SPA-LUCC: Developing land-use/cover scenarios in mountain landscapes

Massive land-use/cover changes (LUCC) have been observed in many regions worldwide over several decades. Modelling frameworks based on spatially explicit land-use/cover maps are particular suitable for analysing the impacts of LUCC on ecosystems and on related functions and services. Spatial allocation procedures have to meet specific characteristics of the study area and mountain regions require particular attention due to their complex topography. The aims of the study were to (1) develop SPatial Allocation procedures of LUCC (SPA-LUCC) adapted to the specific situation of mountain regions — in particular of the Alps, (2) generate land-use/cover scenario maps considering different patterns of socioeconomic development, and (3) evaluate LUCC spatially. Examining historical maps of the Stubai Valley (Austria), we identified biophysical factors as well as socioeconomic drivers. For validation, the 2003 land-use pattern was modelled based on the land-use pattern for 1973, providing an overall accuracy of 73%. Furthermore, we tested SPA-LUCC in other regions of the Alps in France, Germany, Italy and Switzerland successfully (accuracy ranged between 63% and 84%). Hence, SPA-LUCC was proven to be valid for 75% of the Alps. Likely future land-use patterns were modelled for three different socioeconomic scenarios for the Stubai Valley: (a) continuation of previous land-use changes, (b) reduction of use and (c) diversification of use. Results showed that agricultural land in particular is affected by significant changes, whereas the forest belt and near-natural grassland undergo only minor changes. Thus, SPA-LUCC lays the foundation for evaluating future landscape dynamics in the Alps. To provide practitioners with a user-friendly instrument, SPA-LUCC was elaborated as an ArcGIS®-toolbox.     

Modeling the ecological niche of long-term land use changes: The role of biophysical factors

Land use/land cover changes (LULCCs) represent the result of the complex interaction between biophysical factors and human activity, acting over a wide range of temporal and spatial scales. The aim of this work is to quantify the role of biophysical factors in constraining the trajectories of land abandonment and urbanization in the last 50 years. A habitat suitability model borrowed from animal ecology was used to analyze the ecological niche of the following LULCC trajectories occurred in Emilia-Romagna (northern Italy) during 1954–2008: (i) land abandonment (LA) and (ii) urbanization (URB), both from agricultural areas (URB_agr) and from semi-natural areas (URB_for). Results showed that the different LULCC trajectories were driven by different combinations of biophysical factors, such as climate, topography and soil quality. In particular, slope and elevation resulted as the main driving factors for rural processes, while slope and temperatures resulted as the main constraints underlying urban processes. This approach may represent a conceptual and technical step toward the systematic assessment of LULCC processes, thus providing an effective support tool to inform decision makers about land use transformations, their underlying causes, as well as their possible implications.     

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the presatellite era. Here, we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo‐referenced and digitized historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a fivefold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4–1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha^?1 yr^?1. This is at least threefold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8–5.7) Mg C ha^?1, compared to a committed loss of 11.9 (7.2–16.6) Mg C ha^?1 within areas lacking such protection. Furthermore, for nine protected areas where LULCC data are available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long‐term land cover trends in the tropics.     

The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States

Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km² of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700–2005, or 13.4% of carbon losses in non‐PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001–2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large‐scale disturbances that would release large amounts of carbon in PAs.     

A Land System representation for global assessments and land‐use modeling

Current global scale land‐change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land‐use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human‐environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi‐)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land‐use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land‐change models that include the human drivers of land change are best parameterized at sub‐global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.     

The role of natural regeneration to ecosystem services provision and habitat availability: a case study in the Brazilian Atlantic Forest

