How do socio-economic characteristics of communities influence resource use and forest cover in the Cryptosepalum forest of North-western Zambia.

Forests are important ecosystems offering extensive material and immaterial benefits to people and the environment. If not well monitored and sustainably managed, forest resource use can lead to degradation, which has global environmental and socio-economic implications. There is currently limited information on the factors that lead to forest use in the Cryptosepalum forests of Zambia, and how these factors potentially influence forest integrity. This study aimed at establishing the socio-economic aspects that determine resource utilisation and forest loss in the Cryptosepalum forest of Manyinga and Zambezi Districts of North-western Zambia. Using a semi-structured questionnaire 207 randomly selected households were interviewed in 7 villages surrounding the Cryptosepalum forest (4 in Manyinga and 3 in Zambezi district). Additionally, three focus Group Discussions were conducted to triangulate interview data. Descriptive statistics, Pearson's Chi-square test of independence and binary logistic regression were used to analyse the data. The study established 14 forest products used by local communities in the study sites. Socio-economic factors, namely; gender, level of education, household size, wealth, and residence status significantly influenced use of 9 of the 14 forest products. Further, significant relationships (p < 0.5) were established between: (1) gender and use of construction poles, wood fibre, fruits, and honey production (2) level of education and utilisation of timber, tubers, caterpillars, mushrooms, and thatching grass; (3) household size and use of construction poles, wild vegetables, tubers, caterpillars, fruits and thatching grass; (4) wealth status and use of timber, construction poles, wild vegetables, wood fibre, and fruits; and (5) residence status and use of construction poles, tubers and thatching grass. Timber harvesting, agricultural expansion, and population increase were established as key drivers of forest cover loss in the Cryptosepalum forest. The study recommends that policies and strategies aimed at conserving this forest focus on strict law enforcement (monitoring and control) of timber harvesting activities; and provision of agricultural inputs and/or community sensitisation on conservation agriculture interventions to curb shifting cultivation practices. The study adds to the body of knowledge on the importance of forests to rural livelihoods in Sub-saharan Africa, and the influence of socio-economic factors on forest cover and resource use.

Analysis of forest cover change and its driving factors in Senan district, Amhara Region, Ethiopia.

Forests are pivotal in upholding and stabilizing ecosystem functions and services globally. Assessing changes in forest cover serves as a crucial indicator to comprehend the scope, scale, and dynamics of land use and land cover alterations on regional and global scales. This study evaluates the forest cover changes between 2005 and 2021, pinpointing the key drivers of forest land changes within the Senan district in Ethiopia's Amhara region. The analysis incorporated Landsat satellite images from 2005, 2011, and 2021, supplemented by field surveys using questionnaire data. Results reveal a shift: forest cover declined from 13.6% (2005) to 11.2% (2011) but rose to 15.4% by 2021, averaging a 12.9% annual change. Several crucial factors were identified as contributors to this forest cover change. These include expanding agricultural land, population growth, urbanization, and using wood as a fuel source. Poverty, exacerbated by population growth, climate change impacts, and a scarcity of food resources, directly linked to a shortage of farmlands, emerged as significant drivers of forest cover change. In light of these findings, an in-depth analysis of land use and land cover dynamics should be conducted, particularly at the expense of forest lands. Moreover, implementing sustainable management practices by developing strategies for intensive agriculture and fostering environmentally friendly non-farm income-generating activities is essential. This study provides reference material to policymakers and land-use planners setting sustainable development goals, advocating for balanced economic growth and environmental conservation to foster a harmonious relationship between humans and forests.

From desolation to preservation: Investigating longitudinal trends in forest coverage and implications for future environmental strategies.

