Search Results (13)

Numerical simulations quantify the transient impacts of implementing green infrastructure (GI) grass swales on unconfined aquifer storage and groundwater-surface water interactions around the Red Butte Creek (RBC) of Utah, USA. The Red Butte Creek Watershed (RBCW) transitions from undeveloped mountainous National Forest land to downstream urbanized areas within Salt Lake Valley (SLV). This reconnaissance-level study demonstrates that increasing stormwater infiltration in urbanized areas during the rainy months (April-June) can, until at least the subsequent March, (a) enhance aquifer recharge and support sustainable groundwater yields; and (b) improve surface water availability. Simulations predict hydrologic impacts of aquifer recharge resulting from hypothetical grass-swale implementation within a 704-acre area located around RBC. The employed model, HyperRBC, is an adaptation of a United States Geological Survey (USGS) transient numerical flow, MODFLOW, model implementation for SLV. Adaptations involved (a) uniformly refined horizontal discretization of seven aquifer layers within a sub-area encompassing parts of RBCW and an adjacent watershed; (b) updated input data; and (c) MODFLOW’s Streamflow-Routing (SFR) package to simulate RBC flow and aquifer-stream seepage. Model predictions indicated that by the end of next March: (a) about 3% of the GI-induced recharge would remain within the unconfined aquifer in the HyperRBC area; (b) 66.6% of the recharge would flow northward into the downgradient continuation of the unconfined aquifer; and (c) 30.3% would discharge to nearby stream and river. In summary, predicted hydrologic changes due to the short-term GI-induced recharge highlight increased groundwater availability within and outside the study area for at least the subsequent 12 months, including high-water-demand summer. These findings show the importance of GI in interim environmental management and in enhancing the effective use of water resources. Full article

In the face of intensifying climate disruptions, coastal landscapes like Necoclí in Colombia’s Department of Antioquia are sites of both vulnerability and resilience. This paper examines how thick mapping acts as a methodology for decentralized spatial planning and a practice of revolutionary care by amplifying youth voices and fostering situated climate adaptation. Drawing from a participatory mapping process co-developed with young people, we reflect on how community-based approaches can trigger territorial restructuring from the bottom up. Through storytelling, visual documentation, and collective drawing, the mapping process brought to light lived experiences and local ecological knowledge that are often excluded from technocratic spatial integration strategies. These thick maps function as tools for sub-local territorial agency, allowing youth to reconnect with their landscapes while providing municipal administrations with the granular data needed for equitable spatial development. The paper explores how this form of mapping challenges top-down adaptation narratives and enables more inclusive planning for just futures by centering the territorial dimensions of climate risk. Our findings reveal a profound divergence in territorial perception: while older settlers maintain a narrative of loss tied to a lush, forested past, children’s drawings expose an internalized ecological thinning, characterized by the absence of native flora and the threatening proximity of a rising sea. Ultimately, this study demonstrates how thick mapping contributes to socio-ecological transitioning by bridging the gap between national climate policies and the spatial expression of local needs in frontline communities. Full article

The rapid rise in the use of Liquefied Petroleum Gas (LPG) as an alternative vehicle fuel in Ghana presents both opportunities and risks within the national energy transition agenda. This study investigates LPG safety as well as environmental and regulatory implications using a multi-method quantitative approach that combines structured survey data, exploratory multivariate analysis (MCA), and machine learning classification (Random Forest) to uncover emerging associations and patterns in LPG safety practices. Primary data were obtained from 384 respondents, including vehicle operators, auto-technicians, regulatory officials, and LPG station attendants across five major transport zones: Kejetia, Asafo, Ahodwo, Bantama, and Suame Magazine. The MCA identified four distinct behavioural and safety profiles—At-Risk, Proactive Safety, Compliant and Equipped, and Formal and Reported—reflecting diverse compliance and risk patterns across socio-occupational groups. The Random Forest classifier achieved a predictive accuracy of 96.5% based on cross-validated performance. Sensitivity and specificity values were high, indicating reliable discrimination among incident types. To reduce the risk of overfitting, k-fold cross-validation and monitored error convergence were performed across increasing numbers of trees. While the model shows strong predictive capability, we present these results cautiously and emphasize observed associations and emerging patterns rather than definitive predictive conclusions. The findings reveal that while economic motivations underpin LPG adoption, weak institutional enforcement and widespread informal installations heighten safety vulnerabilities. Comparisons with sub-Saharan and Asian contexts underscore the need for a structured regulatory framework, mandatory certification of installers, and periodic vehicle inspections. The study contributes to the broader discourse on informal energy transitions in developing economies by demonstrating how technical and behavioural determinants interact within weak regulatory systems. Policy recommendations emphasize the integration of data-driven risk assessment tools into regulatory oversight to enhance vehicular LPG safety and sustainability. Full article

