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Recently, as global climate change and local disturbances such as wildfires continue, long- and short-term changes in the high-latitude vegetation systems have been observed in various studies. Although remote sensing technology using optical satellites has been widely used in understanding vegetation dynamics in high-latitude areas, there has been limited understanding of various landscape changes at different spatiotemporal scales, their mutual relationships, and overall long-term landscape changes. The objective of this study is to devise a change monitoring strategy that can effectively observe landscape changes at different spatiotemporal scales in the boreal ecosystems from temporally sparse time series remote sensing data. We presented a new post-classification-based change analysis scheme and applied it to time series Landsat data for the central Yakutian study area. Spectral variability between time series data has been a major problem in the analysis of changes that make it difficult to distinguish long- and short-term land cover changes from seasonal growth activities. To address this issue effectively, two ideas in the time series classification, such as the stepwise classification and the lateral stacking strategies were implemented in the classification process. The proposed classification results showed consistently higher overall accuracies of more than 90% obtained in all classes throughout the study period. The temporal classification results revealed the distinct spatial and temporal patterns of the land cover changes in central Yakutia. The spatiotemporal distribution of the short-term class illustrated that the ecosystem disturbance caused by fire could be affected by local thermal and hydrological conditions of the active layer as well as climatic conditions. On the other hand, the long-term class changes revealed land cover trajectories that could not be explained by monotonic increase or decrease. To characterize the long-term land cover change patterns, we applied a piecewise linear model with two line segments to areal class changes. During the former half of the study period, which corresponds to the 2000s, the areal expansion of lakes on the eastern Lena River terrace was the dominant feature of the land cover change. On the other hand, the land cover changes in the latter half of the study period, which corresponds to the 2010s, exhibited that lake area decreased, particularly in the thermokarst lowlands close to the Lena and Aldan rivers. In this area, significant forest decline can also be identified during the 2010s. [ABSTRACT FROM AUTHOR]

This paper reports a study of bioclimatic dynamics and land use in the region of Tlemcen (north-west of Algeria). GIS (geographic information system) and satellite images (LandSat) were used to conduct a diachronic study based on a series of satellite images from the years 2000 and 2019 to demonstrate changes in the study area while highlighting the importance of environmental conditions, including climate and anthropogenic impact on dynamic vegetation cover. Bioclimatic synthesis has shown an improvement in the rainfall regime and an evolution towards higher bioclimatic atmospheres between the two periods (1985–1999) and (2004–2018). Land use in the study area is under the influence of strong anthropogenic pressures and is experiencing a decline in forest areas from 28.74 to 17.49% but also in agricultural land and lawns from 38.61% to 27.67% in favour of built-up areas which increased from 0.81% to 1.09% but mainly to the benefit of bare soil: an ultimate stage of degradation whose surface area increased from 31.59% in 2000 to 53.46% in 2019. [ABSTRACT FROM AUTHOR]

Globally, animals that are range-restricted are frequently becoming species of conservation concern, in part due to competitive exclusion by phylogenetically and ecologically similar species that are more tolerant of human disturbance. However, climate and land use changes to natural landscapes can create pockets of refugia for range-restricted species. Western gray squirrels (Sciurus griseus) are native to the west coast of North America, principally California and western Oregon. Over the past several decades, Western Gray Squirrel populations have declined in human-dominated areas, with increased competition from introduced congeneric species native to eastern North America cited as a primary driver. Despite declines in their established range west of the Pacific Crest in western North America, western gray squirrels are extending their range into the Great Basin, where they were not historically found. Using a network of remote camera traps deployed across the Sierra Nevada–Great Basin ecotone in northwestern Nevada, we detected western gray squirrels across 16 of 100 camera-trapping sites. The majority of detections were located in piñon–juniper woodland, a land cover type not previously occupied by this species. Occupancy modeling revealed that western gray squirrels were equally likely to occur in piñon–juniper woodland compared to mature pine forest that they occupy elsewhere in their range. A species distribution model parameterized with historical gray squirrel observations (pre-1950), indicated increased climatic suitability for the species on the eastern side of the Sierra Nevada in recent decades, which may have facilitated this range expansion. Our findings reveal the potential for species declining in their historical range to colonize novel habitats that become increasingly suitable as a result of human-driven changes to ecosystems. [ABSTRACT FROM AUTHOR]

In recent years, Togo's protected areas have been subject to a worrying process of anthropisation. This has led to a decline in forest ecosystems, their biodiversity and their functions. The general objective of this study is to assess the state of conservation of the classified forest of Amou-Mono between 1986 and 2021. More specifically, it aims to: (i) characterize the dynamics of land use from 1986, 2000, 2013 and 2021 and, (ii) assess the impact of changes in land use on the potential for carbon sequestration. A multi-date classification of Landsat images for the years 1986, 2000, 2013 and 2021 made it possible to quantify and assess changes in occupation. The dynamics of land use between 1986 and 2021 is mainly reflected by a regression of dense/riparian forests (81.40%) and open forests/wooded savannahs (67.79%) and the progression of wooded/shrubby Savannah (172.93%). Anthropogenic formations: Fields/fallow and Agglomerations/Bare soils, absent in 1986, occupy in 2021 respective proportions of 38.1 % and 2.19%. Human activities, particularly logging and agricultural clearing, are causing fragmentation and regression of forest ecosystems. Unless action is taken to reverse the trend, the conservation of biodiversity and ecosystem functions in this classified forest will be increasingly threatened. [ABSTRACT FROM AUTHOR]

Soil erosion poses an environmental threat to the ecosystem functions. Land use and land cover (LULC) changes are largely responsible for soil erosion severity. This study aimed to evaluate the impacts of LULC on soil erosion and erosion distribution in the Laonung watershed over the study period (1995–2016). To model the response of soil erosion to LULC changes, a physiographic soil erosion–deposition (PSED) model is employed, which incorporates Geographic Information Systems (GIS) with rain-runoff models and erosion–deposition models. The results revealed that over a three period (1995, 2008 and 2011), agricultural land, grassland, bare land, water bodies, and other land uses increased, whereas forest land declined by 11,424 × 104 m2 (2008 relative to 1995) and 16,159 × 104 m2 (2011 relative to 1995). In addition to the land use, landslide was considered as a land cover in this study. As landslides dramatically alter the land cover dynamics of mountainous regions in Taiwan. The landslide areas substantial changed over the period 2003 to 2016 (847 × 104 m2–9474 × 104 m2). The significant increase in landslide area together with the abrupt dynamics in LU severely aggravated soil erosion. Compared with the period of primeval forest, total soil erosion increased from 29,295 × 104 m3 to 102,597 × 104 m3 (1995–2011 LU) and 205,833 × 104 m3 (LULC). The study has illustrated how LULC changes strongly affects soil erosion. [ABSTRACT FROM AUTHOR]

