Geospatial assessment and monitoring of historical forest cover changes (1920–2012) in Nilgiri Biosphere Reserve,Western Ghats,India

Deforestation in the biosphere reserves, which are key Protected Areas has negative impacts on biodiversity, climate, carbon fluxes and livelihoods. Comprehensive study of deforestation in biosphere reserves is required to assess the impact of the management effectiveness. This article assesses the changes in forest cover in various zones and protected areas of Nilgiri Biosphere Reserve, the first declared biosphere reserve in India which forms part of Western Ghats-a global biodiversity hotspot. In this study, we have mapped the forests from earliest available topographical maps and multi-temporal satellite data spanning from 1920’s to 2012 period. Mapping of spatial extent of forest cover, vegetation types and land cover was carried out using visual interpretation technique. A grid cell of 1 km?×?1 km was generated for time series change analysis to understand the patterns in spatial distribution of forest cover (1920–1973–1989–1999–2006–2012). The total forest area of biosphere reserve was found to be 5,806.5 km² (93.8 % of total geographical area) in 1920. Overall loss of forest cover was estimated as 1,423.6 km² (24.5 % of the total forest) with reference to 1920. Among the six Protected Areas, annual deforestation rate of >0.5 was found in Wayanad wildlife sanctuary during 1920–1973. The deforestation in Nilgiri Biosphere Reserve is mainly attributed to conversion of forests to plantations and agriculture along with submergence due to construction of dams during 1920 to 1989. Grid wise analysis indicates that 851 grids have undergone large-scale negative changes of >75 ha of forest loss during 1920–1973 while, only 15 grids have shown >75 ha loss during 1973–1989. Annual net rate of deforestation for the period of 1920 to 1973 was calculated as 0.5 followed by 0.1 for 1973 to 1989. Our analysis shows that there was large-scale deforestation before the declaration of area as biosphere reserve in 1986; however, the deforestation has drastically reduced after the declaration due to high degree of protection, thus indicating the secure future of reserve in the long term under the current forest management practices. The present work will stand as the most up-to-date assessment on the forest cover of the Nilgiri Biosphere Reserve with immediate applications in monitoring and management of forest biodiversity.     

Assessment of land cover changes & water quality changes in the Zayandehroud River Basin between 1997–2008

Water quality of rivers is strongly influenced by landscape characteristics of their watershed, including land use /cover types, and their spatial configuration. This research evaluates the effects of land cover changes on the water quality of the Zayandehroud River, which is the most important river in the center of Iran. The main goal of this study was to quantify the change in rangelands, forests, and bare lands in the Zayandehroud river basin, which suffered intense human interference, in a period of 11 years (1997–2008), and to evaluate how landscape patterns (including the number of patches, edge density, percentage of rangelands, forests, and bare lands) influence on the 14 water quality indices (including BOD5, EC, NO3, P, and TDS) measured in 10 stations along the river. Results showed that from 1997 to 2008, bare lands increased from 5.8 to 20 %, while rangelands decreased from 70 to 55 % in the whole basin. The results indicated that water quality was significantly correlated with both the proportions and configuration of rangeland and bare land areas. The total edge (TE) of rangeland area had positive effects on water quality, especially on BOD5 and EC. Percentage of landscape (PLAND) and largest patch index (LPI) metrics of rangeland had positive effect on decreasing nutrient (NO₃, PO₄). The results showed that water quality was more likely degraded when there was high edge density (ED) of bare lands. Results of this study also revealed that degradation of rangeland lead to the degradation of water quality. Finding of this study highlights the importance of rangeland conservation in water quality management at landscape scale.     

Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979�C2009) in China

This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979?C2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.     

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987–2016) case study of Hamoun Wetland,Iran

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R²?=?0.94) than fall and spring (R²?=?0.58) seasons. Before 2000, ~?50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.     

