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.

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.

Forest Cover Change and Ecosystem Services: A Case Study of Community Forest in Mechinagar and Buddhashanti Landscape (MBL), Nepal.

The community-based forest management program has been successful in the conservation of forest cover in Nepal. We investigated forest cover change for the Mechinagar and Buddhashanti Landscape (MBL) area within the Jhapa district, Nepal, during 1990-2019 using Landsat images and GIS tools and valuated the major ecosystem services (ES) of Kalika Community-managed Forest (KCF) within the MBL landscape using the economic approach-market price method (revealed price). Land cover analysis of the MBL area indicated that over the study period, there were increases in urban/built-up areas, forest, and tea plantations, and declines in cultivated land, shrub, barren land, water body, and grassland areas. In particular, forest cover increased by 8.6% from 41.5 sq.km to 45.1 sq.km, due to the conversion of 3.9 sq.km cultivated land and 2.4 sq.km shrub into forest cover. KCF, the selected case study area for ES valuation, has been successful in providing noticeable economic benefits from provisioning and cultural services. Of the provisioning services, wood and timber make the largest contribution with an average revenue collection of Nepali Rupees (NRs) 3091.4 thousands followed by non-timber forest products (NRs 883.1 thousands) and firewood (NRs 524.3 thousands), respectively, while ecotourism-based income is also important (NRs 458.4 thousands) and is increasing in later years. As monitoring forest cover in a rapidly changing landscape and evaluating the ES of the community-managed forest cover are imperative for sustainable environmental planning and policy formulation, these research outputs are expected to be a significant benchmark for planners, policy makers, and future researchers.

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.

Changes in forest areas and land cover and their causes using intensity analysis: the case of Alabarda forest planning unit.

The examination of land cover change, as the main driving force of global climate change, and the determination of its economic, ecological, and social effects are necessary for making the right decisions in sustainable development, planning, and management. This study, conducted in the local forest areas of Alabarda, located in Tavsanli District (Turkey), examined temporal and spatial changes in land cover using an intensity analysis consisting of three levels: interval, category, and transition. Using the three maps of 1994, 2004, and 2015, we analyzed the land use changes during two time intervals (1993-2004 and 2004-2015) in the area for six categories, including three for forest areas (Productive, Degraded, and Treeless) and three for non-forest areas (Others, e.g., mine sites, roads, wetlands; Settlement; and Cultivated). The interval level results of the analysis showed that the land change rate was more rapid in the 2004-2015 time interval compared to 1993-2004. According to the category level results, in both time intervals, the Productive category was dormant in terms of loss and gain, whereas the Cultivated category was active. The level showing transitions between categories indicated that the Productive category targeted the Treeless and Cultivated losses in the first time interval and targeted the Degraded losses most intensely in the second time interval. The successful forestry activities (afforestation and rehabilitation) carried out by the government as of 2006 and the ongoing migration of the population from the region have had a joint effect on the increase of forest areas and the transformation of Degraded forest areas into Productive ones in the study area.

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.

Below the canopy: global trends in forest vertebrate populations and their drivers.

Global forest assessments use forest area as an indicator of biodiversity status, which may mask below-canopy pressures driving forest biodiversity loss and 'empty forest' syndrome. The status of forest biodiversity is important not only for species conservation but also because species loss can have consequences for forest health and carbon storage. We aimed to develop a global indicator of forest specialist vertebrate populations to improve assessments of forest biodiversity status. Using the Living Planet Index methodology, we developed a weighted composite Forest Specialist Index for the period 1970-2014. We then investigated potential correlates of forest vertebrate population change. We analysed the relationship between the average rate of change of forest vertebrate populations and satellite-derived tree cover trends, as well as other pressures. On average, forest vertebrate populations declined by 53% between 1970 and 2014. We found little evidence of a consistent global effect of tree cover change on forest vertebrate populations, but a significant negative effect of exploitation threat on forest specialists. In conclusion, we found that the forest area is a poor indicator of forest biodiversity status. For forest biodiversity to recover, conservation management needs to be informed by monitoring all threats to vertebrates, including those below the canopy.

Use of long-term data to evaluate loss and endangerment status of Natura 2000 habitats and effects of protected areas.