Natural regeneration provides multiple benefits to nature and human societies, and can play a major role in global and national restoration targets. However, these benefits are context specific and impacted by both biophysical and socioeconomic heterogeneity across landscapes. Here, we investigate the benefits of natural regeneration for climate change mitigation, sediment retention and biodiversity conservation in a spatially explicit way at very high resolution for a region within the global biodiversity hotspot of the Atlantic Forest. We classified current land‐use cover in the region and simulated a natural regeneration scenario in abandoned pasturelands, areas where potential conflicts with agricultural production would be minimized and where some early stage regeneration is already occurring. We then modeled changes in biophysical functions for climate change mitigation and sediment retention, and performed an economic valuation of both ecosystem services. We also modeled how land‐use changes affect habitat availability for species. We found that natural regeneration can provide significant ecological and social benefits. Economic values of climate change mitigation and sediment retention alone could completely compensate for the opportunity costs of agricultural production over 20 yr. Habitat availability is improved for three species with different dispersal abilities, although by different magnitudes. Improving the understanding of how costs and benefits of natural regeneration are distributed can be useful to design incentive structures that bring farmers’ decision making more in line with societal benefits. This alignment is crucial for natural regeneration to fulfill its potential as a large‐scale solution for pressing local and global environmental challenges.     

Factors and Processes Shaping Land Cover and Land Cover Changes Along the Wisconsin River

Land use can exert a powerful influence on ecological systems, yet our understanding of the natural and social factors that influence land use and land-cover change is incomplete. We studied land-cover change in an area of about 8800 km² along the lower part of the Wisconsin River, a landscape largely dominated by agriculture. Our goals were (a) to quantify changes in land cover between 1938 and 1992, (b) to evaluate the influence of abiotic and socioeconomic variables on land cover in 1938 and 1992, and (c) to characterize the major processes of land-cover change between these two points in time. The results showed a general shift from agricultural land to forest. Cropland declined from covering 44% to 32% of the study area, while forests and grassland both increased (from 32% to 38% and from 10% to 14% respectively). Multiple linear regressions using three abiotic and two socioeconomic variables captured 6% to 36% of the variation in land-cover categories in 1938 and 9% to 46% of the variation in 1992. Including socioeconomic variables always increased model performance. Agricultural abandonment and a general decline in farming intensity were the most important processes of land-cover change among the processes considered. Areas characterized by the different processes of land-cover change differed in the abiotic and socioeconomic variables that had explanatory power and can be distinguished spatially. Understanding the dynamics of landscapes dominated by human impacts requires methods to incorporate socioeconomic variables and anthropogenic processes in the analyses. Our method of hypothesizing and testing major anthropogenic processes may be a useful tool for studying the dynamics of cultural landscapes. Received 7 December 2000; accepted 2 October 2001.     

Landscape Dynamics in Northwestern Amazonia: An Assessment of Pastures,Fire and Illicit Crops as Drivers of Tropical Deforestation

Many studies have identified drivers of deforestation throughout the tropics and, in most cases, have recognised differences in the level of threat. However, only a few have also looked at the temporal and spatial dynamics by which those drivers act, which is critical for assessing the conservation of biodiversity as well as for landscape planning. In this study, we analyse land cover change between 2000 and 2009 in north-western Colombian Amazonia to identify the interactions between the use of fire, cultivation of illicit crops and establishment of pastures, and their impacts on the loss of forest in the region. Yearly analyses were undertaken at randomly selected sample areas to quantify the average areas of transition of land cover types under different landscape compositions: forest-dominated mosaics, pasture mosaics, fire mosaics, and illicit crop mosaics. Our results indicate that despite the fact that forest areas were well-preserved, deforestation occurred at a low annual rate (0.06%). Conversion to pasture was the main factor responsible for forest loss (the area of pastures tripled within forest mosaics over 8 years), and this process was independent of the landscape matrix in which the forests were located. In fire mosaics, burning is a common tool for forest clearing and conversion to pasture. Thus, forests in fire mosaics were highly disturbed and frequently transformed from primary to secondary forests. The use of fire for illicit cropping was not detected, partly due to the small size of common illicit crops. Forest regeneration from pastures and secondary vegetation was observed in areas with large amounts of natural forest. Overall, assuming the continuation of the observed pasture conversion trend and the use of forest fire, we suggest that our results should be incorporated into a spatially explicit and integrated decision support tool to target and focus land-planning activities and policies.     