Characterizing the forest fragmentation of Canada’s national parks

Characterizing the amount and configuration of forests can provide insights into habitat quality, biodiversity, and land use. The establishment of protected areas can be a mechanism for maintaining large, contiguous areas of forests, and the loss and fragmentation of forest habitat is a potential threat to Canada’s national park system. Using the Earth Observation for Sustainable Development of Forests (EOSD) land cover product (EOSD LC 2000), we characterize the circa 2000 forest patterns in 26 of Canada’s national parks and compare these to forest patterns in the ecological units surrounding these parks, referred to as the greater park ecosystem (GPE). Five landscape pattern metrics were analyzed: number of forest patches, mean forest patch size (hectare), standard deviation of forest patch size (hectare), mean forest patch perimeter-to-area ratio (meters per hectare), and edge density of forest patches (meters per hectare). An assumption is often made that forests within park boundaries are less fragmented than the surrounding GPE, as indicated by fewer forest patches, a larger mean forest patch size, less variability in forest patch size, a lower perimeter-to-area ratio, and lower forest edge density. Of the 26 national parks we analyzed, 58% had significantly fewer patches, 46% had a significantly larger mean forest patch size (23% were not significantly different), and 46% had a significantly smaller standard deviation of forest patch size (31% were not significantly different), relative to their GPEs. For forest patch perimeter-to-area ratio and forest edge density, equal proportions of parks had values that were significantly larger or smaller than their respective GPEs and no clear trend emerged. In summary, all the national parks we analyzed, with the exception of the Georgian Bay Islands, were found to be significantly different from their corresponding GPE for at least one of the five metrics assessed, and 50% of the 26 parks were significantly different from their respective GPEs for all of the metrics assessed. The EOSD LC 2000 provides a heretofore unavailable dataset for characterizing broad trends in forest fragmentation in Canada’s national parks and in their surrounding GPEs. The interpretation of forest fragmentation metrics must be guided by the underlying land cover context, as many forested ecosystems in Canada are naturally fragmented due to wetlands and topography. Furthermore, interpretation must also consider the management context, as some parks are designed to preserve fragmented habitats. An analysis of forest pattern such as that described herein provides a baseline, from which changes in fragmentation patterns over time could be monitored, enabled by earth observation data.     

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.     

NDVI indicated characteristics of vegetation cover change in China��s metropolises over the last three decades

How urban vegetation was influenced by three decades of intensive urbanization in China is of great interest but rarely studied. In this paper, we used satellite derived Normalized Difference Vegetation Index (NDVI) and socioeconomic data to evaluate effects of urbanization on vegetation cover in China??s 117 metropolises over the last three decades. Our results suggest that current urbanization has caused deterioration of urban vegetation across most cities in China, particularly in East China. At the national scale, average urban area NDVI (NDVI_u) significantly decreased during the last three decades (P?<?0.01), and two distinct periods with different trends can be identified, 1982?C1990 and 1990?C2006. NDVI_u did not show statistically significant trend before 1990 but decrease remarkably after 1990 (P?<?0.01). Different regions also showed difference in the timing of NDVI_u turning point. The year when NDVI_u started to decline significantly for Central China and East China was 1987 and 1990, respectively, while NDVI_u in West China remained relatively constant until 1998. NDVI_u changes in the Yangtze River Delta and the Pearl River Delta, two regions which has been undergoing the most rapid urbanization in China, also show different characteristics. The Pearl River Delta experienced a rapid decline in NDVI_u from the early 1980s to the mid-1990s; while in the Yangtze River Delta, NDVI_u did not decline significantly until the early 1990s. Such different patterns of NDVI_u changes are closely linked with policy-oriented difference in urbanization dynamics of these regions, which highlights the importance of implementing a sustainable urban development policy.     

Forest cover change and fragmentation using Landsat data in Maçka State Forest Enterprise in Turkey

In this study, Grey model (GM) and artificial neural network (ANN) were employed to predict suspended solids (SSeff) and chemical oxygen demand (CODeff) in the effluent from a wastewater treatment plant in industrial park of Taiwan. When constructing model or predicting, the influent quality or online monitoring parameters were adopted as the input variables. ANN was also adopted for comparison. The results indicated that the minimum MAPEs of 16.13 and 9.85% for SSeff and CODeff could be achieved using GMs when online monitoring parameters were taken as the input variables. Although a good fitness could be achieved using ANN, they required a large quantity of data. Contrarily, GM only required a small amount of data (at least four data) and the prediction results were even better than those of ANN. Therefore, GM could be applied successfully in predicting effluent when the information was not sufficient. The results also indicated that these simple online monitoring parameters could be applied on prediction of effluent quality well.     