Land use/cover change (LULCC) is an integral part of global environmental change and is influenced by both natural and socioeconomic factors. This study aims to comprehensively analyze land use and land cover (LULC) in Kwazulu-Natal and Mpumalanga provinces in eastern South Africa from 1995 to 2020 and to identify the driving force behind LULCC. Utilizing Landsat series satellite imagery as a data source and based on the Google Earth Engine (GEE) platform and eCognition software 9.0, two different classification methods, pixel-based classification and object-oriented classification, were adopted to gather LULC data every five years. The spatiotemporal characteristics of the data were then analyzed. Using an optimal parameter-based geodetector (OPGD), this study explored the driving factors of LULCC in this region. The results show the following: (1) Of the two classification methods examined, the object-oriented classification had higher accuracy, with an overall accuracy of 80–90%. The pixel-based classification had lower accuracy, with an overall accuracy of 62.33–72.14%. (2) From 1995 to 2020, the area of farmland in the study area showed a fluctuating increase, while the areas of forest and grassland declined annually. The area of constructed land increased annually, whereas the areas of water and unused land fluctuated over time. (3) Socioeconomic factors generally had greater explanatory power than natural factors, with population growth and economic development being the main drivers of LULCC in the region. This study provides a reliable scientific basis for the formulation of sustainable land resource development strategies in the area, as well as for the management and implementation of urban and rural planning, ecological protection, and environmental governance by relevant departments. [ABSTRACT FROM AUTHOR]

Spatially explicit reconstruction of historical land cover change is a prerequisite for a more comprehensive understanding of environmental changes. Anthropogenic activities have dramatically altered the land cover of the conterminous United States (CONUS), encroaching heavily on the primary vegetation. However, few datasets exist that depict the historical trajectory of forest and grassland cover changes in CONUS over the last millennium, and previous efforts have only focused on reconstructions for the last four centuries. By integrating remote sensing-derived land use/cover change (LUCC) data and potential vegetation data, we determined the potential extent of natural forest (PENF) and grassland (PENG) in CONUS. Based on a qualitative analysis of the trends and driving forces of forest and grassland changes, we devised a method of subtracting reconstructed historical cropland (1000–2000 AD) and built-up land (1850–2000 AD) from PENG and PENF to reconstruct a 5 min × 5 min grid dataset of forest and grassland cover at 13 time-points over the past millennium. The results showed that forest and grassland cover in CONUS underwent a slow decline (1000–1600 AD), an accelerated decline (1600–1800 AD), a dramatic decline (1800–1950 AD), and finally, a recovery (1950–2000 AD) over the study period. The modelled forest fraction decreased from 49% in 1000 AD to 33% in 2000 AD, representing a 32% area reduction, whereas the modelled grassland fraction decreased from 37% to 22%, representing a 42% area reduction. The reduction occurred primarily in the last 200 years, with forest and grassland reductions accounting for 86% and 97% of the total reduction over the millennium, respectively. Spatially, more than 80% of the land was originally covered by forests and grasslands, and the loss occurred mainly in the eastern CONUS and Great Plains over the past millennium. After the 1930s, farmland abandonment began in central and eastern CONUS, simultaneously with environmental protection laws. Federal government regeneration programs for forest and grassland resources and the Shelterbelt Project all contributed to a slowdown in forest and grassland decline and recovery in cover. [ABSTRACT FROM AUTHOR]

Land use and land cover (LULC) is a major concern of global environmental change, particularly the case, in developing countries. In the Central Ethiopian Rift Valley (CRV), unprecedented changes in LULC have been observed over the last decades. This study aims to scrutinize the dynamics of the CRV over a timespan of three decades (1984–2013). Satellite imageries were acquired from Multispectral Scanner System, Thematic Mapper, and Enhanced Thematic mapper for the years 1984, 1995, and 2013 respectively. The data were obtained from the United States Geological Survey and Ethiopian Geospatial Information Institute. In addition, Focus Group Discussions and Key Informants Interviews were undertaken to support analysis and interpretation of LULC anomalies, identify drivers, and associated impacts. Geospatial technologies were used to analyze the extent of LULC change across the study period. An object-oriented supervised classification and a change detection technique were applied to compartmentalize the change into six LULC classes. Results revealed that farmlands and built-up areas have shown continuous progressive expansion at the expense of bareland and forestland. Farmland and built-up area in 1984 were expanded from 33.3% and 2.6% to 40.6% and 8.2% in 2013, respectively. In contrast, forestland and bareland coverages in 1984 were dwindled from 11.7% and 17.7% to 4.2% and 10.1% in 2013, respectively. Comparatively, shrubland and waterbody were also slightly augmented by 1.9% and 0.2% from 1984 to 2013. Therefore, the result suggested that policymakers and development actors must take appropriate actions to minimize the progressive decline of forest cover in the milieu. [ABSTRACT FROM AUTHOR]

In the last 50 years, forest disturbances, caused mainly by insect outbreaks and windstorms, had a significant impact on the subalpine Norway spruce (Picea abies (L.) H. Karst.) stands across Europe. The high intensity of these factors often led to complete dieback of existing forest stands, as in Gorce National Park (Southern Poland). The aim of this study was to monitor land cover changes in subalpine Norway spruce stands and their dynamics in Gorce NP in the years 1977–2020 (43 years), with the use of archival remote sensing data. The study area was divided into two subareas: A—the Kudłoń and B—the Jaworzyna range. Changes were tracked in six defined land cover classes, based on available aerial orthophotos and Landsat (NASA) imagery, with the help of the authors' photointerpretation key. The results showed that almost 50% of old-growth Norway spruce stands died in the analyzed time period (50.9% in subarea A; 48.8% in subarea B). However, young forests appeared in almost 17% of the study area (20.7% and 14.2% in subarea A and B, respectively). The dynamics of land cover changes were different for the analyzed subareas; in subarea A Norway spruce dieback processes weakened at the end of the analyzed time period, whereas in subarea B they maintained high intensity. The process of old-growth Norway spruce stands dieback is still occurring in Gorce NP, but it does not result in the disappearance of the whole subalpine spruce forest ecosystem but is rather a generational change, due to emerging young forests. [ABSTRACT FROM AUTHOR]

Our knowledge about the Holocene vegetation changes in southern China has been based on the inference from pollen percentages. However, the relationship between pollen percentages and vegetation is non-linear. This may lead to significant bias in real vegetation cover and limit our understanding of land cover changes and its relation to climate and human activities. Here we quantitatively reconstruct past regional land-cover changes by applying the REVEALS model to four pollen records collected from two study areas in southern and middle subtropical zones. The two study areas, representing the Pearl River Basin (PRB) and Wuyi Mountain (WYM), are located in spatial gradients, thus help to elucidate not only the climate forcing, but also the spatio-temporal spread of agriculture in this region. The REVEALS reconstruction shows a clear difference from original pollen percentages and is considered more realistic in depicting regional vegetation changes. Based on more reasonable reconstruction result by excluding wetland-associated taxa, i.e., Cyperaceae and Alnus , we found a gradual decline of forest covers since the middle Holocene which may be related to the reduced rainfall in response to the weakening East Asian Summer Monsoon. The human impact on the forest cover was identified by an abrupt increase of Poaceae cover at 3500–2700 cal yr B.P. in the PRB area, which appeared later in the WYM mountainous area. Thus, our study reveals a progressive expansion of anthropogenic activities from the coastal lowlands to mountainous areas. [ABSTRACT FROM AUTHOR]