Largely underestimated carbon emission from land use and land cover change in the conterminous United States

Carbon (C) emission and uptake due to land use and land cover change (LULCC) are the most uncertain term in the global carbon budget primarily due to limited LULCC data and inadequate model capability (e.g., underrepresented agricultural managements). We take the commonly used FAOSTAT‐based global Land Use Harmonization data (LUH2) and a new high‐resolution multisource harmonized national LULCC database (YLmap) to drive a land ecosystem model (DLEM) in the conterminous United States. We found that recent cropland abandonment and forest recovery may have been overestimated in the LUH2 data derived from national statistics, causing previously reported C emissions from land use have been underestimated due to the definition of cropland and aggregated LULCC signals at coarse resolution. This overestimation leads to a strong C sink (30.3 ± 2.5 Tg C/year) in model simulations driven by LUH2 in the United States during the 1980–2016 period, while we find a moderate C source (13.6 ± 3.5 Tg C/year) when using YLmap. This divergence implies that previous C budget analyses based on the global LUH2 dataset have underestimated C emission in the United States owing to the delineation of suitable cropland and aggregated land conversion signals at coarse resolution which YLmap overcomes. Thus, to obtain more accurate quantification of LULCC‐induced C emission and better serve global C budget accounting, it is urgently needed to develop fine‐scale country‐specific LULCC data to characterize the details of land conversion.     

Deforestation rates in insular Southeast Asia between 2000 and 2010

Insular Southeast Asia experienced the highest level of deforestation among all humid tropical regions of the world during the 1990s. Owing to the exceptionally high biodiversity in Southeast Asian forest ecosystems and the immense amount of carbon stored in forested peatlands, deforestation in this region has the potential to cause serious global consequences. In this study, we analysed deforestation rates in insular Southeast Asia between 2000 and 2010 utilizing a pair of 250 m spatial resolution land cover maps produced with regional methodology and classification scheme. The results revealed an overall 1.0% yearly decline in forest cover in insular Southeast Asia (including the Indonesian part of New Guinea) with main change trajectories to plantations and secondary vegetation. Throughout the region, peat swamp forests experienced clearly the highest deforestation rates at an average annual rate of 2.2%, while lowland evergreen forests declined by 1.2%/yr. In addition, the analysis showed remarkable spatial variation in deforestation levels within the region and exposed two extreme concentration areas with over 5.0% annual forest loss: the eastern lowlands of Sumatra and the peatlands of Sarawak, Borneo. Both of these areas lost around half of their year 2000 peat swamp forest cover by 2010. As a whole this study has shown that deforestation has continued to take place on high level in insular Southeast Asia since the turn of the millennium. These on‐going changes not only endanger the existence of numerous forest species endemic to this region, but they further increase the elevated carbon emissions from deforested peatlands of insular Southeast Asia thereby directly contributing to the rising carbon dioxide concentration in the atmosphere.     

Keeping management effects separate from environmental effects in terrestrial carbon accounting

This study proposes that carbon fluxes identified as being from land use and land‐cover change (LULCC) include only that component of a flux that can be attributed to LULCC, exclusive of the effects of environmental change (CO₂, climate, N, etc.). This proposal seems too obvious to need saying, but published estimates of the LULCC flux are widely variable for reasons that have more to do with modeling environmental effects than with LULCC.     

Dynamics of past forest cover changes and future scenarios with implications for soil degradation in Misiones rainforest,Argentina