The Liaodong oak (Quercus wutaishanica Mayr) is dominant in the composition scheme in Qingyang City, and its growth performance and management practices have long been central concerns of forest management. However, the long cycles and complex dynamics of forest development make accurate prediction difficult, thereby constraining the design of optimal silvicultural strategies. To remedy the slow growth and suboptimal timber quality of Q. wutaishanica plantations—while fostering large-diameter trees, increasing merchantable yield and the output of high-value timber, and enhancing forests’ carbon-sequestration and oxygen-release services—there is an urgent need for a rigorous predictive framework. Using data from the sixth, seventh, and eighth National Forest Resource Inventories, we developed a transition-matrix growth model comprising growth, ingrowth, and mortality sub-models. With this model, we selected representative plots and simulated 25-year trajectories of stand diameter-class structure and growing stock under three climate scenarios (RCP2.6, RCP4.5, RCP8.5). Results indicate divergent trends in growing stock among scenarios; under RCP2.6, stands attain higher growing stock, a more balanced diameter-class distribution, and a markedly larger number of large-diameter trees. Moreover, Q. wutaishanica exhibits relatively stable growth throughout the simulation horizon. Overall, the transition-matrix model effectively captures short-term stand dynamics, fills a regional research gap for Qingyang City, and provides a robust evidence base for subsequent science-based forest management. Full article

Planosols are seasonally waterlogged soils characterized by an abrupt transition from coarse-textured surface horizons to dense, clay-enriched subsoils. Despite the increased agricultural expansion in the Planosol landscapes, these soils have been largely overlooked in Ethiopia. The FAO soil map of Ethiopia (1:200,000 scale) does not recognize the presence of Planosols. In contrast, the more recent digital soil map of Ethiopia, EthoSoilGrids v1.0, at a 250 spatial resolution, was not detailed enough to capture Planosol landscapes, reflecting their historical undersampling in the legacy data. To address this gap, we conducted a thorough mapping and characterization of Planosols in the Omo-Gibe basin, southwestern Ethiopian highlands. Using over 200 auger observations, 74 georeferenced soil profiles, 296 laboratory analyses, and Random Forest modeling, we produced a 30 m-resolution soil-landscape map. Our results show that Planosols cover about 18% of the basin, a substantial extent previously unrecognized in national exploratory maps. Morphologically, these soils exhibit abrupt textural change from the coarse-textured, light grey Ap/Eg horizon (about 30–40 cm thick) to a very clayey, grey–black Bssg/Bt horizon occurring below 40 cm depth. Analytical data on selected parameters show the following pattern: low clay contents (20–29%) and acidic pH (5.2–5.8) with relatively low CEC values (11–26 cmol/kg) in the surface horizons (Ap/Eg), but pronounced clay increase (37–74%), higher bulk density (1.3 g/cm³), higher pH (up to 6.5), and substantially higher CEC (37–47 cmol/kg) in the sub-surface horizons (Bss/Bt). In terms of soil fertility, Planosols are low in SOC, TN, and exchangeable K contents, but micronutrient levels are variable—high in Fe-Mn-Zn and low in B and Cu. The findings confirm the diagnostic features of WRB Planosols and align with regional East African averages, underscoring the reproducibility of our approach. By rectifying long-standing misclassifications and generating fine-scale, field-validated evidence on soil fertility constraints and management options, this study establishes a strong foundation for targeted soil management in Ethiopia. It offers transferable insights for Planosol-dominated agroecosystems across Eastern Africa. Globally, the dataset contributes to enriching the global scientific knowledge and evidence base on Planosols, thereby supporting their improved characterization and management. Full article