The rapid expansion of agriculture and human settlements has simplified natural ecosystems and harmed the earth's biodiversity. The current study was conducted in south-central Ethiopia to identify LULC change dynamics, and analysis of their driving force using geospatial technology. A supervised maximum likelihood image classification method was employed in combination with the visual interpretation of satellite images to categorise and map LULC classes of the study landscape. Semi-structured interviews, field observations, key informants, and Focus Group Discussions (FGDs) were employed to identify major driving forces, periodic LULC changes and impacts. The classification result showed a considerable decline in forestland from (43.1%) in 1973 to (13.1%) in 2000. Similarly, grasslands declined from (45.5%) in 1973 to (6.3%) in 2018. On the other hand, cropland has increased from (9.24%) in 1973 to (32.04%) in 1986 likewise between 2000 and 2018 its coverage was augmented from 45.4% to 51.1%, respectively.. Local communities perceived population growth, settlement, urbanisation, expansion of farmlands, and fuel wood collection as dominant drivers of LULC changes in the study area in thewatershed. The respondents also observed that the decline in forest LULC triggered the loss of biodiversity, soil fertility, and water availability. Hence, local and national regimes must take adequate measures to minimise the rapid shift in land use and to balance the protection of the human livelihood with the environment. [ABSTRACT FROM AUTHOR]

Land includes vegetation and water bodies and provides the basis for human livelihoods through primary production, food and freshwater supply, and multiple other ecosystem services. The last three decades have recorded frequent drought events as well as rapid population growth, which has often resulted in adverse land use and land cover change (LULCC) in the Sahel of Sub-Saharan Africa. In order to propose sustainable land management strategies, it is a prerequisite to investigate the rate of LULCC and its driving factors in specific locations. This study investigated the case of Wacoro municipality in Mali using a combined approach of remote sensing, Geographic Information Systems, and focus group discussions. Satellite images and local people's perceptions on LULCC and drivers were collected and analyzed for the years 1990, 2000, 2010, and 2020. We found that the study area faced a rapid decrease in wooded savannah that was degraded and converted to shrub savannah and later to farmland and settlement. Changes were directly or indirectly related to the rapid population growth, high cotton price (which encouraged cropland expansion), drought, firewood extraction, and charcoal production, which was exacerbated by poverty. We suggest promoting integrated land management strategies that consider current and future livelihood needs and preserve the environment for the benefits of future generations. New agricultural policies, such as cotton price incentives, should always be accompanied by an assessment of their potential environmental impacts and design of adequate mitigation measures. [ABSTRACT FROM AUTHOR]

Addressing undesirable changes associated with the driving forces of land use cover change are critical to sustainable land management, and the future modeling of land use systems in developing countries. The study accentuates local drivers of land use cover change in Southwestern Ghana using a mixed-method approach. The approach aided in identifying key land-use drivers, using different research strategies for comparisons through confidence level analysis and Analytic Hierarchy Process. We used expert interviews, existing literature and geostatistical tools to ascertain the driving forces triggering such unprecedented changes. Landsat imagery 5 MSS, 4 and 5 TM, 7 ETM + and 8 OLI/TIRS were acquired from the United States Geological Survey's website. Land-use analysis revealed a decline in forests (− 82.41%) and areas covered by waterbodies (− 27.39%). A fundamental drift in built-up (+ 1288.36%) and farmlands/shrubs (+ 369.81%) areas were also observed. The contribution rate of change analysis revealed built-environment and increasing population contributed the most to surface temperature and land-use change. A steady increase in surface temperature can be attributed to the undesirable changes associated with land-use systems over the past 50 years. Socio-economic development in Southwestern Ghana is fuelling interest in studies related to land use cover change. Biophysical, cultural and technological factors are considered key drivers despite the "medium-to-very low confidence" in results generated. They could potentially impact climate-sensitive sectors that significantly modify land-use systems from the pessimists' and optimists' perspectives. Standpoints established through this study will enrich basic datasets for further studies at the continental level. [ABSTRACT FROM AUTHOR]

The wet evergreen forest ecological zone of Ghana is undergoing notable structural changes, although most maps erroneously depict the area to be an intact forest. Several hectares of plantation agriculture such as rubber, oil palm, and cocoa are replacing the natural vegetation and habitats, thereby threatening indigenous biodiversity. This study aimed to assess the effects of tree monocrop proliferation on landscape transitions between 1986 and 2020 in the Wassa East District of Ghana. The ISODATA clustering technique was used to produce land cover category maps from Landsat images of 1986, 2002, and 2020. A post-classification change detection technique resulted in transition matrices which were used for the computation of land cover transition intensities over 34 years. The results showed that the landscape was dominated by forests in 1986. Still, the forest continuously declined by 34% (1% annually) in 2020 while all other land cover types increased in both periods with cocoa covering 23% oil palm covering 14%, and rubber covering 2% of the land area. These conversions in the land area are important, especially since the closed forests usually transition to monocrops through the intermediate process: food crop farming. This information is essential for decision making on land development and biodiversity conservation. [ABSTRACT FROM AUTHOR]

Land cover change for agriculture is thought to be a major threat to global biodiversity. However, its ecological impact has rarely been quantified in the Northern Hemisphere, as broad-scale conversion to farmland mainly occurred until the 1400s–1700s in the region, limiting the availability of sufficient data. The Ishikari Lowland in Hokkaido, Japan, offers an excellent opportunity to address this issue, as hunter–gatherer lifestyles dominated this region until the mid-nineteenth century and land cover maps are available for the period of land cover changes (i.e. 1850–2016). Using these maps and a hierarchical community model of relationships between breeding bird abundance and land cover types, we estimated that broad-scale land cover change over a 166-year period was associated with more than 70% decline in both potential species richness and abundance of avian communities. We estimated that the abundance of wetland and forest species declined by greater than 88%, whereas that of bare-ground/farmland species increased by more than 50%. Our results suggest that broad-scale land cover change for agriculture has led to drastic reductions in wetland and forest species and promoted changes in community composition in large parts of the Northern Hemisphere. This study provides potential baseline information that could inform future conservation policies. [ABSTRACT FROM AUTHOR]

Evaluation of Land Use Land Cover (LULC) changes play a vital role in understanding the landscape dynamics that have been influencing climate, biodiversity, hydrology, and ecology of a region. The information of temporal LULC aids decision-makers in framing sustainable land use policies for nature conservation. Anthropogenic pressure, especially unplanned developmental activities, has contributed towards fragmenting contiguous forests, thus affecting their structure and loss of habitat for endemic taxa. LULC changes in the Bellary district, Karnataka have been assessed through temporal remote sensing data. Classification of remote sensing data for estimating the spatial extent of land uses has been done through supervised machine learning algorithms namely random forest (RF), support vector machine (SVM), and parametric maximum likelihood classifier (MLC). The performance of these algorithms was evaluated through accuracy assessments. Results reveal that RF has the highest overall accuracy (88.94%) and Kappa value (0.76) compared to overall Kappa of MLC (85.51%, 0.74) and SVM (85.47%, 0.63). Based on this, RF was considered for temporal data analyses, which highlighted the decline of forest cover from 2.61% (1973) to 0.74% (2022). The built-up has increased from 0.27% (1973) to 2.43% (2022), and agriculture from 68.21% (1973) to 84.95% (2022). Fragmentation of contiguous forests is evident from the decline in the interior or intact forests from 6.73% (1973) to 2.41% (2022) and the increase in the non-forest areas such as built-up, agriculture, etc., amounting now to 89.81%. Results highlight the need for immediate policy interventions for the conservation and protection of the remnant forest patches. [ABSTRACT FROM AUTHOR]