Misiones rainforest is one of the most threatened subtropical forests worldwide. Anthropogenic pressure by agriculture and forestry expansion continues transforming landscapes with negative consequences on ecosystem service provision, such as soil erosion control. Understanding how land use and land cover change (LUCC) management, policies, and social factors influenced in the past, allows decision-makers to anticipate potential effects on future land use and soil loss, contributing to the sustainable planning and management of productive activities. We developed three spatially explicit scenarios for Misiones province by 2030 using the Dinamica EGO modeling platform: 1) Business as Usual (BAU), 2) Low Deforestation (ALTlow), and 3) High Deforestation (ALThigh), based on different international and domestic socioeconomic contexts. We used land cover data from 2002 to 2015 as well as biophysical, social-infrastructure, political-administrative factors, and legal restrictions to estimate changes that may occur by 2030. We analyzed magnitude, intensity, and spatial pattern of future forest cover changes through transition rates and a cellular automata allocation model. Moreover, we used the Universal Soil Loss Equation (USLE) integrated into a Geographic Information System (GIS) to determine soil water erosion and soil loss tolerance in each scenario. Our results revealed that around 19% of the remaining native forest would be transformed into either agriculture or cultivated forest by 2030 for all scenarios. In addition, and contrary to that trend, the ALTlow scenario showed a recovery of 3% of native forest. Regarding soil erosion, our study indicated that the mean annual soil loss by 2030 would range from 12.03 to 19.15 t. ha⁻¹.year⁻¹ for ALTlow and ALThigh scenarios, respectively. Additionally, between 21% and 31% of Misiones province showed soil loss values higher than tolerance. Our work shows that a 10% decrease in the deforestation rate, compared to the current rate, would lead not only to a recovery of native forest cover, but also to a reduction in soil loss of about 4.5 Mt.yr⁻¹ by 2030. This study demonstrates the suitability of the applied model to simulate future LUCC processes and provides inputs for decision-making involving natural resource management and the potential impacts of these decisions on ecosystem services. Finally, our results highlight the need for appropriate policies and regulations, especially, in terms of land use change restrictions in areas of high erosion risk.     

Landscape attributes shape dung beetle diversity at multiple spatial scales in agricultural drylands

Land-use change is one of the main drivers of biodiversity loss worldwide, but its negative effects can vary depending on the spatial scale analyzed. Considering the continuous expansion of agricultural demand for land, it is urgent to identify the drivers that shape biological communities in order to balance agricultural production and biodiversity conservation in human-modified landscapes. We used a patch-landscape design and a multimodel inference approach to assess the effects of landscape composition and configuration at two spatial scales (patch and landscape) on the structure of dung beetle assemblages. We performed our study in the Caatinga, the largest dry forest in South America. We sampled 3,526 dung beetles belonging to 19 species and 11 genera. At patch scale, our findings highlight the positive relationship of forest cover and landscape heterogeneity with dung beetle diversity, which are the major drivers of beetle assemblages. Edge density, in turn, is a major driver at the landscape scale and has a negative effect on beetle diversity. Our results support the hypothesis that landscapes combining natural vegetation remnants and heterogeneous agricultural landscapes are the most effective at conserving the biodiversity of dung beetles in the Caatinga landscapes. Directing efforts to better understand the dynamics of dung beetles in agricultural lands can be helpful for policymakers and scientists to design agri-environment schemes and apply conservation strategies in tropical dry forests.     

Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range‐wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back‐cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long‐term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long‐term demographic decline and range contraction for a species of high‐conservation concern. Range‐wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal‐limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management.     

Changing Landscapes for Forest Commons: Linking Land Tenure with Forest Cover Change Following Mexico’s 1992 Agrarian Counter-Reforms

Mexico’s 1992 agrarian counter-reforms opened up the country’s vast network of common property regimes, known as ejidos, to the possibility of privatization. This study investigates the relationship between dynamic common property regimes and deforestation in the wake of policy reform among eight ejidos in southeastern Mexico. Using institutional analyses, land use/land cover change (LULCC) analyses and a Forest Dependency Index, we examine how land tenure arrangements relate to land use and forest cover change patterns. We demonstrate that informally privatized ejidos had larger individual landholdings, more land in use, and higher rates of deforestation. Commonly-held ejidos exhibited lower deforestation rates and, in some cases, forests provided economic benefits via community forest management. However, forest dependency did not correlate with low deforestation rates, suggesting alternative pathways for conservation.     