Habitat loss is a key driver of biodiversity loss. However, hardly any long-term time series analyses of habitat loss are available above the local scale for finer-level habitat categories. We analysed, from a long-term perspective, the habitat specificity of habitat-area loss, the change in trends in habitat loss since 1989 (dissolution of the communist state), and the impact of protected areas on habitat loss in Hungary. We studied 20 seminatural habitat types in 5000 randomly selected localities over 7 periods from 1783 to 2013 based on historical maps, archival and recent aerial photos and satellite imagery, botanical descriptions, and field data. We developed a method for estimating habitat types based on information transfer between historical sources (i.e., information from a source was used to interpret or enrich information from another source). Trends in habitat loss over time were habitat specific. We identified 7 types of habitat loss over time regarding functional form: linear, exponential, linear and exponential, delayed, minimum, maximum, and disappearance. Most habitats had continuous loss from period to period. After 1986 the average annual rates of habitat loss increased, but the trend reversed after 2002. Nature conservation measures significantly affected habitat loss; net loss was halted, albeit only inside protected areas. When calculating the degree of endangerment based on short-term data (52 years), we classified only 1 habitat as critically endangered, but based on long-term data (230 years), this increased to 7 (including habitat that no longer existed). Hungary will probably reach the global Convention on Biological Diversity Target 5 but will probably not achieve the EU Biodiversity Strategy target of halting habitat loss by 2020. Long-term trend data were highly useful when we examined recent habitat-loss data in a wider context. Our method could be applied effectively in other countries to augment shorter-term data sets on trends in habitat area.

Accelerated deforestation in the humid tropics from the 1990s to the 2000s.

Using a consistent, 20 year series of high- (30 m) resolution, satellite-based maps of forest cover, we estimate forest area and its changes from 1990 to 2010 in 34 tropical countries that account for the majority of the global area of humid tropical forests. Our estimates indicate a 62% acceleration in net deforestation in the humid tropics from the 1990s to the 2000s, contradicting a 25% reduction reported by the United Nations Food and Agriculture Organization Forest Resource Assessment. Net loss of forest cover peaked from 2000 to 2005. Gross gains accelerated slowly and uniformly between 1990-2000, 2000-2005, and 2005-2010. However, the gains were overwhelmed by gross losses, which peaked from 2000 to 2005 and decelerated afterward. The acceleration of humid tropical deforestation we report contradicts the assertion that losses decelerated from the 1990s to the 2000s.

Distribution and dynamics of mangrove forests of South Asia.

Mangrove forests in South Asia occur along the tidal sea edge of Bangladesh, India, Pakistan, and Sri Lanka. These forests provide important ecosystem goods and services to the region's dense coastal populations and support important functions of the biosphere. Mangroves are under threat from both natural and anthropogenic stressors; however the current status and dynamics of the region's mangroves are poorly understood. We mapped the current extent of mangrove forests in South Asia and identified mangrove forest cover change (gain and loss) from 2000 to 2012 using Landsat satellite data. We also conducted three case studies in Indus Delta (Pakistan), Goa (India), and Sundarbans (Bangladesh and India) to identify rates, patterns, and causes of change in greater spatial and thematic details compared to regional assessment of mangrove forests. Our findings revealed that the areal extent of mangrove forests in South Asia is approximately 1,187,476 ha representing ∼7% of the global total. Our results showed that from 2000 to 2012, 92,135 ha of mangroves were deforested and 80,461 ha were reforested with a net loss of 11,673 ha. In all three case studies, mangrove areas have remained the same or increased slightly, however, the turnover was greater than the net change. Both, natural and anthropogenic factors are responsible for the change and turnover. The major causes of forest cover change are similar throughout the region; however, specific factors may be dominant in specific areas. Major causes of deforestation in South Asia include (i) conversion to other land use (e.g. conversion to agriculture, shrimp farms, development, and human settlement), (ii) over-harvesting (e.g. grazing, browsing and lopping, and fishing), (iii) pollution, (iv) decline in freshwater availability, (v) floodings, (vi) reduction of silt deposition, (vii) coastal erosion, and (viii) disturbances from tropical cyclones and tsunamis. Our analysis in the region's diverse socio-economic and environmental conditions highlights complex patterns of mangrove distribution and change. Results from this study provide important insight to the conservation and management of the important and threatened South Asian mangrove ecosystem.

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.

Effects of participatory forest management programs on Land use/land cover change and its Determinants in Alle District, southwest Ethiopia.