Studying spatial distribution patterns and intraspecific and interspecific associations of tree species is crucial for understanding the maintenance of biodiversity and offering insights into community dynamics and stability. The Shennongjia National Park, located in the transition zone between the (sub)tropics and the temperate climate, holds great significance for understanding how species interact with each other and coexist within forest communities. We used data from a fully mapped 25 ha montane deciduous broad-leaved forest dynamic plot at Shennongjia (SNJ) National Park, central China, to conduct a community-level evaluation of spatial distribution patterns and intraspecific and interspecific associations. We analyzed the spatial distribution patterns of 20 dominant species with univariate and bivariate g(r) functions, as well as intraspecific and interspecific associations across different life-history stages. We assessed the relative contributions of underlying processes in community assembly with three models: complete spatial randomness (CSR), heterogeneous Poisson (HP), and antecedent condition (AC). The results showed that all 20 tree species exhibited aggregated distribution patterns within a 100 m scale. After excluding the influence of environmental heterogeneity, the degree of aggregation decreased, and with the increasing spatial scale from 0 to 100 m, the distribution gradually shifted from aggregated to random or uniform appearance. Positive associations were common in different life-history stages. Negative associations were common across different species, while most of the intraspecific and interspecific associations turned out to be irrelevant when environmental heterogeneity was excluded. We concluded that habitat heterogeneity and dispersal limitation may primarily determine the spatial distribution of species in subtropical montane deciduous broad-leaved forests. This indicates that species distribution may align with environmental patterns, and interspecific correlations may exist. However, the exact responses of these species to environmental changes remain uncertain. Upcoming management approaches ought to concentrate on ongoing observation, which is crucial for mitigating how climate change might affect species distribution and community interactions, thus guaranteeing enduring stability and the conservation of biodiversity. Full article

Longleaf pine (Pinus palustris Mill.) is a conifer historically associated with an open forest ecosystem that extended across much of the coastal plain of the Southeastern United States. It now exists mainly in isolated fragments following the conversion of forests and the long-term disruption of the low-intensity fire regime upon which the species depends. Recent decades have seen efforts to restore longleaf pine forests by government and private landowners. This was reflected in analyses of national forest inventory data during two time periods, ca. 2009–2015 and 2016–2021, that showed increases in the estimated number of longleaf pine trees, the area of the longleaf pine forest type, and the number and area of planted longleaf pine, along with growth in mean plot-level longleaf pine carbon and importance value. At the same time, we found a decrease in the overall forest area containing longleaf pine, manifested across a variety of other forest types. These results point to a dynamic through which forests dominated by longleaf pine are becoming more widespread via restoration, while forests in which the species is a less important component are transitioning to other forest types or land uses. We also detected a decrease over time in the estimated number of longleaf seedlings across most states and forest types and a decline in naturally regenerated longleaf pine. To further assess regeneration trends in longleaf pine, we calculated the estimated proportion of small trees (seedlings and saplings) for the entire species and for seed zone sub-populations. We found a species-wide decrease in the proportion of small trees, from 82.1 percent to 75.1 percent. This reduction was most pronounced along the edges of the species distribution and could indicate less sustainable levels of regeneration in some areas. These results underscore the challenges of facilitating natural regeneration in this important species. Full article