Pakistan's forest cover is experiencing significant degradation in the ongoing efforts to combat climate change. The current state of the climate catastrophe is acknowledged. Nevertheless, there is a significant lack of readiness to tackle it effectively, especially regarding safeguarding the welfare of forthcoming generations. Pakistan bears significant relevance for future generations in this global crisis. The primary objective of this study is to examine the environmental difficulties faced by Pakistan and emphasize the critical need to safeguard its natural resources, considering the well-being of present and future generations. By using rigorous correlation and robust least squares regression methods, we investigate the complex interplay of financial aid, environmental legislation, precipitation, population growth, foreign direct investment, and afforestation within the time frame spanning from 1990 to 2022. The findings demonstrate that providing financial aid for afforestation initiatives significantly expands forested areas in Pakistan. Furthermore, the expansion of the population, the implementation of rigorous environmental restrictions, and the yearly amount of precipitation all play a role in the augmentation of forest coverage in Pakistan. Nevertheless, an alarming pattern of diminishing forest coverage over the years presents noteworthy obstacles. The importance of governance in promoting afforestation initiatives and sustainable development is highlighted by the emergence of adequate regulatory quality as a key factor. The average amount of precipitation has a discernible beneficial influence, underscoring the significance of climatic factors. The results above emphasize the need to implement cautious water resource management strategies and regulations responsive to climatic conditions. Based on these observations, the study proposes promoting sustainable agricultural and forest management, adopting a well-balanced strategy towards population expansion, implementing regulatory changes, and prudent use of water resources.

The first generation of a regional-scale 1-m forest canopy cover dataset using machine learning and google earth engine cloud computing platform: A case study of Arkansas, USA.

Forest canopy cover (FCC) is essential in forest assessment and management, affecting ecosystem services such as carbon sequestration, wildlife habitat, and water regulation. Ongoing advancements in techniques for accurately and efficiently mapping and extracting FCC information require a thorough evaluation of their validity and reliability. The primary objectives of this study are to: (1) create a large-scale forest FCC dataset with a 1-meter spatial resolution, (2) assess the regional spatial distribution of FCC at a regional scale, and (3) investigate differences in FCC areas among the Global Forest Change (Hansen et al., 2013) and U.S. Forest Service Tree Canopy Cover products at various spatial scales in Arkansas (i.e., county and city levels). This study utilized high-resolution aerial imagery and a machine learning algorithm processed and analyzed using the Google Earth Engine cloud computing platform to produce the FCC dataset. The accuracy of this dataset was validated using one-third of the reference locations obtained from the Global Forest Change (Hansen et al., 2013) dataset and the National Agriculture Imagery Program (NAIP) aerial imagery with a 0.6-m spatial resolution. The results showed that the dataset successfully identified FCC at a 1-m resolution in the study area, with overall accuracy ranging between 83.31% and 94.35% per county. Spatial comparison results between the produced FCC dataset and the Hansen et al., 2013 and USFS products indicated a strong positive correlation, with R2 values ranging between 0.94 and 0.98 for county and city levels. This dataset provides valuable information for monitoring, forecasting, and managing forest resources in Arkansas and beyond. The methodology followed in this study enhances efficiency, cost-effectiveness, and scalability, as it enables the processing of large-scale datasets with high computational demands in a cloud-based environment. It also demonstrates that machine learning and cloud computing technologies can generate high-resolution forest cover datasets, which might be helpful in other regions of the world.

The habitat quality paradox: loss of riparian forest cover leads to decreased risk of parasitism and improved body condition in an imperiled amphibian.

