Forest damage assessments in Austria

Different types of assessments of forest damage are conducted in Austria. Faced with forest dieback reports, a needle and leaf sampling programme and a terrestrial crown assessment have been started after 1983, in addition to the forest inventory. In order to obtain more comprehensive and detailed information for the analysis of cause-effect relationships, as many investigations concerning forest health status as possible were concentrated on permanent plots out of the grid of the Austrian National Forest Inventory. This new, long-term project, started in 1987, was called the Forest Damage Monitoring System. An overview of the investigations and assessments, as they have been conducted by the end of 1991, is given in this paper.     

Impacts of ecological water conveyance on groundwater dynamics and vegetation recovery in the lower reaches of the Tarim River in northwest China

The ecological water conveyance project (EWCP) in the lower reaches of the Tarim River provided a valuable opportunity to study hydro-ecological processes of desert riparian vegetation. Ecological effects of the EWCP were assessed at large spatial and temporal scales based on 13 years of monitoring data. This study analyzed the trends in hydrological processes and the ecological effects of the EWCP. The EWCP resulted in increased groundwater storage—expressed as a general rise in the groundwater table—and improved soil moisture conditions. The change of water conditions also directly affected vegetative cover and the phenology of herbs, trees, and shrubs. Vegetative cover of herbs was most closely correlated to groundwater depth at the last year-end (R?=?0.81), and trees and shrubs were most closely correlated to annual average groundwater depth (R?=?0.79 and 0.66, respectively). The Normalized Difference Vegetation Index (NDVI) responded to groundwater depth on a 1-year time lag. Although the EWCP improved the NDVI, the study area is still sparsely vegetated. The main limitation of the EWCP is that it can only preserve the survival of existing vegetation, but it does not effectively promote the reproduction and regeneration of natural vegetation.     

Determining Ecoregions for Environmental and GMO Monitoring Networks

A representative environmental monitoring network at the regional scale cannot use raster-based or random sampling designs, but requires a stratified sampling procedure integrating different information layers, and it has to occur in ecologically differing homogeneous regions (ecoregions). These we have determined using a set of spatial strata with ecological variables which we analysed with classification and regression trees (CART). We present a framework for environmental monitoring, that covers different scales, and we transfer the framework to a potential GMO (genetically modified organisms) monitoring network. We use ecoregion and other environmental strata together with existing environmental monitoring networks to determine GMO monitoring sites more precisely.     

Assessment of hydraulic redistribution on desert riparian forests in an extremely arid area

The roots of Populus euphratica, a plant that grows in the lower reaches of the Tarim River, Northwest China, exhibit a significant level of hydraulic redistribution; however, quantitative assessments of the water-sharing process and its ecological effects are limited. This study was designed to obtain such data using an assessment model based on field observation parameters, including soil water content (soil water potential), root distribution, and stable isotope δ¹⁸O values of soil and plant samples during the entire growing season. The results showed that hydraulic redistribution in P. euphratica can be detected in 0–120 cm soil layers, with the amount of hydraulically redistributed water (HRW) in the soil found at different depths as follows: 60–80?>?40–60?>?20–40?>?0–20?>?80–100?>?100–120 cm. The variations in HRW in soil layers can be partly attributed to the vertical distribution of roots. The denser roots found at greater depths positively influenced the amount of redistributed water in lower soil layers. During the growing season, the amount of HRW reached a daily average of 0.27 mm, which allowed increased transpiration and provided an adequate water supply to herbs. Based on the stable isotope (δ¹⁸O) data, the amount of HRW provided by the roots of P. euphratica could meet 22–41 % of its water demand.     