Spatio-temporal analysis of transitions in land cover is critical to understanding many ecological challenges, especially in environmentally vulnerable regions. For instance, in Sub-Saharan Africa, large-scale cropland expansion is expected due to the increasing demand for fuel, food, and fibre. Clearing land for cropland expansion is a driving factor in the degradation of natural ecosystems. We present a spatio-temporal analysis of land-cover change in Ghana’s Northern, Upper East, and Upper West provinces using Intensity Analysis on the periods from 1992 to 2003 and 2003 to 2015. The objectives of this study were to determine whether the intensity of land-use and land-cover (LULC) change is consistent between the two periods and to investigate the direction and extent of change for different LULC categories in northern Ghana. The methodology measures land-cover changes at the interval, category, and transition levels. The results suggest that the annual rate of land change was higher between 1992 and 2003 compared to that between 2003 and 2015. Furthermore, the category-level analysis reveals that the gains in the arable land and tree/forest-cover classes during both time intervals were higher than the uniform intensity. The transition-level analysis results indicate that most of the gains in arable land and tree/forest-cover came at the cost of semi-arid shrublands during both periods. There is also evidence of local increases in forest-cover, likely linked to afforestation policies established by the Ghanian government; however, overall, there has been a loss of natural habitat. The study provides data to improve our understanding of the magnitude and direction of land-cover change, essential for the development of policies designed to mitigate the impact of land-cover change on the livelihoods of local people and the environment at the national and sub-national levels. Full article

Vietnam has seemingly been able to shortcut the forest transition (FT) by quickly moving to the reforestation phase. Provincial-level forest cover and socio-economic trends are, however, not necessarily compatible with a standard FT framework. This article compares forest cover change and associated policy reforms in two provinces. Bac Kan is one of the poorest provinces in Vietnam, and has, after years of deforestation and forest degradation, expanded its forest cover during the past two decades. In contrast, Lam Dong province has higher GDP and population density, but has had high deforestation linked to expansion of perennial crops. This is contrary to what could be expected from a conventional FT hypothesis. Land use dynamics in Vietnam is heavily driven by its historical heritage related to the independence from French rule and heavy state-control and collectivization, and its more recent shift to “market-led socialism” (doi moi), involving export promotion, decentralization and land tenure reforms. The Vietnam experience shows that policies can trump the typical FT patterns linked to general development trends and structural changes, and that the typical FT-trajectory is not unavoidable. Yet, these policies have not primarily been guided by forest concerns, but should be viewed as a side effect of the doi moi policies pursuing economic growth and of the devolution of rights and decision-making. Full article

The Colombian Andes foothills have seen an expansion of forest disturbance since the 1950s. While understanding the drivers of disturbance is important for quantifying the implications of land use change on regional biodiversity, methods for attributing disturbance to specific drivers of change at a high temporal and spatial resolution are still lacking in the Andes region, in part due to persistent cloud cover. Using 20 years of Landsat images (1996–2015) covering Picachos National Park in the Colombian Andes, we detected sub-annual forest cover disturbances using the Breaks For Additive Season and Trend (BFAST) Monitor algorithm; characterized different types of disturbance using spectral, spatial, and topographic indicators; and attributed causes of forest disturbance such as conversion to pasture, conversion to agriculture, and non-stand replacing disturbance (i.e., thinning) using a Random Forest (RF) classifier. Conversion to pasture has been the main driver of forest disturbance in Picachos, responsible for 11,395 ± 72 ha (17%) of forest cover loss, followed by non-stand replacing disturbance and conversion to agriculture. Disturbance detection had 96% overall agreement with validation data, although we had a high omission error of 21% primarily associated with forest to agriculture conversion. Other change drivers had a much more reliable attribution with forest to pasture conversion or non-stand-replacing disturbance, showing only 1–5% commission and 2–14% omission errors. Our results provide spatially-explicit information on sub-annual disturbances and associated drivers of change that are necessary for evaluating and improving domestic conservation efforts and establishing systematic ecological observations, which is currently absent from Colombia. While effective at revealing forest change dynamics in a geographically remote and socio-politically complex region like Picachos, our approach is highly automated and it can be easily extended to the rest of Andes-Amazon transition belt where low availability of remote sensing data and high cloud cover impede efforts at consistent monitoring of forest cover change dynamics and drivers. Full article

Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR) remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS) PALSAR Fine Beam Dual Polarization (FBD) mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA), National Land Cover Database (NLCD), Oklahoma Ecological Systems Map (OKESM) and Oklahoma Forest Resource Assessment (OKFRA), the PALSAR/Landsat forest map showed great improvement. The area of the PALSAR/Landsat forest was about 40,149 km² in 2010, which was close to the area from OKFRA (40,468 km²), but much larger than those from JAXA (32,403 km²) and NLCD (37,628 km²). We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km², 6.9% of the total forest area in 2010) and gain (3630 km², 9.0%) in southeast and central Oklahoma, and the total area of forests increased by 684 km² from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be helpful to forest management. Full article