The Accra Plain of Ghana is experiencing rapid urbanization, but there is scant information on its impact on local biodiversity. We assessed the changes in land use/land cover of the Accra Plain since 1991 and evaluated how the observed changes have influenced local small mammals in forest fragments. We applied supervised classification and intensity analysis time-series Landsat imagery data to assess land use/land cover changes between 1991 and 2017. Small mammals were surveyed in two forest fragments, the Pinkwae and Adumanya forests from June 2019 to January 2020, using capture-mark-recapture technique. We compared our data with baseline data gathered in 1991–1992, when large areas of the city remained mostly undeveloped. Our data revealed that the urban area has increased by 832%, while the forest area declined by 85% between 1991 and 2017. The Pinkwae and Adumanya forests, which covered 120 and 1.5 ha, respectively, in 1991 have each been reduced to < 1 ha. We found changes in the small mammal species composition in the forest fragments, but not species richness due to species turnover. Grammomys poensis and Dephomys defua are first records for the Accra Plain. Our data suggested that small forest fragments within the urbanizing landscape are important for maintaining the local small mammal species. For the conservation of local small mammals in urbanizing landscapes, it is important to maintain the greatest possible number of small forest fragments and establish policies that prevent forest remnants from being further depleted. [ABSTRACT FROM AUTHOR]

Delivery of ecosystem services is strongly affected by changes in the land use/land cover (LULC) of an area. In this study, we analyze spatiotemporal changes in LULC of the rapidly changing Bagmati River Basin (BRB) of Nepal during 1988–2018 using Landsat satellite images. We also quantify carbon storage in different physiographic regions and LULC classes using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and assess economic valuation of carbon using the benefit transfer method. According to our analysis, there were increases in urban/built-up (247.5%), barren land (109.5%), shrub land (32.4%), and declines in forest cover (− 6.2%), cultivated land (− 4.1%), waterbodies (− 30.3%), sand (− 29.2%), and grass cover (− 10.6%) during the study period. As a result of these changes in LULC, carbon storage declined from 31.4 million tons year−1 in 1988 (worth 157.0 million USD) to 30.8 million tons year−1 (154.1 million USD) in 2018 with the total loss of 2.9 million USD. The largest decline in stored carbon was observed in Tarai and Dun valleys, from 6.8 to 6.5 million tons (− 1.4 million USD) followed by Churia, from 7.8 to 7.6 million tons (- 1.1 million USD). Increases in carbon storage were observed in urban/built-up and shrub land areas and declines in cultivated land, forest, barren land, waterbodies and grass land. The results of LULC change and estimated carbon stock in BRB provides a baseline for planners and policy makers to formulate appropriate plans to sustainably manage the region's land cover and to mitigate carbon loss. [ABSTRACT FROM AUTHOR]

Restoring degraded forest is essential if we are to reduce human pressure on natural ecosystems and their biodiversity. Forests were nationalized in 1957 in Nepal and as a consequence, forest cover declined from 45% in 1964 to just 29% in 1994. However, as its response, sectoral plans and policies, particularly introduction of community-based forest management programs since the 1980s and conservation activities resulted in large scale forest cover restoration. Here, we examined the forest cover change in the Gandaki River Basin (GRB), the catchment with the largest altitudinal variation (ranging from ± 93 to 8167 m) and environmental and ecological significance. To see how forests have changed since then, we analyzed snapshots of spatiotemporal, ecological and physiographic changes in forest cover, and forest type at decadal intervals from 1996 to 2016 using Landsat 5 and 8 satellite images. We observed an overall gain in forest cover of 207 km2, from 7571 km2 (34.4% of the total area) in 1996 to 7778 km2 (35.3%) in 2016. Of the 21 forest cover types identified, the greatest forest coverage during 2016 was of Schima-Castanopsis forest (25.9%) and hill sal forests (16.4%). In terms of physiographic zones, land below 500 m (Tarai) where most people live, witnessed gradual declines in forest cover, in contrast to large increases in forests above 500 m. Historical examination of forest cover at ecological and physiographic scales helps to identify the elevation-wise distribution of forest resources, vegetation composition, ecosystem characteristics, anthropogenic pressure upon vegetation, and hence the overall influence of LULC upon the environment. These outputs will assist planners, policy makers, and researchers in their formulation of effective basin wide plans and policies to ensure the protection of basin level biodiversity and ecosystem function. [ABSTRACT FROM AUTHOR]

Agricultural, forestry‐impacted and natural catchments are all vectors of nutrient loading in the Nordic countries. Here, we present concentrations and fluxes of total nitrogen (totN) and phosphorus (totP) from 69 Nordic headwater catchments (Denmark: 12, Finland:18, Norway:17, Sweden:22) between 2000 and 2018. Catchments span the range of Nordic climatic and environmental conditions and include natural sites and sites impacted by agricultural and forest management. Concentrations and fluxes of totN and totP were highest in agricultural catchments, intermediate in forestry‐impacted and lowest in natural catchments, and were positively related %agricultural land cover and summer temperature. Summer temperature may be a proxy for terrestrial productivity, while %agricultural land cover might be a proxy for catchment nutrient inputs. A regional trend analysis showed significant declines in N concentrations and export across agricultural (−15 μg totN L−1 year−1) and natural (−0.4 μg NO3‐N L−1 year−1) catchments, but individual sites displayed few long‐term trends in concentrations (totN: 22%, totP: 25%) or export (totN: 6%, totP: 9%). Forestry‐impacted sites had a significant decline in totP (−0.1 μg P L−1 year−1). A small but significant increase in totP fluxes (+0.4 kg P km−2 year−1) from agricultural catchments was found, and countries showed contrasting patterns. Trends in annual concentrations and fluxes of totP and totN could not be explained in a straightforward way by changes in runoff or climate. Explanations for the totN decline include national mitigation measures in agriculture international policy to reduced air pollution and, possibly, large‐scale increases in forest growth. Mitigation to reduce phosphorus appears to be more challenging than for nitrogen. If the green shift entails intensification of agricultural and forest production, new challenges for protection of water quality will emerge possible exacerbated by climate change. Further analysis of headwater totN and totP export should include seasonal trends, aquatic nutrient species and a focus on catchment nutrient inputs. [ABSTRACT FROM AUTHOR]

Tropical forest regions in equatorial Africa are threatened with degradation, deforestation and biodiversity loss as a result of land-cover change. We investigated historical land-cover dynamics in unprotected forested areas of the Littoral Region in south-western Cameroon during 1975–2017, to detect changes that may influence this important biodiversity and wildlife area. Processed Landsat imagery was used to map and monitor changes in land use and land cover. From 1975 to 2017 the area of high-value forest landscapes decreased by c. 420,000 ha, and increasing forest fragmentation caused a decline of c. 12% in the largest patch index. Conversely, disturbed vegetation, cleared areas and urban areas all expanded in extent, by 32% (c. 400,000 ha), 5.6% (c. 26,800 ha) and 6.6% (c. 78,631 ha), respectively. The greatest increase was in the area converted to oil palm plantations (c. 26,893 ha), followed by logging and land clearing (c. 34,838 ha), all of which were the major factors driving deforestation in the study area. Our findings highlight the increasing threats facing the wider Littoral Region, which includes Mount Nlonako and Ebo Forest, both of which are critical areas for regional conservation and the latter a proposed National Park and the only sizable area of intact forest in the region. Intact forest in the Littoral Region, and in particular at Ebo, merits urgent protection. [ABSTRACT FROM AUTHOR]