Crown density assessments, control surveys and reproducibility

This study aims to evaluate the quality of crown density data, based on independent, pairwise tree assessments. The data originates from monitoring of forest health (crown condition) in Norway; 250 plots, comprising 12 000 individual trees of Norway spruce, have been reassessed by a single observer during 1990–95. Of the trees, 2300 were controlled more than twice, providing the possibility of evaluating the quality of assessed temporal changes of crown density. True errors (standard deviation) are estimated to be about 10% for single trees and 5% for plot means, while the real standard deviation of the differences were slightly higher. The errors of the temporal changes of crown density were of similar magnitude. Systematic differences in crown density were found between sites and plot types, partly resulting from observer bias. However, the results suggest that observer bias is really the result of each observer's personal style in assessment.     

Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R ²?=?0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R ²?=?0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.     

Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data

This study deals with the future scope of REDD (Reduced Emissions from Deforestation and forest Degradation) and REDD+ regimes for measuring and monitoring the current state and dynamics of carbon stocks over time with integrated geospatial and field-based biomass inventory approach. Multi-temporal and multi-resolution geospatial synergic approach incorporating satellite sensors from moderate to high resolution with stratified random sampling design is used. The inventory process involves a continuous forest inventory to facilitate the quantification of possible CO₂ reductions over time using statistical up-scaling procedures on various levels. The combined approach was applied on a regional scale taking Himachal Pradesh (India), as a case study, with a hierarchy of forest strata representing the forest structure found in India. Biophysical modeling implemented revealed power regression model as the best fit (R ²?=?0.82) to model the relationship between Normalized Difference Vegetation Index and biomass which was further implemented to calculate multi-temporal above ground biomass and carbon sequestration. The calculated value of net carbon sequestered by the forests totaled to 11.52 million tons (Mt) over the period of 20 years at the rate of 0.58 Mt per year since 1990 while CO₂ equivalent reduced from the environment by the forests under study during 20 years comes to 42.26 Mt in the study area.     

Landsat image and sample design for water reservoirs (Rapel dam Central Chile)

Spatial heterogeneity of the Rapel reservoir surface waters is analyzed through Landsat images. The image digital counts are used with the aim or developing an aprioristic quantitative sample design.Natural horizontal stratification of the Rapel Reservoir (Central Chile) is produced mainly by suspended solids. The spatial heterogeneity conditions of the reservoir for the Spring 86-Summer 87 period were determined by qualitative analysis and image processing of the MSS Landsat, bands 1 and 3. The space-time variations of the different observed strata obtained with multitemporal image analysis.A random stratified sample design (r.s.s.d) was developed, based on the digital counts statistical analysis. Strata population size as well as the average, variance and sampling size of the digital counts were obtained by the r.s.s.d method.Stratification determined by analysis of satellite images were later correlated with ground data. Though the stratification of the reservoir is constant over time, the shape and size of the strata varys.     

Improving the precision of sample-based forest damage inventories through two-phase sampling and post-stratification using remotely sensed auxiliary information

Many countries have a national forest inventory (NFI) designed to produce statistically sound estimates of forest parameters. However, this type of inventory may not provide reliable results for forest damage which usually affects only small parts of the forest in a country. For this reason, specially designed forest damage inventories are performed in many countries, sometimes in coordination with the NFIs. In this study, we evaluated a new approach for damage inventory where existing NFI data form the basis for two-phase sampling for stratification and remotely sensed auxiliary data are applied for further improvement of precision through post-stratification. We applied Monte Carlo sampling simulation to evaluate different sampling strategies linked to different damage scenarios. The use of existing NFI data in a two-phase sampling for stratification design resulted in a relative efficiency of 50 % or lower, i.e., the variance was at least halved compared to a simple random sample of the same size. With post-stratification based on simulated remotely sensed auxiliary data, there was additional improvement, which depended on the accuracy of the auxiliary data and the properties of the forest damage. In many cases, the relative efficiency was further reduced by as much as one-half. In conclusion, the results show that substantial gains in precision can be obtained by utilizing auxiliary information in forest damage surveys, through two-phase sampling, through post-stratification, and through the combination of these two approaches, i.e., post-stratified two-phase sampling for stratification.     

