Carbon storage and emissions offset potential in an African dry forest, the Arabuko-Sokoke Forest, Kenya

Concerns about rapid tropical deforestation, and its contribution to rising atmospheric concentrations of greenhouse gases, increase the importance of monitoring terrestrial carbon storage in changing landscapes. Emerging markets for carbon emission offsets may offer developing nations needed incentives for reforestation, rehabilitation, and avoided deforestation. However, relatively little empirical data exists regarding carbon storage in African tropical forests, particularly for those in arid or semi-arid regions. Kenya's 416 km(2) Arabuko-Sokoke Forest (ASF) is the largest remaining fragment of East African coastal dry forest and is considered a global biodiversity hotspot (Myers et al. 2000), but has been significantly altered by past commercial logging and ongoing extraction. Forest carbon storage for ASF was estimated using allometric equations for tree biomass, destructive techniques for litter and herbaceous vegetation biomass, and spectroscopy for soils. Satellite imagery was used to assess land cover changes from 1992 to 2004. Forest and thicket types (Cynometra webberi dominated, Brachystegia spiciformis dominated, and mixed species forest) had carbon densities ranging from 58 to 94 Mg C/ha. The ASF area supported a 2.8-3.0 Tg C carbon stock. Although total forested area in ASF did not change over the analyzed time period, ongoing disturbances, quantified by the basal area of cut tree stumps per sample plot, correlated with decreased carbon densities. Madunguni Forest, an adjoining forest patch, lost 86% of its forest cover and at least 76% of its terrestrial carbon stock in the time period. Improved management of wood harvesting in ASF and rehabilitation of Madunguni Forest could substantially increase terrestrial carbon sequestration in the region.     

Estimation of late twentieth century land-cover change in California

We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973?C2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km² and forest class at 4,722 km². Developed lands increased by 37.6%, composing an estimated 4.2% of the state??s land cover by 2000.     

Atmospheric Change, Forests and Biodiversity

Predicted atmospheric change, mainly climate change, will have profound effects on the biodiversity of Canadian forests. Predictions derived from forest models, responses of species and ecosystems related to modern ecological characteristics and paleoecological studies suggest large-scale, wide-ranging changes from the biome to physiological levels. Paleoecological analogues in B.C. and other parts of Canada reveal that major changes must be expected in forest composition, range, structure and ecological processes. In B.C., past warmer and drier climates supported a different forest pattern, including forest types with no modern analogue. This produced dramatically different disturbance regimes, specifically more fires, and affected tree growth rates. The relationship of forests with non-forest habitats, especially wetlands and grasslands was different suggesting implications for wildlife biodiversity. British Columbia's Forest Practices Code prescribes guidelines for biodiversity objectives but ignores the issue of atmospheric change. This omission may result from a lack of understanding of the profound potential effects of atmospheric change on forest biodiversity in the next harvest cycle and lack of mechanisms to assess impacts and develop management strategies for specific sites. An example of a simple paleoecological assessment method involving pollen ratios is proposed.     

Using landsat data to determine land use/land cover changes in Samsun, Turkey

The rapid industrialization and urbanization of an area require quick preparation of actual land use/land cover (LU/LC) maps in order to detect and avoid overuse and damage of the landscape beyond sustainable development limits. Remote sensing technology fits well for long-term monitoring and assessment of such effects. The aim of this study was to analyze LU/LC changes between 1980 and 1999 in Samsun, Turkey, using satellite images. Three Landsat images from 1980, 1987 and 1999 were used to determine changes. A post classification technique was used based on a hybrid classification approach (unsupervised and supervised). Images were classified into six LU/LC types; urban, agriculture, dense forest, open forest-hazelnut, barren land and water area. It is found that significant changes in land cover occurred over the study period. The results showed an increase in urban, open forest/hazelnut, barren land and water area and a decrease in agriculture and dense forest in between 1980 and 1999. In this period, urban land increased from 0.77% to 2.47% of the total area, primarily due to conversions from agricultural land and forest to a lesser degree. While the area of dense forest decreased from 41.09% to 29.64% of the total area, the area of open forest and hazelnut increased from 6.73% to 11.88%.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

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.     