Amphibian declines are a global phenomenon but responses of populations to specific threats are often context dependent and mediated by individual physiological condition. Habitat degradation due to reduced riparian forest cover and parasitism are two threats facing the hellbender salamander (Cryptobranchus alleganiensis), but their potential to interact in nature remains largely unexplored. We investigated associations between forest cover, parasitic infection and physiology of hellbenders to test the hypotheses that physiological condition responds to infection and/or habitat degradation. We sampled 17 stream reaches in southwest Virginia, USA, on a year-round basis from 2013 to 2016 and recorded 841 captures of 405 unique hellbenders. At each capture we documented prevalence of two blood-associated parasites (a leech and trypanosome) and quantified up to three physiological condition indices (body condition, hematocrit, white blood cell [WBC] differentials). We used generalized linear mixed models to describe spatiotemporal variation in parasitic infection and each condition index. In general, living in the most heavily forested stream reaches, where hellbender density was highest, was associated with the greatest risk of parasitism, elevated neutrophil-to-lymphocyte (N:L) ratios and eosinophils, slightly lower hematocrit and lower mean body condition in hellbenders. All condition indices fluctuated temporally in a manner consistent with seasonal variation in hellbender metabolic demands and breeding phenology and were associated with land use during at least part of the year. Paradoxically, relatively low levels of forest cover appeared to confer a potential advantage to individuals in the form of release from parasites and improved body condition. Despite improved body condition, individuals from less forested areas failed to exhibit fluctuating body condition in response to spawning, which was typical in hellbenders from more forested habitats. We postulate this lack of fluctuation could be due to reduced conspecific competition or reproductive investment and/or high rates of filial cannibalism in response to declining forest cover.

Spatio-temporal distribution and contributing factors of tegumentary and visceral leishmaniasis: A comparative study in Bahia, Brazil.

Tegumentary (TL) and visceral (VL) leishmaniasis are neglected zoonotic diseases in Brazil, caused by different parasites and transmitted by various vector species. This study investigated and compared spatio-temporal patterns of TL and VL from 2007 to 2020 in the state of Bahia, Brazil, and their correlations with extrinsic factors. The results showed that the total number of cases of both TL and VL were decreasing. The number of municipalities with reported cases reduced for TL over time but remained almost unchanged for VL. There were few municipalities with reported both diseases. Statistical analysis showed that local TL incidence was associated positively with natural forest. Local VL incidence was associated positively with Cerrado (Brazilian savannah) vegetation. This study identified different patterns of occurrence of VL and TL and the risk areas that could be prioritized for epidemiological surveillance.

A cloud-integrated GIS for forest cover loss and land use change monitoring using statistical methods and geospatial technology over northern Algeria.

Over the last two decades, forest cover has experienced significant impacts from fires and deforestation worldwide due to direct human activities and climate change. This paper assesses trends in forest cover loss and land use and land cover changes in northern Algeria between 2000 and 2020 using datasets extracted from Google Earth Engine (GEE), such as the Hanssen Global Forest Change and MODIS Land Cover Type products (MCD12Q1). Classification was performed using the pixel-based supervised machine-learning algorithm called Random Forest (RF). Trends were analyzed using methods such as Mann-Kendall and Sen. The study area comprises 17 basins with high rainfall variability. The results indicated that the forest area decreased by 64.96%, from 3718 to 1266 km2, during the 2000-2020 period, while the barren area increased by 40%, from 134,777 to 188,748 km2. The findings revealed that the Constantinois-Seybousse-Mellegue hydrographic basin was the most affected by deforestation and cover loss, exceeding 50% (with an area of 1018 km2), while the Seybouse River basin experienced the highest percentage of cover loss at 40%. Nonparametric tests showed that seven river basins (41%) had significantly increasing trends of forest cover loss. According to the obtained results, the forest loss situation in Algeria, especially in the northeastern part, is very alarming and requires an exceptional and urgent plan to protect forests and the ecological system against wildfires and climate change. The study provides a diagnosis that should encourage better protection and management of forest cover in Algeria.

Modeling landslide activity and sediment connectivity after eruptions: Insights from the Blanco River (Chile).