Adapting forest health assessments to changing perspectives on threats—a case example from Sweden

A revised Swedish forest health assessment system is presented. The assessment system is composed of several interacting components which target information needs for strategic and operational decision making and accommodate a continuously expanding knowledge base. The main motivation for separating information for strategic and operational decision making is that major damage outbreaks are often scattered throughout the landscape. Generally, large-scale inventories (such as national forest inventories) cannot provide adequate information for mitigation measures. In addition to broad monitoring programs that provide time-series information on known damaging agents and their effects, there is also a need for local and regional inventories adapted to specific damage events. While information for decision making is the major focus of the health assessment system, the system also contributes to expanding the knowledge base of forest conditions. For example, the integrated monitoring programs provide a better understanding of ecological processes linked to forest health. The new health assessment system should be able to respond to the need for quick and reliable information and thus will be an important part of the future monitoring of Swedish forests.     

Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmaraş, Turkey

This study assessed land cover (LC) changes in Kahramanmara? (K.Mara?) and its environs by using multitemporal Landsat and ASTER imagery, respectively belong to 1989, 2000 and 2004. A priori defined nine land cover classes in the classification scheme were urban and built-up, forest, sparsely vegetated areas, grassland, vegetated stream beds, unvegetated stream beds, bare areas, crop fields, and water bodies. Individual classifications were employed using the combination of both unsupervised and supervised classification methods. Iterative Self Organizing Data Analysis (ISODATA) was used to reduce spectral variation in the scenes arising from complex pattern of crop fields. Maximum Likelihood classifier was used in the LC classification of the individual images. Image pairs of consecutive dates were compared by overlaying the thematic LC maps and cross-tabulating the LC statistics. Urbanization and expansion of agriculture were the major reasons for the dramatic LC conversions. The amount of conversion from crop fields to water occurred as large as 927.67 ha, accounting for 73% of the total land-to-water conversion. Conversions to agriculture have mainly been occurred from grasslands and sparsely vegetated areas as large as 1,314.95 and 1,325.84 ha, respectively. Urban coverage doubled in this period as a result of 1,443.45 ha of increase. Urban area increased in the second period from 2,920 to 3,526 ha. Conversions to agriculture occurred at high amounts. A total of 1,075.79 ha area changed from sparsely vegetated areas to crop fields. A landscape-level environmental monitoring scheme based on satellite remote sensing was proposed for effective environmental resource management.     

Grasslands changes in the Northern Songnen Plain,China during 1954–2000

Songnen Plain in Northeast China is one of the most significantly altered biological hotspots on Earth. Based on the information from integrated topographic maps, Landsat MSS, TM/ETM images and geographic information systems, grassland cover change, grassland fragmentation, agricultural reclamation, and saline–alkaline wasteland expansion in the region were investigated for the period of 1954 to 2000. The results showed that the native grassland decreased by 44.6 × 10⁴ ha and moderate density grassland decreased from 78.3 × 10⁴ to 20.3 × 10⁴ ha. Calculated from change dynamic model, the annual decrease rate of grassland was 1.1%.The distribution center of the grasslands illustrated a trend of shifting southeastward. The distance between centroids of grassland was 10.1 km. The numbers of grassland patch increased by 1,378, while the patch size of grasslands declined. Grassland experienced substantial clearing and fragmentation. The decreased grassland was converted into cropland, wetland, and saline–alkaline wasteland. The loss and degradation of grasslands was closely related to regional climate during the past 47 years. Population and livestock number increased significantly as grassland quality decreased. Intensive human activities including irrational reclamation and overgrazing may have accelerated the degradation of grasslands.     