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

Status of the Southern Carpathian forests in the long-term ecological research network

Air pollution, bulk precipitation, throughfall, soil condition, foliar nutrients, as well as forest health and growth were studied in 2006–2009 in a long-term ecological research (LTER) network in the Bucegi Mountains, Romania. Ozone (O₃) was high indicating a potential for phytotoxicity. Ammonia (NH₃) concentrations rose to levels that could contribute to deposition of nutritional nitrogen (N) and could affect biodiversity changes. Higher that 50% contribution of acidic rain (pH?<?5.5) contributed to increased acidity of forest soils. Foliar N concentrations for Norway spruce (Picea abies), Silver fir (Abies alba), Scots pine (Pinus sylvestris), and European beech (Fagus sylvatica) were normal, phosphorus (P) was high, while those of potassium (K), magnesium (Mg), and especially of manganese (Mn) were significantly below the typical European or Carpathian region levels. The observed nutritional imbalance could have negative effects on forest trees. Health of forests was moderately affected, with damaged trees (crown defoliation >25%) higher than 30%. The observed crown damage was accompanied by the annual volume losses for the entire research forest area up to 25.4%. High diversity and evenness specific to the stand type’s structures and local climate conditions were observed within the herbaceous layer, indicating that biodiversity of the vascular plant communities was not compromised.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Dynamics of land change: insights from a three-level intensity analysis of the Legedadie-Dire catchments,Ethiopia

Earlier studies on land change (LC) have focused on size and magnitude, gains and losses, or land transfers between categories. Therefore, these studies have failed to simultaneously show the complete LC processes. This paper examines LCs in the Legedadie-Dire catchments in Oromia State, Ethiopia, using land-category maps with intensity analysis (IA) at three points in time. We comprehensively analyze LC to jointly encompass the rate, intensity, transition, and process. Thirty-meter US Geological Survey (USGS) Landsat imagery from 1986, 2000, and 2015 (<?10% cloud) is processed using TerrSet-LCM and ArcGIS. Six categories are identified using a maximum likelihood classification technique: settlement, cultivation, forest, water, grassland, and bare land. Then, classified maps are superimposed on the images to statistically examine changes with an IA. Considerable changes are observed among categories, except for water, between 1986–2000 and 2000–2015. Overall land change occurred quickly at first and then slowly in the second time interval. The total land area that exhibited change (1st?≈?54% and 2nd?≈?51%) exceeded the total area of persistence (1st?≈?46% and 2nd?≈?49%) across the landscape. Cultivation and human settlements were the most intensively increased categories, at the expense of grassland and bare ground. Hence, when grassland was lost, it tended to be displaced by cultivation more than other categories, which was also true with bare land. Annual intensity gains were active for forest but minimal for cultivation, implying that the gains of forest were associated with in situ reforestation practices and that the gains in cultivation were caused by its relatively large initial area under a uniform intensity concept. This study demonstrates that IA is valuable for investigating LC across time intervals and can help distinguish dormant vs. active and targeted vs. avoided land categories.     

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.     

Quantification of forest fragmentation in pre- and post-establishment periods,inside and around Apuseni Natural Park,Romania

Protected areas (PAs) represent real cornerstones in the conservation of biodiversity and natural habitats. Their protection must be a priority today for each society. The enhanced socio-economic requirements increase the pressure upon protected areas, and the effect can result in a reduction of biodiversity. The aim of this study is to quantify forest fragmentation in the pre- (1986–2002) and post-establishment (2002–2016) periods, inside and around (buffer 1, buffer 2 and buffer 3) Apuseni Natural Park (ANP), Romania, using a series of classified Landsat satellite images and six landscape metrics. The results show that forest fragmentation occurred both in the pre- and post-establishment periods, inside and around ANP. Inside the park, the deforestation rate increased four times, from 0.03% year^?1 in the pre-establishment period to 0.14% year^?1 in the post-establishment period. Around the park, the deforestation rate decreased from 0.31% year^?1 in the pre-establishment period (buffer 1) to 0.10% year^?1 in the post-establishment period (buffer 1). Forest fragmentation resulted in an increase in the patch density and edge density, and a decrease in the total core area and mean patch size leading to isolation of patches and fragmentation of landscape, especially in ANP in the post-establishment period. Several measures can be taken in order to stop forest fragmentation inside and around ANP, including the education of buffer-zone communities, reforestation, enforcement of park regulations, and forest legislation.     

Trends in land use and land cover change in the protected and communal areas of the Zambezi Region,Namibia

Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984–1991 represented high deforestation and gradual increase in shrub land; (2) 1991–2000 and 2000–2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.     