Volcanic eruptions can disrupt entire river basins by affecting the hydro-geomorphic characteristics of channel networks and hillslopes. Reports suggest a pulsed and delayed increase in landslide activity following the eruptions, which, depending on the degree of linkage between hillslopes and channels, i.e. sediment connectivity, can represent a massive source of sediment input for the fluvial system. Therefore, predicting landslide occurrence and sediment connectivity is fundamental for management risk strategies, especially in such dynamic and complex environments. The aim of this work is to develop and offer a more reliable approach to map the areas susceptible to landslides and connected to the active channel in a catchment impacted by volcanic eruption. The analyses were carried out in the Blanco River catchment in southern Chile, affected by the Chaitén eruption (2008-09). A combined approach is presented, based on landslide susceptibility models, carried out multi-temporally (from 2010 to 2019), and a threshold-based sediment connectivity map. The results showed that the highest landslide occurrence was reported 4 years after the eruption, whereas the faster increase in the overall area affected was observed only after 7 years. Landslide susceptibility models showed high accuracy when applied in the same year, but were less accurate in predicting future occurrences. This result is ascribed to the dynamic conditions of the vegetation, regenerating quickly after the mass movements. Nevertheless, considering the potential sources of error, the combined landslide susceptibility-connectivity map for the year 2019 well-identified relevant areas for catchment management. The largest part of the catchment was found non-susceptible and disconnected, while areas classified as susceptible and connected represent only 3.1 %. The application of this novel approach allowed to unravel the geomorphic trajectory of the study area and, more importantly, can represent a benchmark for future applications in other catchments affected by large disturbances.

Anthropogenic activities dominated tropical forest carbon balance in two contrary ways over the Greater Mekong Subregion in the 21st century.

The tropical forest carbon (C) balance threatened by extensive socio-economic development in the Greater Mekong Subregion (GMS) in Asia is a notable data gap and remains contentious. Here we generated a long-term spatially quantified assessment of changes in forests and C stocks from 1999 to 2019 at a spatial resolution of 30 m, based on multiple streams of state-of-the-art high-resolution satellite imagery and in situ observations. Our results show that (i) about 0.54 million square kilometers (21.0% of the region) experienced forest cover transitions with a net increase in forest cover by 4.3% (0.11 million square kilometers, equivalent to 0.31 petagram of C [Pg C] stocks); (ii) forest losses mainly in Cambodia, Thailand, and in the south of Vietnam, were also counteracted by forest gains in China due mainly to afforestation; and (iii) at the national level during the study period an increase in both C stocks and C sequestration (net C gain of 0.087 Pg C) in China from new plantation, offset anthropogenetic emissions (net C loss of 0.074 Pg C) mainly in Cambodia and Thailand from deforestation. Political, social, and economic factors significantly influenced forest cover change and C sequestration in the GMS, positively in China while negatively in other countries, especially in Cambodia and Thailand. These findings have implications on national strategies for climate change mitigation and adaptation in other hotspots of tropical forests.

Protection from overheating of simulated Sceloporus horridus lizards in a biosphere reserve of seasonally dry tropical forest in central Mexico.

In seasonally dry ecosystems, loss of vegetation cover leads to warmer microclimates that can increase lizards' body temperatures to the point of threatening their performance. Preserving vegetation by establishing protected areas may mitigate these effects. We used remote sensing to test these ideas in the Sierra de Huautla Biosphere Reserve (REBIOSH) and surrounding areas. First, we determined whether vegetation cover was higher in the REBIOSH compared to adjacent unprotected areas to the north (NAA) and south (SAA). Then, we used a mechanistic niche model to test whether simulated Sceloporus horridus lizards in the REBIOSH experienced a cooler microclimate, higher thermal safety margin, longer foraging duration, and lower basal metabolic rate compared to adjacent unprotected areas. We compared these variables between 1999, when the reserve was declared, and 2020. We found that vegetation cover increased from 1999 to 2020 in all three areas; it was higher in the REBIOSH than in the more anthropized NAA, and was intermediate in the less anthropized SAA in both years. The microclimate temperature decreased from 1999 to 2020 and was lower in the REBIOSH and SAA than in the NAA. Thermal safety margin increased from 1999 to 2020; it was higher in the REBIOSH than in the NAA and intermediate in the SAA. Foraging duration increased from 1999 to 2020 and was similar among the three polygons. Basal metabolic rate decreased from 1999 to 2020 and was higher in the NAA than in the REBIOSH and SAA. Our results suggest that the REBIOSH provides cooler microclimates that increase the thermal safety margin and lower the metabolic rate of this generalist lizard compared to the NAA, and that the REBIOSH could contribute to increased vegetation cover in its surroundings. Besides, protecting original vegetation cover is an important part of climate change mitigation strategies more generally.