Combining mapped and statistical data in forest ecological inventory and monitoring – supplementing an existing system

A forest ecological inventory and monitoring system combining information derived from maps and samples is proposed based on ecosystem regions (Bailey, 1994). The system extends the design of the USDA Forest Service Region 6 Inventory and Monitoring System (R6IMS) in the Pacific Northwest of the United States. The key uses of the information are briefly discussed and expected results are illustrated with examples. The system is flexible, allowing regions based on ecological considerations to be modified. Sampling intensities that are affordable are likely to be insufficient to provide meaningful estimates for key parameters relating to rare and endangered species, watersheds, and other ecological units. Methods are proposed for collecting additional information in follow-up surveys and combining it with relevant information obtained in R6IMS. Near-continuous information on weather and possible pollution variables recorded by instruments at sampling sites is needed to develop meaningful models to understand what is happening in the ecoregions. R6IMS and the proposed additions constitute a dynamic system which will be modified further as data are analyzed.     

Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in —Laikipia,of Kenya

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.     

Assessment of benthic changes during 20 years of monitoring the Mexican Salina Cruz Bay

In this work a non-parametric multivariate analysis was used to assess the impact of metals and organic compounds in the macro infaunal component of the mollusks benthic community using surface sediment data from several monitoring programs collected over 20 years in Salina Cruz Bay, Mexico. The data for benthic mollusks community characteristics (richness, abundance and diversity) were linked to multivariate environmental patterns, using the Alternating Conditional Expectations method to correlate the biological measurements of the mollusk community with the physicochemical properties of water and sediments. Mollusks community variation is related to environmental characteristics as well as lead content. Surface deposit feeders are increasing their relative density, while subsurface deposit feeders are decreasing with respect to time, these last are expected to be more related with sediment and more affected then by its quality. However gastropods with predatory carnivore as well as chemosymbiotic deposit feeder bivalves have maintained their relative densities along time.     

Ambient ozone injury to forest plants in Northeast and North Central USA: 16?years of biomonitoring

The US Forest Service administers a long-term, nationwide ozone biomonitoring program in partnership with other state and federal agencies to address national concerns about ozone impacts on forest health. Biomonitoring surveys begun in 1994 in the East and 1998 in the West provide important regional information on ozone air quality and a field-based record of ozone injury unavailable from any other data source. Surveys in the Northeast and North Central subregions cover 450 field sites in 24 states where ozone-sensitive plants are evaluated for ozone-induced foliar injury every year. Sites are typically large, undisturbed openings (>3 acres in size) close to forested areas where >3 bioindicator species are available for evaluation. Over the 16-year sampling period, injury indices have fluctuated annually in response to seasonal ozone concentrations and site moisture conditions. Sites with and without injury occur at all ozone exposures but when ambient concentrations are relatively low, the percentage of uninjured sites is much greater than the percentage of injured sites; and regardless of ozone exposure, when drought conditions prevail, the percentage of uninjured sites is much greater than the percentage of injured sites. Results indicate a declining trend in foliar injury especially after 2002 when peak ozone concentrations declined across the entire region.     

Assessing forest canopy closure in a geospatial medium to address management concerns for tropical islands—Southeast Asia

The present study outlines an approach to classify forest density and to estimate canopy closure of the forest of the Andaman and Nicobar archipelago. The vector layers generated for the study area using satellite data was validated with the field knowledge of the surveyed ground control points. The methodology adopted in this present analysis is three-tiered. First, the density stratification into five zones using visual interpretation for the complete archipelago. In the second step, we identified two island groups from the Andaman to investigate and compare the forest strata density. The third and final step involved more of a localised phytosociological module that focused on the North Andaman Islands. The results based on the analysis of the high-resolution satellite data show that more than 75% of the mangroves are under high- to very high-density canopy class. The framework developed would serve as a significant measure to forest health and evaluate management concerns whilst addressing issues such as gap identification, conservation prioritisation and disaster management—principally to the post-tsunami assessment and analysis.     