A comparative assessment of land cover dynamics of three protected forest areas in tropical eastern Africa

Processes of deforestation, known to threaten tropical forest biodiversity, have not yet been studied sufficiently in East Africa. To shed light on the patterns and causes of human influences on protected forest ecosystems, comparisons of different study areas regarding land cover dynamics and potential drivers are needed. We analyze the development of land cover since the early 1970s for three protected East African rainforests and their surrounding farmlands and assess the relationship between the observed changes in the context of the protection status of the forests. Processing of Landsat satellite imagery of eight or seven time steps in regular intervals results in 12 land cover classes for the Kakamega–Nandi forests (Kenya) and Budongo Forest (Uganda) whereas ten are distinguished for Mabira Forest (Uganda). The overall classification accuracy assessed for the year 2001 or 2003 is similarly high for all three study areas (81% to 85%). The time series reveal that, despite their protection status, Kakamega–Nandi forests and Mabira Forest experienced major forest decrease, the first a continuous forest loss of 31% between 1972/1973 and 2001, the latter an abrupt loss of 24% in the late 1970s/early 1980s. For both forests, the temporally dense time series show short-term fluctuations in forest classes (e.g., areas of forest regrowth since the 1980s or exotic secondary bushland species from the 1990s onwards). Although selectively logged, Budongo Forest shows a much more stable forest cover extent. A visual overlay with population distribution for all three regions clearly indicates a relationship between forest loss and areas of high population density, suggesting population pressure as a main driver of deforestation. The revealed forest losses due to local and commercial exploitation further demonstrate that weak management impedes effective forest protection in East Africa.     

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

Effects of changing forest land definitions on forest inventory on the West Coast, USA

A key function of forest inventory is to detect changes in the area of forest land over time, yet different definitions of forest land are used in different regions of the world. Changes in the definition of forest intended to improve international consistency can affect the ability to quantify true changes over time. The objective of this study was to evaluate the effects of a definitional change from relative stocking to canopy cover on the area classified as forest land and its relationship to species and forest density in California, Oregon, and Washington. Both western Juniper and ponderosa pine will yield higher estimates of forest land area using a canopy cover definition in comparison to a stocking-based definition, with the difference being most pronounced where land is marginally forested. The change in definition may result in an additional 146,000 ha of forest land identified on the West Coast. Measuring marginal forest lands with both metrics for the first cycle after implementation should make it possible to distinguish real change from definitional change.     

Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey

Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yaln?zçam and U?urlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS^TM. As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.     

Use of object-oriented classification and fragmentation analysis (1985�C2008) to identify important areas for conservation in Cockpit Country, Jamaica

Forest fragmentation is one of the most important threats to global biodiversity, particularly in tropical developing countries. Identifying priority areas for conservation within these forests is essential to their effective management. However, this requires current, accurate environmental information that is often lacking in developing countries. The Cockpit Country, Jamaica, contains forests of international importance in terms of levels of endemism and overall diversity. These forests are under severe threat from the prospect of bauxite mining and other anthropogenic disturbances. In the absence of adequate, up-to-date ecological information, we used satellite remote sensing data and fragmentation analysis to identify interior forested areas that have experienced little or no change as priority conservation sites. We classified Landsat images from 1985, 1989, 1995, 2002, and 2008, using an object-oriented method, which allowed for the inclusion of roads. We conducted our fragmentation analysis using metrics to quantify changes in forest patch number, area, shape, and aggregation. Deforestation and fragmentation fluctuated within the 23-year period but were mostly confined to the periphery of the forest, close to roads and access trails. An area of core forest that remained intact over the period of study was identified within the largest forest patch, most of which was located within the boundaries of a forest reserve and included the last remaining patches of closed-broadleaf forest. These areas should be given highest priority for conservation, as they constitute important refuges for endemic or threatened biodiversity. Minimizing and controlling access will be important in maintaining this core.     

Vegetation, Soil, and Animal Indicators of Rangeland Health

We studied indicators of rangeland health on benchmark sites with long, well documented records of protection from stress by domestic livestock or histories of environmental stress and vegetation change. We measured ecosystem properties (metrics) that were clearly linked to ecosystem processes. We focused on conservation of soil and water as key processes in healthy ecosystems, and on maintenance of biodiversity and productivity as important functions of healthy ecosystems. Measurements from which indicators of rangeland health were derived included: sizes of unvegetated patches, cover and species composition of perennial grasses, cover and species composition of shrubs and herbaceous perennials, soil slaking, and abundance and species composition of the bird fauna. Indicators that provided an interpretable range of values over the gradient from irreversibly degraded sites to healthy sites included: bare patch index, cover of long-lived grasses, palatability index, and weighted soil surface stability index. Indicators for which values above a threshold may serve as an indicator of rangeland health include: cover of plant species toxic to livestock, cover of exotic species, and cover of increaser species. Several other indicator metrics were judged not sensitive nor interpretable. Examples of application of rangeland health indicators to evaluate the success of various restoration efforts supported the contention that a suite of indicators are required to assess rangeland health. Bird species diversity and ant species diversity were not related to the status of the sample site and were judged inadequate as indicators of maintenance of biodiversity.