Modelling, mapping and monitoring of forest cover changes, using support vector machine, kernel logistic regression and naive bayes tree models with optical remote sensing data.

The present study is designed to monitor the spatio-temporal changes in forest cover using Remote Sensing (RS) and Geographic Information system (GIS) techniques from 1990 to 2017. Landsat data from 1990 (Thematic mapper [TM]), 2000 and 2010 (Enhanced Thematic Mapper [ETM+]), and 2013 to 2017 (Operational Land Imager/Thermal Infrared Sensor [OLI/TIRS]) were classified into the classes termed snow, water, barren land, built-up area, forest, and vegetation. The method was built using multitemporal Landsat images and the machine learning techniques Support Vector Machine (SVM), Naive Bayes Tree (NBT) and Kernel Logistic Regression (KLR). According to the results, forest area was decreased from 19,360 km2 (26.0%) to 18,784 km2 (25.2%) from 1990 to 2010, while forest area was increased from 18,640 km2 (25.0%) to 26,765 km2 (35.9%) area from 2013 to 2017 due to "One billion tree Project". According to our findings, SVM performed better than KLR and NBT on all three accuracy metrics (recall, precision, and accuracy) and the F1 score was >0.89. The study demonstrated that concurrent reforestation in barren land areas improved methods of sustaining the forest and RS and GIS into everyday forestry organization practices in Khyber Pakhtun Khwa (KPK), Pakistan. The study results were beneficial, especially at the decision-making level for the local or provincial government of KPK and for understanding the global scenario for regional planning.

Land-use change and forest cover depletion in Bhawal National Park, Gazipur, Bangladesh from 2005 to 2020.

Despite being a historically significant and biologically diverse protected area in Bangladesh, Bhawal National Park (BNP) has been the victim of anthropogenic activities that have challenged its sustainability. This study aims to determine the extent of landscape change and forest area depletion within BNP territory from 2005 to 2020, as land use change is the most visible indicator of human footprint liable to biodiversity loss and land degradation. Landsat satellite images from four sensors are used in this research (MSS, TM, OLI, and TIRS). The complex spatial composition of Bhawal National Park was characterized using a supervised classification technique using ArcMap version 10.8. The findings show a steady decline in the dense and degraded forest classifications, but an increase in the other classed classes. Waterbody, settlement, and chala/baid are found to increase by approximately 105, 369, and 650% respectively from 2005 till 2020, while, the area of dense and degraded forest decreased by about 47 and 51%. Within 16 years, nearly 1000 ha of dense forest cover has been depleted. Comparing the latest classified image of BNP with the relevant map, Bhabanipur, B.K. Bari, and Boupara beat are identified to be the most degraded areas. The conclusion can be drawn from this study that owing to most suppressing factors, namely settlement and chala/baid, a forest cover of nearly 2284 ha has been depleted from this national park which is almost 49% of the total possessed forest cover in 2005.

The effect of financial crises on deforestation: a global and regional panel data analysis.