Land use is a dynamic phenomenon, changing with time and space. Land use/land cover (LULC) information and its periodic changes has become crucial to carry out the prediction to the dynamical change of land use. This study analyzed the spatial and temporal changes in land use that has taken place in Nagaland over the last 10 years (2005–2016). It has been observed that the dynamic change in land use and land cover has been mainly caused by the traditional practice of jhum cultivation, also known as shifting cultivation in Nagaland, which constitute about 81% of the total agricultural land. As a result, there is a decline in forest area by 593.87 km2 (5.66%) from 2005–2006 to 2015–2016. Concurrently, abandoned jhum land and scrubland has increased by 11.72% and 24.89%, demonstrating the decreased in jhum/ shifting cultivation cycle. The loss of forest in the last decade was attributed to ever increasing population, putting pressure on demand of jhum/ shifting cultivation and other anthropogenic activities. The degradation of forest is ever increasing, which calls for intervention of appropriate technology and holistic approach to address this issue. [ABSTRACT FROM AUTHOR]

The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001 to 2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error (SE) was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001 and 2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this period. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001–2006 at twice the rate of 2011–2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database. [ABSTRACT FROM AUTHOR]

After the year 2010, a century of rapid decline in Philippine forest cover was reversed due to a deliberate National Greening Program (NGP). Drivers that can sustain or counter this increase can be better investigated through the help of land change models. However, such models are not yet in mainstream use for planning in the Philippines. Hence, this study used two models – FOREST-SAGE and GEOMOD – to simulate forest conditions based on anthropogenic drivers and to evaluate model applicability in the Philippines. The performance of each model was assessed using the root-mean-square error (RMSE), mean absolute error (MAE), Kappa, national average tree cover percentage, and common deforestation hotspots with reference datasets. Validation with Climate Change Initiative Land Cover dataset (CCI-LC) yielded similar results between the models: 2015 tree cover maps with RMSE of 22–25% tree cover, MAE of 10–12% tree cover, and moderate agreement with reference map based on Kappa (0.4–0.6); and 2010–2015 change maps with RMSE of 8–9% tree cover, MAE of 1–2% tree cover, and agreement due to chance based on Kappa (0.01–0.03). Validation with MODerate Resolution Imaging Spectroradiometer-Vegetation Continuous Field (MODIS-VCF) maps yielded similar MAE results (10% tree cover) between the models. Validating FOREST-SAGE end-time and change maps with MODIS-VCF yielded better RMSE results than GEOMOD (RMSE of 13% tree cover for FOREST-SAGE; 22% tree cover for GEOMOD). However, GEOMOD tree cover maps yielded better Kappa than FOREST-SAGE (0.60 for GEOMOD; 0.01 for FOREST-SAGE). Results suggest that FOREST-SAGE is more applicable in the Philippines for provincial extent studies that aim to quantitively track forest cover change, while GEOMOD is more applicable for national extent studies that use categorical data. Results also suggest that input parameter settings must be improved to simulate spatial distribution of forest cover. [ABSTRACT FROM AUTHOR]

The systematic decline of land quality due to the mismatch between land quality and land use is called land degradation. It is the consequences of different physical factors but accelerated by human activities. The processes and factors of land degradation are different in different morpho-climatic regions of the world. Present study is primarily concerned in identifying the factors and status of land degradation in a tropical plateau region. Tropical plateaus are one of the most water erosion related land degraded areas of world. Chotanagpur plateau in tropical eastern India is one of the vulnerable soil degraded areas of the tropical environment. The Precambrian geological formation, undulating topography, immature soil, increasing aridity sets natural settings for land degradation in tropical plateau areas. However, induced degradation results from inappropriate land use, clearance of forest land and heavy land pressure related anthropogenic factors accelerates the processes of land degradation. Kangsabati River basin of eastern Chotanagpur plateau bears all of the above characteristics has been taken for present study as a degraded tropical plateau region. Water erosion and vegetal degradation are the major factors of land degradation in Kangsabati basin. The physical factors responsible for land degradation in the studied area includes physiographic formations, edaphic maturity, hydrologic characteristics, and vegetation cover dynamics etc. This land degradation processes is accelerated by different anthropogenic factors like, land use land cover dynamics, deforestation, agricultural pressure. Multispectral remote sensing data, digital elevation data, thematic maps, recorded climatological data, secondary data and field observation have been utilised to understand the different factors of land degradation in a typical tropical plateau region. The less developed soil profile over Precambrian geology with undulated landforms causes high soil erosion in upper plateau proper regions of the basin. High agricultural pressure, forest and groundwater decline with associated land use land cover dynamics creates decline of land quality in lower basin regions of tropical plateau. The varying intensities of land degraded areas for the basin has been identified through the multiplication of different physical and anthropogenic factor overlaying rasters in GIS environment. Before multiplying, each of these input factor rasters has assigned with weightage after considerable importance of land degradation. The lower basin area with accelerated human interference is the most vulnerable land degraded area for the Kangsabati River basin. [ABSTRACT FROM AUTHOR]

The understanding of groundwater recharge occurrence in drylands is central to water resources management for various uses. This study uses Remote Sensing and GIS techniques to understand where groundwater recharge occurs, and its implications for water and food security in Notwane River Basin located in the Botswana drylands. WetSpass, a distributed hydrological model was applied to map the potential groundwater recharge zones. Crop yield was predicted using the Commonwealth Science and Industrial Research Organization (CSIRO) precision weighing system. Model inputs were land use, soil texture class, topology, slope, groundwater level and catchment hydro meteorological patterns from 1987 to 2017- all sourced from satellite images. Image based classification was done to map the land cover changes in the catchment using ILWIS 30 software. Model outputs were evapotranspiration, surface runoff and groundwater recharge zone maps. The results of image-based land cover classification showed an increase of Settlements/buildup area (22.35%), grassland (5.24%) and a decline in forest cover (3.64%), agricultural land (22.23%) and bareland (3.16%). The results indicate that high recharge zones are associated with low surface runoff in rural, forested areas with sandy soils and the opposite is true for urban, buildup with clay soils. CSIRO predicts yield estimation of up to 2.037 × 103 tonnes of drought resistant maize or sorghum annually using 1100 × 106 L of the available 517.32–434.32 mm/year and 532.64–426.50 mm/year potential surface runoff and groundwater recharge, respectively. Runoff and potential recharge in Notwane sub-catchment suggest an existence of water resources worthy to be explored for food security in water scarce drylands. • Data availability is proven key for sound hydrological modelling in WetSpass model. • Model performance is highly sensitive to quality of land use land cover maps and precipitation data. • Recharge zone mapping are subjective to runoff residence time through soil type and topography. • Groundwater recharge declines with increased urbanisation. [ABSTRACT FROM AUTHOR]

• Land cover dynamics in dry tropical environments are often overlooked. • Classification accuracy of 79–86% was attained using Landsat data. • Primary forest declined, while secondary forest increased. • Deforestation has continued to increase with low rates of recovery. • Forest connectivity declined by 22% between 1972 and 2016. Land cover dynamics in the tropical dry environments of sub-Saharan Africa are not well understood compared to humid environments, especially on a national scale. Previous studies describing land cover in the dry tropics are spatially or temporally constrained. This study presents the first long-term (1972–2016) nationwide land cover dynamics and forest connectivity analyses for Zambia. We employed 300 Landsat images and an object-based image analysis (OBIA) approach with the Random Forests (RF) classifier to map nine land covers at six time steps (1972, 1984, 1990, 2000, 2008 and 2016). Post-classification change detection was used to understand the dynamics, while landscape metrics were derived to assess the forest structural connectivity. Overall accuracies ranging from 79 to 86% were achieved. In 1972, 48% of Zambia was covered by primary forest and 16% was covered by secondary forest. By 2016, 62.74% of Zambia had undergone changes, with primary forest decreasing by 32% and secondary forest increasing by 23%. Our results showed that forests have been recovering by 0.03 to 1.3% yr−1 (53, 000–242, 000 ha yr-1); however, these rates are markedly lower than deforestation rates (- 0.54 to - 3.05% yr-1: 83, 000–453, 000 ha yr-1). Annual rates of change varied by land cover, with irrigated crops having the largest increase (+ 3.19 yr-1) and primary forest having the greatest decrease (-2.48% yr-1). Forest connectivity declined by 22%, with primary forest having the greatest decline, while the connectivity for secondary and plantation forest increased. We showed here that land cover in Zambia is highly dynamic with high rates of change, low forest recovery and decline in forest connectivity. These findings will aid in land use planning, reporting for the forthcoming 2020 Global Forest Resources Assessment, and carbon accounting, especially under the reduction in carbon emissions from deforestation and degradation programme (REDD+). [ABSTRACT FROM AUTHOR]