The aim of this paper is to explore possible links between forest cover change and characteristics of social-ecological systems at sub-national scale based mainly on census data. We assessed relationships between population density, poverty, ethnicity, accessibility and forest cover change during the last decade for four regions of Bolivia and the Lao PDR, combining a parcel-based with a cell-based approach. We found that accessibility is a key driver of forest cover change, yet it has the effect of intensifying other economic and policy-related underlying drivers, like colonization policies, cash crop demand, but also policies that lead to forest gain in one case. Poverty does not appear as a driver of deforestation, but the co-occurrence of poverty and forest loss driven by external investments appears critical in terms of social-ecological development. Ethnicity was found to be a moderate explanatory of forest cover change, but appears as a cluster of converging socio-economic characteristics related with settlement history and land resource access. The identification of such clusters can help ordering communities into a typology of social-ecological systems, and discussing their possible outcomes in light of a critical view on forest transition theory, as well as the relevance and predictive power of the variables assessed. Résumé: L’objectif de cet article est d’explorer les liens entre le changement de la couverture forestière et les caractéristiques des systèmes socio-écologiques à l’échelle nationale, principalement à l’aide de données de recensement. Nous avons évalué les relations entre la densité de population, la pauvreté, l’ethnicité, l’accessibilité et le changement de la couverture forestière pendant la dernière décennie pour quatre régions de Bolivie et du Laos, en combinant des approches par parcelles et par cellules. Nous avons constaté que l’accessibilité est un facteur clé du changement de la couverture forestière, tandis qu’elle a pour effet d'intensifier d'autres facteurs économiques et politiques sous-jacents, comme les politiques de colonisation, la demande de cultures de rente, mais aussi, dans un cas, des politiques conduisant à un accroissement de la forêt. La pauvreté n’apparait pas comme un facteur de déforestation, mais la co-occurrence de la pauvreté et de la perte de forêt entrainée par les investissements extérieurs semble critique en termes de développement socio-écologique. L'ethnicité se révèle être modérément explicative du changement de la couverture forestière, mais elle apparait comme un ensemble de caractéristiques socio-économiques convergentes liées à l'histoire de l’implantation humaine et à l'accès aux ressources foncières. L'identification de tels ensembles peut aider à classer les communautés selon une typologie des systèmes socio-écologiques, et à discuter leurs possibles impacts sur la forêt avec un point de vue critique sur la théorie de la transition forestière, ainsi que la pertinence et la puissance prédictive des variables évaluées. Full article

Taking Luangprabang province in Lao Peoples’s Democratic Republic (PDR) as an example, we simulated future forest cover changes under the business-as-usual (BAU), pessimistic and optimistic scenarios based on the Markov-cellular automata (MCA) model. We computed transition probabilities from satellite-derived forest cover maps (1993 and 2000) using the Markov chains, while the “weights of evidence” technique was used to generate transition potential maps. The initial forest cover map (1993), the transition potential maps and the 1993–2000 transition probabilities were used to calibrate the model. Forest cover simulations were then performed from 1993 to 2007 at an annual time-step. The simulated forest cover map for 2007 was compared to the observed (actual) forest cover map for 2007 in order to test the accuracy of the model. Following the successful calibration and validation, future forest cover changes were simulated up to 2014 under different scenarios. The MCA simulations under the BAU and pessimistic scenarios projected that current forest areas would decrease, whereas unstocked forest areas would increase in the future. Conversely, the optimistic scenario projected that current forest areas would increase in the future if strict forestry laws enforcing conservation in protected forest areas are implemented. The three simulation scenarios provide a very good case study for simulating future forest cover changes at the subnational level (Luangprabang province). Thus, the future simulated forest cover changes can possibly be used as a guideline to set reference scenarios as well as undertake REDD/REDD+ preparedness activities within the study area. Full article