Managing our transition to sustainability requires a solid understanding of how conditions of financial crisis affect our natural environment. Yet, there has been little focus on the nature of the relationship between financial crises and environmental sustainability, especially in relation to forests and deforestation. This study addressed this gap by providing novel evidence on the impact of financial crises on deforestation. A panel data approach is used looking at Global Forest Watch deforestation data from > 150 countries in > 100 crises in the twenty-first century. This includes an analysis of crises effects on principle drivers of deforestation; timber and agricultural commodities-palm oil, soybean, coffee, cattle, and cocoa. At a global level, financial crises are associated with a reduction in deforestation rates (- 36 p.p) and deforestation drivers; roundwood (- 6.7 p.p.), cattle (- 2.3 p.p.) and cocoa production (- 8.3 p.p.). Regionally, deforestation rates in Asia, Africa, and Europe decreased by - 83, - 43, and 22 p.p, respectively. Drivers behind these effects may be different, from palm oil (- 1.3 p.p.) and cocoa (- 10.5 p.p.) reductions in Africa, to a combination of timber (- 9.5 p.p) and palm oil in Asia. Moreover, financial crises have a larger effect on deforestation in low-income, than upper middle- and high-income countries (- 51 vs - 39 and - 18 p.p. respectively). Using another main dataset on yearly forest cover-the ESA-Climate Change Initiative-a picture arises showing financial crises leading to small global decreases in forest cover (- 0.1 p.p.) with a small agricultural cover increase (0.1 p.p). Our findings point to financial crises as important moments for global deforestation dynamics. Yet, to consolidate benefits on decreasing deforestation, governments need to enhance their sustainable forest management during crisis periods rather than let it slip down national agendas. Finally, to achieve the SDGs related to forests, better global forest cover datasets are needed, with better forest loss/gain data, disturbance history, and understanding of mosaicked landscape dynamics within a satellite pixel.

The drivers of avian-haemosporidian prevalence in tropical lowland forests of New Guinea in three dimensions.

Haemosporidians are among the most common parasites of birds and often negatively impact host fitness. A multitude of biotic and abiotic factors influence these associations, but the magnitude of these factors can differ by spatial scales (i.e., local, regional and global). Consequently, to better understand global and regional drivers of avian-haemosporidian associations, it is key to investigate these associations at smaller (local) spatial scales. Thus, here, we explore the effect of abiotic variables (e.g., temperature, forest structure, and anthropogenic disturbances) on haemosporidian prevalence and host-parasite networks on a horizontal spatial scale, comparing four fragmented forests and five localities within a continuous forest in Papua New Guinea. Additionally, we investigate if prevalence and host-parasite networks differ between the canopy and the understory (vertical stratification) in one forest patch. We found that the majority of Haemosporidian infections were caused by the genus Haemoproteus and that avian-haemosporidian networks were more specialized in continuous forests. At the community level, only forest greenness was negatively associated with Haemoproteus infections, while the effects of abiotic variables on parasite prevalence differed between bird species. Haemoproteus prevalence levels were significantly higher in the canopy, and an opposite trend was observed for Plasmodium. This implies that birds experience distinct parasite pressures depending on the stratum they inhabit, likely driven by vector community differences. These three-dimensional spatial analyses of avian-haemosporidians at horizontal and vertical scales suggest that the effect of abiotic variables on haemosporidian infections are species specific, so that factors influencing community-level infections are primarily driven by host community composition.

Have China's national forest reserves designated since 1990 conserved forests effectively?

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.

Ephemeral forest regeneration limits carbon sequestration potential in the Brazilian Atlantic Forest.

Although deforestation remains widespread in the tropics, many places are now experiencing significant forest recovery (i.e., forest transition), offering an optimistic outlook for natural ecosystem recovery and carbon sequestration. Naturally regenerated forests, however, may not persist, so a more nuanced understanding of the drivers of forest change in the tropics is critical to ensure the success of reforestation efforts and carbon sequestration targets. Here we use 35 years of detailed land cover data to investigate forest trajectories in 3014 municipalities in the Brazilian Atlantic Forest (AF), a biodiversity and conservation hotspot. Although deforestation was evident in some regions, deforestation reversals, the typical forest transition trajectory, were the prevalent trend in the AF, accounting for 38% of municipalities. However, simultaneous reforestation reversals in the region (13% of municipalities) suggest that these short-term increases in native forest cover do not necessarily translate into persistent trends. In the absence of reversals in reforestation, forests in the region could have sequestered 1.75 Pg C, over three times the actual estimated carbon sequestration (0.52 Pg C). We also showed that failure to distinguish native and planted forests would have masked native forest cover loss in the region and overestimated reforestation by 3.2 Mha and carbon sequestration from natural forest regeneration by 0.37 Pg C. Deforestation reversals were prevalent in urbanized municipalities with limited forest cover and high agricultural productivity, highlighting the importance of favorable socioeconomic conditions in promoting reforestation. Successful forest restoration efforts will require development and enforcement of environmental policies that promote forest regeneration and ensure the permanence of regrowing forests. This is crucial not only for the fate and conservation of the AF, but also for other tropical nations to achieve their restoration and carbon sequestration commitments.