The current study describes the land use and land cover dynamics in Eastern Arunachal Pradesh from 1985 to 2005 using remote sensing and Geographical Information System (GIS). Landsat-MSS, IRS-LISS-I and LISS-III data for the period 1985, 1995 and 2005 were used to prepare the land use/land cover (LULC) map at 1:250K for different periods. Post-classification change detection technique for quantifying the changes for twelve major land use and land cover types was analyzed. The study signifies that the region experiences expansion in crop land and built-up area and decline in forest area. Crop land and built-up area has increased by 665.41 km2 and 16.72 km2, respectively, from 1985 to 2005. On the other hand, forest area has declined by 699.37 km2 during the period. The study showed that topography and increasing population play an important role in shaping the LULC pattern. The study further revealed the importance of satellite remote sensing and GIS as an effective approach for analyzing the direction, rate and spatial pattern of land use dynamics. It is believed that this type of study will help to contribute towards sustainable land-use planning and management in this part of the North East India in the near future. [ABSTRACT FROM AUTHOR]

This study presents an integrated model based on cellular automata for assessing and simulating land use/cover changes and their impact on the environment. Satellite images from Landsat TM and ETM + sensors from the time period of 1985 to 2014 were applied. Seven static and five dynamic variables were applied. These included elevation, slope, aspect, soil salinity, soil texture, distance from rivers, and roads, and distance from the five classes of land use. The model was validated by a fuzzy reciprocal similarity method. The results showed that this model is suitable for simulating changes in periods of less than 15 years and patches with areas greater than 25 hectares. The model was run for 15 years, beginning with the year 2014. The results for the study area predict that settlement areas will expand; agricultural land, rangeland and barren areas will decline; and forests will remain unchanged until 2029. [ABSTRACT FROM AUTHOR]

• Trailing-edge forests in the western US are vulnerable to climate impacts. • Annual maps of land cover revealed minor declines in total forest cover since 1985. • Pine-oak cover increased since 2000, but other conifer-dominated forests decreased. • Wildfire and drought were major drivers of forest change. Climate change is altering the distribution of woody plants by influencing demographic processes and modifying disturbance regimes. Trailing-edge forests may be particularly vulnerable to these effects because they exist at warm, dry margins of tree distributions. To better understand recent climate-driven changes in trailing-edge forests, we used Landsat time series and 1558 field reference plots to develop annual land cover maps from 1985 to 2020 in two large, biodiverse landscapes in central Arizona, USA. We then combined annual land cover maps with tree ring records and spatial data describing interannual climate, terrain, bark beetle (Curculionidae: Scolytinae) activity, wildfire, and harvest to quantify drivers of forest change. Throughout the two landscapes, forest extent declined by 0.3 % and 0.8 % from 1985 to 2020. However, considerable variation occurred within the study period, with abrupt (ca. 1–2 years) declines in forest extent followed by gradual (ca. 10 years) recovery on each landscape. Pinyon-juniper (Pinus edulis, Pinus monophylla , and/or Juniperus spp.) cover increased from 1985 to ca. 2000 but declined after 2000, a period of extreme drought and regional tree die-off. In contrast, pine-oak (Pinus ponderosa and Quercus spp.) cover increased from 2000 to 2020, primarily due to declines in ponderosa pine and mixed conifer cover over the same period. Wildfire was a key driver of transitions from forest to non-forest cover in our study area, with the occurrence of multiple compounded drought years playing an important role in unburned areas. By driving transitions to alternative forest types or non-forest cover, disturbance and drought will increasingly shape forest dynamics and ecosystem transformations throughout the southwestern US. [ABSTRACT FROM AUTHOR]

China's forests were severely degraded by human activities during the latter half of the 20th century. Therefore, China enacted ambitious programs of natural forest protection and afforestation to protect and expand forests. Yet it is unclear how the programs, especially the designation of forest reserves, have affected forest cover and fragmentation. We evaluated the effectiveness of China's national forest reserves designated since 1990 in conserving forests, by analyzing four forest metrics (i.e., percentage forest cover, mean forest patch size, mean forest patch radius of gyration, and forest patch cohesion index) derived from a newly produced 30 m annual China land cover dataset from 1990 to 2019. We found that overall forest cover increased and fragmentation decreased from baseline years, when reserves were designated, to 2019 in both reserves and their surrounding areas, and only the increase in forest cover relative to baseline was significantly greater in reserves than in surrounding areas. The designation time of reserves under national protection had no considerable effect on changes in the four metrics, but for zonation, the core zone showed a significantly higher increase in forest patch cohesion index relative to baseline than the buffer and transition zones. Nevertheless, forest cover declined and fragmentation increased in highly forested reserves, suggesting destructive human activities and ineffective management. Thus, forest protection and regeneration programs were moderately successful. We recommend that there is significant improvement needed to ensure greater protection of existing forests and reduction of threats to promote effective management. • The nature reserve program showed effectiveness in conserving forests in China. • There was better protection and recovery of forest cover than reducing fragmentation. • Destructive human activities may cause forest declines in highly forested reserves. [ABSTRACT FROM AUTHOR]

Abstract: Annual forest cover loss indicator maps for the humid tropics from 2000 to 2005 derived from time-series 500 m data from the MODerate Resolution Imaging Spectroradiometer (MODIS) were compared with annual deforestation data from the PRODES (Amazon Deforestation Monitoring Project) data set produced by the Brazilian National Institute for Space Research (INPE). The annual PRODES data were used to calibrate the MODIS annual change indicator data in estimating forest loss for Brazil. Results indicate that MODIS data may be useful in providing a first estimate of national forest cover change on an annual basis for Brazil. When directly compared with PRODES change at the MODIS grid scale for all years of the analysis, MODIS change indicator maps accounted for 75% of the PRODES change. This ratio was used to scale the MODIS change indicators to the PRODES area estimates. A sliding threshold of percent PRODES forest and 2000 to 2005 deforestation classes per MODIS grid cell was used to match the scaled MODIS to the official PRODES change estimates, and then to differentiate MODIS change within various sub-areas of the PRODES analysis. Results indicate significant change outside of the PRODES-defined intact forest class. Total scaled MODIS change area within the PRODES historical deforestation and forest area of study is 120% of the official PRODES estimate. Results emphasize the importance of synoptic monitoring of all forest change dynamics, including the cover dynamics of intact humid forest, regrowth, plantations, and cerrado tree cover assemblages. Results also indicate that operational MODIS-only forest cover loss algorithms may be useful in providing near-real time areal estimates of annual change within the Amazon Basin. [Copyright &y& Elsevier]