Changes in aquatic vegetation and floodplain land cover in the Upper Mississippi and Illinois rivers (1989–2000–2010)

Quantifying changes in the cover of river-floodplain systems can provide important insights into the processes that structure these landscapes as well as the potential consequences to the ecosystem services they provide. We examined net changes in 13 different aquatic and floodplain land cover classes using photo interpreted maps of the navigable portions of the Upper Mississippi River (UMR, above the confluence with the Ohio River) and Illinois River from 1989 to 2000 and from 2000 to 2010. We detected net decreases in vegetated aquatic area in nearly all river reaches from 1989 to 2000. The only river reaches that experienced a subsequent recovery of vegetated aquatic area from 2000 to 2010 were located in the northern portion of the UMR (above navigation pool 14) and two reaches in the Illinois River. Changes on the floodplain were dominated by urban development, which increased in nearly every river reach studied from 1989 to 2000. Agricultural lands declined in most river reaches from 2000 to 2010. The loss of agricultural land cover in the northern UMR was accompanied by increases in forest cover, whereas in the lower UMR and Illinois River, declines in agriculture were accompanied by increases in forest and shallow marsh communities. The changes in aquatic vegetation occupied between 5 and 20% of the total aquatic area and are likely associated with previously reported regional improvements in water clarity, while smaller (1–15% of the total floodplain area) changes in anthropogenic land cover types on the floodplain are likely driven by broad-scale socio-economic conditions.     

Assessment of flood-induced changes of phytoplankton along a river–floodplain system using the morpho-functional approach

In this research, we aimed to find out how the differences in hydrological connectivity between the main river channel and adjacent floodplain influence the changes in phytoplankton community structure along a river–floodplain system. The research was performed in the River Danube floodplain (Croatian river section) in the period 2008–2009 characterised by different flooding pattern on an annual time scale. By utilising the morpho-functional approach and multivariate analyses, the flood-derived structural changes of phytoplankton were analysed. The lake stability during the isolation phase triggered the specific pattern of morpho-functional groups (MFG) which were characterised by cyanobacterial species achieving very high biomass. Adversely, the high water turbulence in the lake during the frequent and extreme flooding led to evident similarity between lake and river assemblages. Besides different diatom species (groups of small and large centrics and pennates), which are the most abundant representatives in the river phytoplankton, many other groups such as cryptophytes and colonial phytomonads appeared to indicate altered conditions in the floodplain driven by flooding. Having different functional properties, small centric diatom taxa sorted to only one MFG cannot clearly reflect environmental changes that are shown by the species-level pattern. Disadvantages in using the MFG approach highlight that it is still necessary to combine it with taxonomical approach in monitoring of phytoplankton in the river–floodplain ecosystems.     

Evaluation of forest nutrition based on large-scale foliar surveys: are nutrition profiles the way of the future?

This paper introduces the use of nutrition profiles as a first step in the development of a concept that is suitable for evaluating forest nutrition on the basis of large-scale foliar surveys. Nutrition profiles of a tree or stand were defined as the nutrient status, which accounts for all element concentrations, contents and interactions between two or more elements. Therefore a nutrition profile overcomes the shortcomings associated with the commonly used concepts for evaluating forest nutrition. Nutrition profiles can be calculated by means of a neural network, i.e. a self-organizing map, and an agglomerative clustering algorithm with pruning. As an example, nutrition profiles were calculated to describe the temporal variation in the mineral composition of Scots pine and Norway spruce needles in Finland between 1987 and 2000. The temporal trends in the frequency distribution of the nutrition profiles of Scots pine indicated that, between 1987 and 2000, the N, S, P, K, Ca, Mg and Al decreased, whereas the needle mass (NM) increased or remained unchanged. As there were no temporal trends in the frequency distribution of the nutrition profiles of Norway spruce, the mineral composition of the needles of Norway spruce needles subsequently did not change. Interpretation of the (lack of) temporal trends was outside the scope of this example. However, nutrition profiles prove to be a new and better concept for the evaluation of the mineral composition of large-scale surveys only when a biological interpretation of the nutrition profiles can be provided.