Using interview surveys and multispecies occupancy models to inform vertebrate conservation.

Species distribution data are an essential biodiversity variable requiring robust monitoring to inform wildlife conservation. Yet, such data remain inherently sparse because of the logistical challenges of monitoring biodiversity across broad geographic extents. Surveys of people knowledgeable about the occurrence of wildlife provide an opportunity to evaluate species distributions and the ecology of wildlife communities across large spatial scales. We analyzed detection histories of 30 vertebrate species across the Western Ghats biodiversity hotspot in India, obtained from a large-scale interview survey of 2318 people who live and work in the forests of this region. We developed a multispecies occupancy model that simultaneously corrected for false-negative (non-detection) and false-positive (misidentification) errors that interview surveys can be prone to. Using this model, we integrated data across species in composite analyses of the responses of functional species groups (based on disturbance tolerance, diet, and body mass traits) to spatial variation in environmental variables, protection, and anthropogenic pressures. We observed a positive association between forest cover and the occurrence of species with low tolerance of human disturbance. Protected areas were associated with higher occurrence for species across different functional groups compared with unprotected lands. We also observed the occurrence of species with low disturbance tolerance, herbivores, and large-bodied species was negatively associated with developmental pressures, such as human settlements, energy production and mining, and demographic pressures, such as biological resource extraction. For the conservation of threatened vertebrates, our work underscores the importance of maintaining forest cover and reducing deforestation within and outside protected areas, respectively. In addition, mitigating a suite of pervasive human pressures is also crucial for wildlife conservation in one of the world's most densely populated biodiversity hotspots.

Uso de Encuestas y Modelos de Ocupación Multiespecies para Orientar la Conservación de Vertebrados Resumen Los datos de distribución de especies son una variable esencial de la biodiversidad que requieren de un monitoreo sólido para orientar la conservación de la fauna. Aun así, dichos datos permanecen inherentemente escasos debido a los obstáculos logísticos del monitoreo de la biodiversidad a lo largo de extensiones geográficas generalizadas. Las encuestas realizadas a personas conocedoras de la incidencia de fauna proporcionan una oportunidad para evaluar la distribución de las especies y la ecología de las comunidades de fauna en escalas espaciales grandes. Analizamos las historias de detección de 30 especies de vertebrados en los Ghats Occidentales de la India obtenidos a partir de una encuesta a gran escala realizada por entrevistas a 2318 personas que viven y trabajan en los bosques de esta región. Desarrollamos un modelo de ocupación multiespecies que corrigió simultáneamente los errores falsos negativos (no detección) y los falsos positivos (identificación correcta) a los que están propensos las encuestas por entrevista. Con este modelo, integramos los datos de todas las especies a un análisis compuesto de las respuestas de los grupos funcionales de especies (con base en la tolerancia a la perturbación, dieta y características de masa corporal) para la variación espacial en las variables ambientales, protección y presiones antropogénicas. Observamos una asociación positiva entre la incidencia de especies con la baja tolerancia a la perturbación humana y a la cobertura forestal. Las áreas protegidas estuvieron asociadas con una incidencia mayor para las especies ubicadas en diferentes grupos funcionales comparadas con las áreas desprotegidas. También observamos que la incidencia de especies con una tolerancia baja a las perturbaciones, herbívoros y especies de mayor tamaño estaba asociada negativamente con las presiones de desarrollo, como los asentamientos humanos, la producción de energías y minería, y las presiones demográficas, como la extracción de recursos biológicos. Para la conservación de vertebrados amenazados, nuestro trabajo hace hincapié en la importancia de mantener la cobertura forestal y reducir la deforestación dentro y fuera de las áreas protegidas, respectivamente. Además, la mitigación de un conjunto de presiones humanas dominantes también es crucial para la conservación de la naturaleza en uno de los puntos calientes de biodiversidad con una de las mayores densidades poblacionales del mundo.