Hanoi City has been greatly reshaped owing to its "Master Plan by 2030 and a vision to 2050 by Decision 1259/QD-TTg of Vietnam" (called Hanoi Master Plan thereafter). This Hanoi Master Plan results in multi-challenges for the Hanoi City in terms of conserving urban greenspace (UGS). This study pursues to (1) investigate the changing environmental spatial patterns of UGS, (2) identity the areas at high risk due to heat stress based on abnormal land surface temperature (LST) distribution and demographic vulnerability, and (3) suggest mitigation strategies to the authorities by using the proposed UGS management platform. Sentinel-2 multispectral instrument (MSI) data was used to examine the evolution of UGS in relation to LST derived from Landsat 8 OLI thermal band that was subsequently utilized to create heat stress risk patterns. The study region is the inner Hanoi City. The UGS was investigated during the timeframe from Oct. 2016 to Oct. 2018. Accuracy assessment was performed by using Google Earth and field survey data. Results showed that UGS in inner Hanoi City is much declined by 1.3% for woodland and by 4.4% for shrub land, while grass-cover is increased by 2.4% in recent 2 years. Overall accuracies are of 96% and 88% with Kappa coefficients of 0.92 and 0.78 for land cover classification in 2018 and 2016, respectively. Urban heat stress index patterns showed a higher risk in the central inner-city areas of dense residential regions characterized by dense built-up. The identification of environmental heat stress risk patterns provides useful information for calling more attention of urban planners, authorities and health organizations. [Display omitted] • Urban greenspace (UGS) spatial patterns are altered due to the Hanoi Master Plan. • High heat stress areas are identified via land surface temperature (LST) monitoring. • Evolution of UGS in relation to LST was examined by using Sentinel-2 MSI data. • Heat stress index pattern showed higher risks in urban areas with denser residents. [ABSTRACT FROM AUTHOR]

• New energy balance method predicts surface heating following land cover change • This method can simulate temperature change with different environmental conditions • Shrub encroachment and post-drought piñon mortality heat the surface up to 2oC • Shrub encroachment heating is dominated by reduced albedo and canopy conductance • Aerodynamic conductance explains surface temperature increase after piñon mortality The increase in large-scale land cover change (LCC) in recent decades, particularly in response to climate-driven disturbances, has potential to impact local and regional changes in climate due to modification of carbon sources and sinks, albedo, surface roughness and energy fluxes. Using observational data, we predict the impact of two of the most extensive LCCs occurring in the Southwestern US: drought-induced tree mortality and shrub encroachment into grasslands, on surface temperature. We developed a new energy balance method that extracts the biophysical responses to environmental conditions, to predict how structural changes in albedo, surface roughness and canopy conductance following LCC will alter surface temperature. This method allows us not only to explain the observed differences in surface temperature between two non-adjacent study sites with different environmental conditions, but also to separate the contribution of biophysical and non-biophysical properties to surface temperature. Our results suggest that changes in biophysical properties due to shrub encroachment and tree mortality in the Southwestern US (independent of changes in other environmental properties) can potentially lead to an increase in midday surface temperature (11AM to 2PM) of 1 to 2 degrees Celsius, comparable to changes in surface temperature following deforestation. Although the average surface temperature increase in response to both shrub encroachment and tree mortality is similar, the biophysical properties driving the temperature change are different in each scenario. Change in aerodynamic conductance following tree mortality is the largest contributor to heating, while reduced albedo and canopy conductance drive the increase in surface temperature following shrub encroachment. We also show how this increase in daytime surface temperature could be further intensified with future climate, especially with the expected reduction in soil water availability in the Southwest. [ABSTRACT FROM AUTHOR]

• The result of the study indicated that significant LULC changes have happened over the past 46 years. • The study revealed that forest land has declined from 20.9 % in 1973 to 13.7 % in 2019. • The study also revealed the decline of wetlands from 24.0 % in 1973 to 4.8 % in 2019. • LULC dynamics in the study area is driven by a combination of proximate and underlying causes. • The results of the study revealed that there is a significant increase in agricultural land, during the study periods Information on Land Use and Land Cover (LULC) changes and the driving forces behind such modifications underpin a proper understanding of the dynamics of LULC changes. This study aimed to analyse the dynamics of LULC change trends and its driving factors in Jimma Geneti District (JGD) for the year 1973–2019. Five satellite images downloaded from USGS were used to analyze and assess the geospatial and temporal changes in LULC. In addition, in-depth household interviews, key informant interview, focus group discussions (FGD) and field observations were used to address the drivers of LULC changes. The result showed a decline in forest land from 8632.5 ha (20.9 %) in 1973–5647.23 ha (13.7 %) in 2019. The study further revealed that the total of forest land cleared between 1973 and 2019 was estimated to be 2985.27 ha (7.22 %). In other words, 34.6 % of the forest cover that existed in 1973 was lost. Similarly, wetlands declined from 9919.5 ha (24.0 %) in 1973–2000.24 ha (4.8 %) in 2019. Similarly, wetlands declined from 9919.5 ha (24.0 %) in 1973–2000.24 ha (4.8 %) in 2019. On the other hand, cultivated land has increased from 18617.0 ha (45.1 %) to 27708.1 ha (67.1 %). Similarly, the increment in settlement areas has elevated from 908.7 ha (2.2 %) to 4436.46 ha (10.7 %) during the same period. Agricultural expansion, cutting trees for various purposes (such as firewood, charcoal and construction material), overgrazing and the expansion of settlements, were identified as the major proximate causes of these changes. Moreover, the major underlying drivers of LULC changes include population growth, changes in policy and institutions, poverty and lack of awareness on the importance of natural resource conservation for sustainable livelihoods. From this study, it can be concluded that JGD has experienced a significant change in LULC over the past 46 years and were affected both positively and negatively. Hence, a wide range of policy packages are required for sustainable land management practices which take in to account synergies and trade-offs between the various land uses in the study area. The national and local governments should enforce sustainable land management approaches through integrating land use planning and management into all development programmes and projects. [ABSTRACT FROM AUTHOR]

• Continent-wide study on effects of agriculture in forest and prairie ecosystems. • Greater biodiversity loss with higher contrast of agricultural and natural land cover. • Functionally redundant species lost first as agriculture expands. • Numerical compensation following species loss in both ecosystems. The impact of agriculture on biodiversity depends on the extent and types of agriculture and the degree to which agricultural land contrasts with the natural ecosystem. Most research on the latter comes from studies on the influence of different agricultural types within a single ecosystem with far less study on how the natural ecosystem context shapes the response of biodiversity to agricultural production. We used citizen science data from agricultural areas in Canada's Eastern Hardwood-Boreal (forest ecosystem, n=108 landscapes) and Prairie Pothole (prairie ecosystem, n=99) regions to examine how ecosystem context shapes the response of avian species diversity, functional diversity and abundance to the amount of arable crop and pastoral agriculture at landscape scales. Avian surveys were conducted along 8km transects of Breeding Bird Survey routes with land cover assembled within a 20km2 landscape around each transect. The amount of agriculture at which species diversity peaked differed between the forest (15%) and prairie (51%) ecosystems, indicating that fewer species tolerated the expansion of agriculture in the former. In both ecosystems, functional diversity initially increased with agriculture and peaked at higher amounts (forest: 42%, prairie: 77%) than species diversity suggesting that functional redundancy was lost first as agriculture increased. Species turnover with increasing agriculture was primarily among functional groups in forest where a shift from a low to a high agriculture landscape led to a decline in the percent of the community represented by Neotropical migrants, insectivores, upper foliage gleaners and bark foragers, and an increase in the percent of the community represented by short-distance migrants, granivores, omnivores and ground gleaners. There were few distinct shifts in the percent of the community represented by different functional groups in the prairie ecosystem. Total abundance was the least sensitive measure examined in both ecosystems and indicated that species losses with agriculture are likely followed by numerical compensation from agriculture tolerant species. Our results highlight the importance of ecosystem context for understanding how biodiversity is affected by agricultural production with declines in diversity occurring at lower agricultural extents in ecosystems with lower similarity between natural and agricultural land covers. These findings allow for more specific conservation recommendations including managing for species intolerant to agriculture in prairie ecosystems and limiting the expansion of high contrast agriculture and the loss of semi-natural habitat, such as hedge rows, in historically forested ecosystems. [ABSTRACT FROM AUTHOR]