evaluation of a measurement method for forest vegetation in a large-scale ecological survey

We evaluate a field method for determining species richness andcanopy cover of vascular plants for the Forest Health MonitoringProgram (FHM), an ecological survey of U.S. forests. Measurementsare taken within 12 1-m² quadrats on 1/15 ha plots in FHM.Species richness and cover are determined for four height classes(strata) within each quadrat and aggregated by stratum over the entireplot. We estimated (1) the agreement between experienced trainers andinexperienced technicians who collected the data on this survey(accuracy) and (2) the agreement among the technicians (precision) forresults on species richness and cover from 3 test plots at 3 timeintervals. The methods appear to be highly precise, although somediscrepancies with the values obtained by the trainers were found.Trainers found significantly more species in the ground stratum (0–0.6 m) and measured significantly more cover in the uppermost stratum(>4.9 m). The proportion of variation due to measurement error andtemporal variability was less than 13% for species richness (all strata)and cover (all but one stratum). This indicates that the method issuitable for monitoring changes in species richness and canopy coverfor a large-scale synoptic monitoring project such as FHM.     

Sampling The Soil In Long-Term Forest Plots: The Implications Of Spatial Variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.     

Sampling for landscape elements—a case study from Lower Saxony,Germany

The estimation of coverage, i.e., the proportion of the total area in a study region covered by a given target class, is essential to many aspects of environmental monitoring. We analyze and compare the efficiency of different sample-based approaches for the estimation of coverage of different land cover classes from aerial imagery in a case study in Lower Saxony, Germany on the basis of the estimated standard errors. A complete delineation of vegetation classes in n?=?279 aerial photo plots of 400 × 400 m thrown onto the study region of 1,117.7 km² in accordance with a systematic grid is compared to different configurations of line intercept sampling and clusters of points. The observation designs under study are characterized by different complexity and total size of the observation units and therefore also to the efforts related to yield a single observation. Especially for those classes that cover a relatively large proportion of the sampling frame, our results show that difference in performance between the different designs are negligible. A cluster of four transects of 200 m each allows estimating the area of land cover classes with high coverage with nearly similar precision as a complete mapping of fixed area plots of 16 ha each. Clusters of points show unexpected high precision for the estimated coverage of land cover classes with relatively high coverage.     

Ice Storm Damage and Early Recovery in an Old-Growth Forest

We quantified the damage causedby a major ice storm to individual trees in two1-ha permanent plots located at Mont St. Hilairein southwestern Québec, Canada. The storm, whichoccurred in January 1998, is the worst on recordin eastern North America; glaze ice on the orderof 80–100 mm accumulated at our study site. Allbut 3% of the trees (DBH 10 cm) lost at leastsome crown branches, and 35% lost more than halftheir crown. Damage to trees increased in the order: Tsuga canadensis, Betula alleghaniensis, Ostrya virginiana, Acer saccharum, Fagus grandifolia, Quercus rubra, Betula papyrifera, Acer rubrum, Tilia americana, and Fraxinus americana. Only 22% of the saplings and small trees (4 cm < DBH < 10 cm)escaped being broken or pinned to the ground byfalling material. Levels of damage generally weregreater in an exposed ridge top forest than in acove protected from wind. By August 1999 only53% of the trees had new shoots developing fromthe trunk or broken branches; among the moredominant canopy trees, Fagus grandifoliahad the least sprouting and Acer saccharumand Quercus rubra the most. We anticipateand will monitor both significant turnover in thetree community and some shift in composition ofthe canopy dominants.     