Forest Loss in Protected Areas and Intact Forest Landscapes: A Global Analysis

In spite of the high importance of forests, global forest loss has remained alarmingly high during the last decades. Forest loss at a global scale has been unveiled with increasingly finer spatial resolution, but the forest extent and loss in protected areas (PAs) and in large intact forest landscapes (IFLs) have not so far been systematically assessed. Moreover, the impact of protection on preserving the IFLs is not well understood. In this study we conducted a consistent assessment of the global forest loss in PAs and IFLs over the period 2000–2012. We used recently published global remote sensing based spatial forest cover change data, being a uniform and consistent dataset over space and time, together with global datasets on PAs’ and IFLs’ locations. Our analyses revealed that on a global scale 3% of the protected forest, 2.5% of the intact forest, and 1.5% of the protected intact forest were lost during the study period. These forest loss rates are relatively high compared to global total forest loss of 5% for the same time period. The variation in forest losses and in protection effect was large among geographical regions and countries. In some regions the loss in protected forests exceeded 5% (e.g. in Australia and Oceania, and North America) and the relative forest loss was higher inside protected areas than outside those areas (e.g. in Mongolia and parts of Africa, Central Asia, and Europe). At the same time, protection was found to prevent forest loss in several countries (e.g. in South America and Southeast Asia). Globally, high area-weighted forest loss rates of protected and intact forests were associated with high gross domestic product and in the case of protected forests also with high proportions of agricultural land. Our findings reinforce the need for improved understanding of the reasons for the high forest losses in PAs and IFLs and strategies to prevent further losses.     

Unravelling the response of diurnal raptors to land use change in a highly dynamic landscape in northwestern Spain: an approach based on satellite earth observation data

Land use and land cover change (LULCC) is one of the main components of current anthropogenic global change. Unravelling the ecological response of biodiversity to the combined effect of land use change and other stressors is essential for effective conservation. For this purpose, we used co-inertia analysis to combine LULCC analysis of earth observation satellite data-derived maps and raptor data obtained from road censuses conducted in 2001 and 2014 at sampling unit level (10 km² spatial resolution), in northwestern Spain (province of Ourense, c. 7281 km²). In addition, habitat suitability models were also computed using ten widely used single-modelling techniques providing an ensemble of predictions at landscape level (four spatial resolutions: 500-m, 1-km, 2-km and 5-km radius around each sighting) for each year and raptor species to analyse the habitat suitability changes in the whole study area through three niche overlap indices. The models revealed an increase in occurrence and habitat suitability of forest raptor species coupled with a strong decrease in species associated with open habitats, mainly heaths and shrub formations. Open-habitat specialist species were negatively affected by the concomitant effects of intensive forest management and a long-lasting trend of rural abandonment coupled with an unusually high frequency of wildfires. Sustainable forest management and agricultural practices should be encouraged by both public and private sectors, through, e.g. policies related to European funds for rural and regional development (FEDER and FEADER programs) to effectively protect threatened habitats and species, and to comply with current environmental legislation. The combined use of satellite imagery and ground-level biodiversity data proved to be a cost-effective and systematic method for monitoring priority habitats and their species in highly dynamic landscapes.     

Accelerating forest loss in Southeast Asian Massif in the 21st century: A case study in Nan Province,Thailand

Farmers are carving a new agricultural frontier from the forests in the Southeast Asian Massif (SAM) in the 21st century, triggering significant environment degradation at the local scale; however, this frontier has been missed by existing global land use and forest loss analyses. In this paper, we chose Thailand's Nan Province, which is located in the geometric center of SAM, as a case study, and combined high resolution forest cover change product with a fine‐scale land cover map to investigate land use dynamics with respect to topography in this region. Our results show that total forest loss in Nan Province during 2001–2016 was 66,072 ha (9.1% of the forest cover in 2000), and that the majority of this lost forest (92%) had been converted into crop (mainly corn) fields by 2017. Annual forest loss is significantly correlated with global corn price (p < 0.01), re‐confirming agricultural expansion as a key driver of forest loss in Nan Province. Along with the increasing global corn price, forest loss in Nan Province has accelerated at a rate of 2,616 ± 730 ha per decade (p < 0.01). Global corn price peaked in 2012, in which year annual forest loss also reached its peak (7,523 ha); since then, the location of forest loss has moved to steeper land at higher elevations. Spatially, forest loss driven by this smallholder agricultural expansion emerges as many small patches that are not recognizable even at a moderate spatial resolution (e.g. 300 m). It explains how existing global land use/cover change products have missed the widespread and rapid forest loss in SAM. It also highlights the importance of high‐resolution observations to evaluate the environmental impacts of agricultural expansion and forest loss in SAM, including, but not limited to, the impacts on the global carbon cycle, regional hydrology, and local environmental degradation.