Overdependence on and exploitation of forest resources have significantly transformed the natural reserve forest of Sundarban, which shares the largest mangrove territory in the world, into a great degradation status. By observing these, a most pressing concern is how much degradation occurred in the past, and what will be the scenarios in the future if they continue? To confirm the degradation status in the past decades and reveal the future trend, we took Sundarban Reserve Forest (SRF) as an example, and used satellite Earth observation historical Landsat imagery between 1989 and 2019 as existing data and primary data. Moreover, a geographic information system model was considered to estimate land cover (LC) change and spatial health quality of the SRF from 1989 to 2029 based on the large and small tree categories. The maximum likelihood classifier (MLC) technique was employed to classify the historical images with five different LC types, which were further considered for future projection (2029) including trends based on 2019 simulation results from 1989 and 2019 LC maps using the Markov-cellular automata model. The overall accuracy achieved was 82.30%~90.49% with a kappa value of 0.75~0.87. The historical result showed forest degradation in the past (1989–2019) of 4773.02 ha yr−1, considered as great forest degradation (GFD) and showed a declining status when moving with the projection (2019–2029) of 1508.53 ha yr−1 and overall there was a decline of 3956.90 ha yr−1 in the 1989–2029 time period. Moreover, the study also observed that dense forest was gradually degraded (good to bad) but, conversely, light forest was enhanced, which will continue in the future even to 2029 if no effective management is carried out. Therefore, by observing the GFD, through spatial forest health quality and forest degradation mapping and assessment, the study suggests a few policies that require the immediate attention of forest policy-makers to implement them immediately and ensure sustainable development in the SRF. [ABSTRACT FROM AUTHOR]

The Zagros forests in Western Iran are valuable ecosystems that have been seriously damaged by human interference (harvesting the wood and forest sub-products, converting the forests to the agricultural lands, and grazing) and natural events (drought events and fire). In this study, we generated accurate land cover (LC), and tree canopy cover percentage (TCC%) maps for the forests of Shirvan County, a part of Zagros forests in Western Iran using Sentinel-2, Google Earth, and field data for protective management. First, we assessed the accuracy of Google Earth data using 300 random field plots in 10 different land cover types. For land cover mapping, we evaluated the performance of four supervised classification algorithms (minimum distance (MD), Mahalanobis distance (MaD), neural network (NN), and support vector machine (SVM)). The accuracy of the land cover maps was assessed using a set of 150 stratified random plots in Google Earth. We mapped the forest canopy cover by using the normalized difference vegetation index (NDVI) map, and field plots. We calculated the Pearson correlation between the NDVI values and the TCC% (obtained from field plots). The linear regression between the NDVI values and the TCC% was used to obtain the predictive model of TCC% based on the NDVI. The results showed that Google Earth data yielded an overall accuracy of 94.4%. The SVM algorithm had the highest accuracy for the classification of Sentinel-2 data with an overall accuracy of 81.33% and a kappa index of 0.76. The results of the forest canopy cover analysis showed a Pearson correlation coefficient of 0.93 between the NDVI and TCC%, which is highly significant. The results also showed that the linear regression model is a good predictive model for TCC% estimation based on the NDVI (r2 = 0.864). The results can be used as a baseline for decision-makers to monitor land cover change in the region, whether produced by human activities or natural events and to establish measures for protective management of forests. [ABSTRACT FROM AUTHOR]

• Forest will decline more than any other land use/cover category by 2030. • Urban area will increase more than any other land cover category by 2030. • Decreasing streamflow is expected under moderate- and high-emissions warming scenarios. • Precipitation contributes more significantly to change in streamflow under future scenarios. • Streamflow rate of change is an effective indicator of future hydroclimatic relationships. Previous studies have identified the importance of simulating and quantifying the relationship between hydrologic variation and climate change under historical scenarios at regional and continental scales. However, robust demonstration of the potential of combining consistent land use/cover change (LUCC) and climate change to simulate future hydrologic processes is still lacking. Furthermore, investigating the future connections between hydrologic characteristics and climate variables demands exploration of these phenomena at small (basin) scale. To fill this gap, this research simulates land use/cover patterns in 2030 based on the logistic Cellular Automata-Markov model. Then the Soil Water Assessment Tool (SWAT) simulates change in streamflow within the Ashuelot River basin in New England between 2002–2009 and 2032–2039. Projected climate data are obtained from two general circulation models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5. We also quantify relationships between the rates of change (RC) of streamflow, precipitation and potential evapotranspiration (PET) among 29 subbasins at a monthly scale between the two time periods under different climate scenarios by implementing a panel data approach. Results show greatest changes in forestland (−21.07 km2) and intensive urban land (+5.4 km2) by 2030. Comparisons between the two periods show a negative overall trend in runoff under RCPs 4.5 and 8.5 for both selected GCMs. Panel data analysis indicates that precipitation may contribute more to the RC of streamflow when change in streamflow is significantly influenced by both PET and precipitation over the study period. Therefore, this study provides an important insight into quantifying and comparing the relationship of basin-scale change between streamflow and future climate. [ABSTRACT FROM AUTHOR]

Land cover changes, especially excessive economic forest plantations, have significantly threatened the ecological security of West Dongting Lake wetland in China. This work aimed to investigate the spatiotemporal dynamics of forests in the West Dongting Lake region from 2000 to 2018 using a reconstructed monthly Landsat NDVI time series. The multi-type forest changes, including conversion from forest to another land cover category, conversion from another land cover category to forest, and conversion from forest to forest (such as flooding and replantation post-deforestation), and land cover categories before and after change were effectively detected by integrating Breaks For Additive Seasonal and Trend (BFAST) and random forest algorithms with the monthly NDVI time series, with an overall accuracy of 87.8%. On the basis of focusing on all the forest regions extracted through creating a forest mask for each image in time series and merging these to produce an 'anytime' forest mask, the spatiotemporal dynamics of forest were analyzed on the basis of the acquired information of multi-type forest changes and classification. The forests are principally distributed in the core zone of West Donting Lake surrounding the water body and the southwestern mountains. The forest changes in the core zone and low elevation region are prevalent and frequent. The variation of forest areas in West Dongting Lake experienced three steps: rapid expansion of forest plantation from 2000 to 2005, relatively steady from 2006 to 2011, and continuous decline since 2011, mainly caused by anthropogenic factors, such as government policies and economic profits. This study demonstrated the applicability of the integrated BFAST method to detect multi-type forest changes by using dense Landsat time series in the subtropical wetland ecosystem with low data availability. [ABSTRACT FROM AUTHOR]