Water use sources of desert riparian Populus euphratica forests

Desert riparian forests are the main body of natural oases in the lower reaches of inland rivers; its growth and distribution are closely related to water use sources. However, how does the desert riparian forest obtains a stable water source and which water sources it uses to effectively avoid or overcome water stress to survive? This paper describes an analysis of the water sources, using the stable oxygen isotope technique and the linear mixed model of the isotopic values and of desert riparian Populus euphratica forests growing at sites with different groundwater depths and conditions. The results showed that the main water source of Populus euphratica changes from water in a single soil layer or groundwater to deep subsoil water and groundwater as the depth of groundwater increases. This appears to be an adaptive selection to arid and water-deficient conditions and is a primary reason for the long-term survival of P. euphratica in the desert riparian forest of an extremely arid region. Water contributions from the various soil layers and from groundwater differed and the desert riparian P. euphratica forests in different habitats had dissimilar water use strategies.     

Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches

Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis—[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.     

Growing stock and woody biomass assessment in Asola-Bhatti Wildlife Sanctuary,Delhi, India

Biomass is an important entity to understand the capacity of an ecosystem to sequester and accumulate carbon over time. The present study, done in collaboration with the Delhi Forest Department, focused on the estimation of growing stock and the woody biomass in the so-called lungs of Delhi—the Asola-Bhatti Wildlife Sanctuary in northern Aravalli hills. The satellite-derived vegetation strata were field-inventoried using stratified random sampling procedure. Growing stock was calculated for the individual sample plots using field data and species-specific volume equations. Biomass was estimated from the growing stock and the specific gravity of the wood. Among the four vegetation types, viz. Prosopis juliflora, Anogeissus pendula, forest plantation and the scrub, the P. juliflora was found to be the dominant vegetation in the area, covering 23.43 km² of the total area. The study revealed that P. juliflora forest with moderate density had the highest (10.7 m³/ha) while A. pendula forest with moderate density had the lowest (3.6 m³/ha) mean volume. The mean woody biomass was also found to be maximum in P. juliflora forest with moderate density (10.3 t/ha) and lowest in A. pendula forest with moderate density (3.48 t/ha). The total growing stock was estimated to be 20,772.95 m³ while total biomass worked out to be 19,366.83 t. A strong correlation was noticed between the normalized difference vegetation index (NDVI) and the growing stock (R ²?=?0.84)/biomass (R ²?=?0.88). The study demonstrated that growing stock and the biomass of the woody vegetation in Asola-Bhatti Wildlife Sanctuary could be estimated with high accuracy using optical remote sensing data.     

Relationship Between Crown Condition and Tree Diameter Growth in Southern Swedish Oaks

We studied correlation between crown conditions and tree-ring widths in 260 trees of pedunculate oak (Quercus robur L.) growing on 33 sites in southern Sweden. The tree-ring increment over 1998-2002 was highest in trees with healthy crowns, intermediate in trees with moderately declined crowns, and lowest in trees with heavily declining crowns. The time period with significant correlation between crown status and tree-ring increment varied between 10 years (given autocorrelation in tree-ring chronologies preserved) and 4 years (autocorrelation removed). In pairwise comparisons of three crown classes, differences in tree-ring increment between trees with healthy crowns and trees with heavily declining crowns were the most pronounced, Fisher LSD P value staying below 0.05 over 13 years (autocorrelation preserved ) or 4 years (autocorrelation removed). Over two 5-year periods (1993-1997 vs. 1998-2002) the cumulative increment increased significantly for trees with healthy crowns, did not change in trees with moderately declining crowns, and significantly decreased in trees with heavily declining crowns. For trees with healthy crowns, this dynamics may represent growth recovery after 1992 drought. Instead, oaks with defoliation above 60% appear to reach a threshold in their ability to recover growth. At sites on nutrient-poor soils cumulative increments over 1998-2002 differed significantly among trees with different crown condition and no differences were observed at sites on nutrient-rich soils. Analyses and interpretation of the oak growth trends as recovered from tree-ring chronologies may be improved by controlling for the crown status of the trees sampled, e.g., by using sampling strategy that would represent the average crown and growth conditions of the sites.     

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.