In order to create sustainable conservation policies for biodiversity, it is imperative that participatory forest management (PFM) be assessed. Forests contribute to the sustainability of the planet by controlling soil erosion in agricultural areas and by moderating the effects of climate change. However, Ethiopia's forest resources have been under intense pressure because of the increased demand for wood products and agricultural conversion. As one of the potential solutions, the PFM programme was implemented in 1990. This study set out to investigate the effects of the PFM programme on land use and land cover (LULC) in the Alle district of southwest Ethiopia, as well as the variables influencing community involvement and the obstacles to PFM implementation and community involvement. Changes in forest cover were detected using Landsat images from 1992, 2012, and 2022 obtained from Thematic Mapper (TM), Enhanced Thematic Mapper (ETM+), and Operational Land Imager (OLI). Images were obtained during the dry season and were cloud-free. A total of 240 respondents were chosen by means of a straightforward random sampling technique, and survey data were collected using questionnaires, interviews, and field observations. Data were analyzed using ArcGIS 10.5, ERDAS Imagine 2015, SPSS version 20, and Excel 2010. The change in forest cover shows an increasing trend from 2012 to 2022. Again, grassland and wetland coverage in this study decreased rapidly. In the years 2012-2022, forest land increased from 462.7ha (74.8 %), to 569.8ha (92.1 %), while, the agricultural land, grassland, and wetland were reduced from 109.5ha (17.7 %) to 37.8ha (6.1 %), 31.9ha (5.2 %) to 0.0ha (0.0 %); 14.1 ha (2.3 %), to 10.8 ha (1.7 %) respectively. There have been beneficial developments in the forests over the last 30 years. The binary logistic regression model disclose that, land ownership had a negative impact on forest management participation, while other factors such as gender, education level, family size, TLU, access to credit, training, and law enforcement had a positive and significant (p < 0.05) effect on PFM practices. LULC change in study area causes rapid wetland ecosystem deterioration, which may result in the extinction of the most significant and ecologically valuable species and a loss of biodiversity in the environment. In this context, developing an integrated participatory approach requires rapid attention, and all farmers and stakeholders must be actively involved in PFM programs.

Effects of Conservation Policies on Forest Cover Change in Giant Panda Habitat Regions, China.

After long periods of deforestation, forest transition has occurred globally, but the causes of forest transition in different countries are highly variable. Conservation policies may play important roles in facilitating forest transition around the world, including China. To restore forests and protect the remaining natural forests, the Chinese government initiated two nationwide conservation policies in the late 1990s -- the Natural Forest Conservation Program (NFCP) and the Grain-To-Green Program (GTGP). While some studies have discussed the environmental and socioeconomic effects of each of these policies independently and others have attributed forest recovery to both policies without rigorous and quantitative analysis, it is necessary to rigorously quantify the outcomes of these two conservation policies simultaneously because the two policies have been implemented at the same time. To fill the knowledge gap, this study quantitatively evaluated the effects of the two conservation policies on forest cover change between 2001 and 2008 in 108 townships located in two important giant panda habitat regions -- the Qinling Mountains region in Shaanxi Province and the Sichuan Giant Panda Sanctuary in Sichuan Province. Forest cover change was evaluated using a land-cover product (MCD12Q1) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). This product proved to be highly accurate in the study region (overall accuracy was ca. 87%, using 425 ground truth points collected in the field), thus suitable for the forest change analysis performed. Results showed that within the timeframe evaluated, most townships in both regions exhibited either increases or no changes in forest cover. After accounting for a variety of socioeconomic and biophysical attributes, an Ordinary Least Square (OLS) regression model suggests that the two policies had statistically significant positive effects on forest cover change after seven years of implementation, while population density, percent agricultural population, road density, and initial forest cover (i.e. in 2001) had significant negative effects. The methods and results from this study will be useful for continuing the implementation of these conservation policies, for the development of future giant panda habitat conservation projects, and for achieving forest sustainability in China and elsewhere.

Recent trends of forest cover change and ecosystem services in eastern upland region of Bangladesh.

Forest cover changes have diverse outcomes for the livelihoods of rural people across the developing world. However, these outcomes are poorly characterized across varying landscapes. This study examined forest cover changes, associated drivers, and impacts on ecosystem services supporting livelihoods in three distinct areas (i.e. remote, intermediate and on-road) in the Chittagong Hill Tracts region of Bangladesh. The three zones had features of decreasing distance to major roads, decreasing levels of forest cover, and increasing levels of agricultural change. Data was collected from satellite images for 1989-2014, structured household interviews, and group discussions using Participatory Rural Appraisal approaches with local communities to integrate and contrast local people's perceptions of forest cover and ecosystem service change with commonly used methods for mapping forest dynamics. Satellite image analysis showed a net gain of forest areas from 1989 to 2003 followed by a net loss from 2003 to 2014. The gain was slightly higher in intermediate (1.68%) and on-road (1.33%) zones than in the remote (0.5%) zone. By contrast, almost 90% of households perceived severe forest loss and 75% of respondents observed concomitant declines in the availability of fuel wood, construction materials, wild foods, and fresh water. People also reported traveling further from the household to harvest forest products. The main drivers of forest loss identified included increased harvesting of timber and fuel wood over time in the intermediate and on-road zones, whereas swidden farming persisted as the major driver of change over time in the remote zone. The contrast between remotely-sensed forest gains and household-perceived forest loss shows community experiences may be a critical addition to satellite imagery analysis by revealing the livelihood outcomes linked to patterns of forest loss and gain. Community experiences may also evoke solutions by characterizing local drivers of forest change. Failing to disaggregate the impacts of forest loss and gains on ecosystems services over time may lead to uninformed management and further negative consequences for human well-being.

