     

Habitat assessment for forest dwelling species using LiDAR remote sensing: Capercaillie in the Alps

Large-scale information on habitat suitability is indispensable for planning management actions to further endangered species with large-spatial requirements. So far, remote sensing based habitat variables mostly included environmental and land cover data derived from passive sensors, but lacked information on vegetation structure. This is a serious constraint for the management of endangered species with specific structural requirements. Light detection and ranging (LiDAR), in contrast to passive remote sensing techniques, may bridge this gap in structural information at the landscape scale. We investigated the potential of LiDAR data to quantify habitat suitability for capercaillie (Tetrao urogallus), an endangered forest grouse in Central Europe, in a forest reserve of 17.7 km². We used continuous variables of horizontal and vertical stand structure from first and last pulse LiDAR data and presence–absence information from field work to model habitat suitability with generalized linear models (GLM). The two final habitat suitability models explained the observed presence–absence pattern moderately well (AUC of 0.71 and 0.77) with horizontal structure explaining better than vertical structure. Relative tree canopy cover was the most important variable with intermediate values indicating highest habitat suitability. As such, LiDAR allowed us to translate the results from habitat modeling at the landscape scale to effective management recommendations at the local scale at a level of detail that hitherto was unavailable for large areas. LiDAR thus enabled us to integrate individual habitat preferences at the scale of entire populations and thus offers great potential for effective habitat monitoring and management of endangered species.