Freeze tolerance influenced forest cover and hydrology during the Pennsylvanian.

The distribution of forest cover alters Earth surface mass and energy exchange and is controlled by physiology, which determines plant environmental limits. Ancient plant physiology, therefore, likely affected vegetation-climate feedbacks. We combine climate modeling and ecosystem-process modeling to simulate arboreal vegetation in the late Paleozoic ice age. Using GENESIS V3 global climate model simulations, varying pCO2, pO2, and ice extent for the Pennsylvanian, and fossil-derived leaf C:N, maximum stomatal conductance, and specific conductivity for several major Carboniferous plant groups, we simulated global ecosystem processes at a 2° resolution with Paleo-BGC. Based on leaf water constraints, Pangaea could have supported widespread arboreal plant growth and forest cover. However, these models do not account for the impacts of freezing on plants. According to our interpretation, freezing would have affected plants in 59% of unglaciated land during peak glacial periods and 73% during interglacials, when more high-latitude land was unglaciated. Comparing forest cover, minimum temperatures, and paleo-locations of Pennsylvanian-aged plant fossils from the Paleobiology Database supports restriction of forest extent due to freezing. Many genera were limited to unglaciated land where temperatures remained above -4 °C. Freeze-intolerance of Pennsylvanian arboreal vegetation had the potential to alter surface runoff, silicate weathering, CO2 levels, and climate forcing. As a bounding case, we assume total plant mortality at -4 °C and estimate that contracting forest cover increased net global surface runoff by up to 6.1%. Repeated freezing likely influenced freeze- and drought-tolerance evolution in lineages like the coniferophytes, which became increasingly dominant in the Permian and early Mesozoic.

Forest restoration and support for sustainable ecosystems in the Gandaki Basin, Nepal.

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.

Monitoring of land use/land cover changes using GIS and CA-Markov modeling techniques: a study in Northern Turkey.

The purpose of this study, covering the northern Ulus district of Turkey, was to analyze the forest and land use/land cover (LULC) changes in the past period from 2000 to 2020, and to predict the possible changes in 2030 and 2040, using remote sensing (RS) and geographic information systems (GIS) together with the CA-Markov model. The maximum likelihood classified (MLC) technique was used to produce LULC maps, using 2000 and 2010 Landsat (ETM +) and 2020 Landsat (OLI) images based on existing stand-type maps as reference. Using the historical data from the generated LULC maps, the LULC changes for 2030-2040 were predicted via the CA-Markov hybrid model. The reliability of the model was verified by overlapping the 2020 LULC map with the 2020 LULC model (predicted) map. The overall accuracy was found to be 80.90%, with a Kappa coefficient of 0.74. The total forest area (coniferous + broad-leaved + mixed forest) grew by 10,656.4 ha (15.4%) in the 2000-2020 period. Examination of the types within the Forest Class revealed that the coniferous forest area had grown by 5.9% in the period 2000-2010, whereas it had decreased by 4.7% in the period 2010-2020. The broad-leaved forest area had grown by 1.2% and 3.1%, respectively, between 2000 and 2010 and 2010 and 2020. The mixed forest area had been reduced by 7.1% in the period 2000-2010 but had grown by 1.7% in the 2010-2020 period. In the Non-Forest Class, although the water area had increased in the 2000-2020 period, agricultural land and settlement areas had decreased by 11,553.9 ha (32.3%) and 34.6 ha (0.5%), respectively. According to the 2020-2040 LULC simulation results, it was predicted that there would be 3.8% and 26.4% growth in the total forest and water surface areas and 13.9% and 5.3% reduction in the agricultural and settlement areas, respectively. Using the LULC simulation to separate the Forest Class into coniferous, broad-leaved, and mixed forest categories and subsequently examining the individual changes can be of great help to forest planners and managers in decision-making and strategy development.