Modelling Spatial and Temporal Forest Cover Change Patterns (1973-2020): A Case Study from South Western Ghats (India).

This study used time series remote sensing data from 1973, 1990 and 2004 to assess spatial forest cover change patterns in the Kalakad-Mundanthurai Tiger Reserve (KMTR), South Western Ghats (India). Analysis of forest cover changes and its causes are the most challenging areas of landscape ecology, especially due to the absence of temporal ground data and comparable space platform based data. Comparing remotely sensed data from three different sources with sensors having different spatial and spectral resolution presented a technical challenge. Quantitative change analysis over a long period provided a valuable insight into forest cover dynamics in this area. Time-series maps were combined within a geographical information system (GIS) with biotic and abiotic factors for modelling its future change. The land-cover change has been modelled using GEOMOD and predicted for year 2020 using the current disturbance scenario. Comparison of the forest change maps over the 31-year period shows that evergreen forest being degraded (16%) primarily in the form of selective logging and clear felling to raise plantations of coffee, tea and cardamom. The natural disturbances such as forest fire, wildlife grazing, invasions after clearance and soil erosion induced by anthropogenic pressure over the decades are the reasons of forest cover change in KMTR. The study demonstrates the role of remote sensing and GIS in monitoring of large-coverage of forest area continuously for a given region over time more precisely and in cost-effective manner which will be ideal for conservation planning and prioritization.

Population genetic structure of the endemic rosewoods Dalbergia cochinchinensis and D. oliveri at a regional scale reflects the Indochinese landscape and life-history traits.

Indochina is a biodiversity hot spot and harbors a high number of endemic species, most of which are poorly studied. This study explores the genetic structure and reproductive system of the threatened endemic timber species Dalbergia cochinchinensis and Dalbergia oliveri using microsatellite data from populations across Indochina and relates it to landscape characteristics and life-history traits. We found that the major water bodies in the region, Mekong and Tonle Sap, represented barriers to gene flow and that higher levels of genetic diversity were found in populations in the center of the distribution area, particularly in Cambodia. We suggest that this pattern is ancient, reflecting the demographic history of the species and possible location of refugia during earlier time periods with limited forest cover, which was supported by signs of old genetic bottlenecks. The D. oliveri populations had generally high levels of genetic diversity (mean He = 0.73), but also strong genetic differentiation among populations (global GST = 0.13), while D. cochinchinensis had a moderate level of genetic diversity (mean He = 0.55), and an even stronger level of differentiation (global GST = 0.25). These differences in genetic structure can be accounted for by a higher level of gene flow in D. oliveri due to a higher dispersal capacity, but also by the broader distribution area for D. oliveri, and the pioneer characteristics of D. cochinchinensis. This study represents the first detailed analysis of landscape genetics for tree species in Indochina, and the found patterns might be common for other species with similar ecology.

Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies.

Forest cover changes are of global concern due to their roles in global warming and biodiversity. However, many previous studies have ignored the fact that forest loss and forest gain are different processes that may respond to distinct factors by stressing forest loss more than gain or viewing forest cover change as a whole. It behooves us to carefully examine the patterns and drivers of the change by subdividing it into several categories. Our study includes areas of forest loss (4.8% of the study area), forest gain (1.3% of the study area) and forest loss and gain (2.0% of the study area) from 2000 to 2012 in Fujian Province, China. In the study area, approximately 65% and 90% of these changes occurred within 2000m of the nearest road and under road densities of 0.6km/km(2), respectively. We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression. The results indicated the lack of pronounced differences in the regressions between the two sampling designs, although the sample size had a great impact on the regression outcome. The application of multi-model inference indicated that the low level road density had a negative significant association with forest loss and forest loss and gain, the expressway density had a positive significant impact on forest loss, and the road network was insignificantly related to forest gain. The model including socioeconomic and biophysical variables illuminated potentially different predictors of the different forest change categories. Moreover, the multiple comparisons tested by Fisher's least significant difference (LSD) were a good compensation for the multinomial logistic model to enrich the interpretation of the regression results.