Search Results (8)

Coastal ecosystems, particularly mangroves, are essential for ecological stability and human livelihoods, yet they face significant degradation from natural and anthropogenic pressures. This study focuses on the Chaungkaphee Protected Public Forest (PPF) in the Tanintharyi region of Myanmar, which hosts diverse mangrove species critical for carbon storage. Between 2010 and 2020, mangrove forest cover in Myanmar decreased from 540,000 ha to 431,228 ha, resulting in a loss of 108,772 ha. This decline is primarily attributed to illegal logging and agricultural expansion. Our research aims to assess the structural characteristics, biomass, and carbon storage potential of mangrove ecosystems within the Chaungkaphee PPF. Field data collected in early 2024 applied non-destructive sampling methods to gather information on tree structure, species composition, and soil carbon stocks. We identified six dominant mangrove species, with Rhizophora apiculata Blume showing the highest biomass and carbon storage potential. The total biomass was measured at 493.91 Mg ha⁻¹, yielding a carbon stock of 218.76 Mg C ha⁻¹. Soil carbon assessments revealed an average organic carbon stock of 921.09 Mg C ha⁻¹, underscoring the vital role of soil in carbon sequestration. Our findings highlight the significant contribution of mangrove ecosystems to climate change mitigation, emphasizing the urgent need for effective conservation strategies and community involvement in restoration efforts. This study enhances the understanding of mangrove resilience and sustainability, advocating for the protection of these crucial ecosystems amidst ongoing environmental challenges. By recognizing the ecological functions and services provided by mangroves, we can better address the threats they face and promote their restoration for future generations. Full article

Armed conflict and geopolitics are a driving force of Land Use and Land Cover Change (LULCC), but with considerable variation in deforestation trends between broader and finer scales of analysis. Remotely-sensed annual deforestation rates from 1989 to 2018 are presented at the national and (sub-) regional scales for Kachin State in the north of Myanmar and in Kayin State and Tanintharyi Region in the southeast. We pair our multiscaled remote sensing analysis with our multisited political ecology approach where we conducted field-based interviews in study sites between 2018 and 2020. Our integrated analysis identified three common periods of deforestation spikes at the national and state/region level, but with some notable disparities between regions as well as across and within townships and village tracts. We found the rate and geography of deforestation were most influenced by the territorial jurisdictions of armed authorities, national political economic reforms and timber regulations, and proximity to national borders and their respective geopolitical relations. The absence or presence of ceasefires in the north and southeast did not solely explain deforestation patterns. Rather than consider ceasefire or war as a singular explanatory variable effecting forest cover change, we demonstrate the need to analyze armed conflict as a dynamic multisited and diffuse phenomenon, which is simultaneously integrated into broader political economy and geopolitical forces. Full article

Extensive land use changes in forest frontier landscapes are leading to trade-offs in the supply of ecosystem services (ES) with, in many cases, as yet unknown effects on human well-being. In the Tanintharyi Region of Myanmar, a forest frontier landscape facing oil palm and rubber expansion, little is known about local perspectives on ES and the direct impact of trade-offs from land use change. This study assessed the trade-offs experienced with respect to 10 locally important ES from land user perspectives using social valuation techniques. The results show that while intact forests provide the most highly valued ES bundle, the conversion to rubber plantations entails fewer negative trade-offs than that to oil palm. Rubber plantations offer income, fuelwood, a good microclimate, and even new cultural identities. By contrast, oil palm concessions have caused environmental pollution, and, most decisively, have restricted local people’s access to the respective lands. The ES water flow regulation is seen as the most critical if more forest is converted; other ES, such as non-timber forest products, can be more easily substituted. We conclude that, from local perspectives, the impact of ES trade-offs highly depends on access to land and opportunities to adapt to change. Full article

Regime shifts—rapid long-term transitions between stable states—are well documented in ecology but remain controversial and understudied in land use and land cover change (LUCC). In particular, uncertainty surrounds the prevalence and causes of regime shifts at the landscape level. We studied LUCC dynamics in the Tanintharyi Region (Myanmar), which contains one of the last remaining significant contiguous forest areas in Southeast Asia but was heavily deforested between 1992–2015. By combining remote sensing methods and a literature review of historical processes leading to LUCC, we identified a regime shift from a forest-oriented state to an agricultural-oriented state between 1997–2004. The regime shift was triggered by a confluence of complex political and economic conditions within Myanmar, notably the ceasefires between various ethnic groups and the military government, coupled with its enhanced business relations with Thailand and China. Government policies and foreign direct investment enabling the establishment of large-scale agro-industrial concessions reinforced the new agriculture-oriented regime and prevented reversion to the original forest-dominated regime. Our approach of integrating complementary analytical frameworks to identify and understand land-cover regime shifts can help policymakers to preempt future regime shifts in Tanintharyi, and can be applied to the study of land change in other regions. Full article

Myanmar has experienced profound transformations of land use and land governance, often at the expense of smallholders. Empirical evidence on the agency of actors included and excluded in land use decision-making remains scarce. This study analyses who influences land use decision-making, how they do this, and under what circumstances smallholders are included. Comparing three land use trajectories in southern Myanmar, we analysed actors’ agency—conceived as the meanings and means behind (re)actions—in land use decision-making using data from focus groups and interviews. Results showed that uneven distribution of means can lead to unequal decision-making power, enabling actors with more means to exclude those with less means: smallholders. However, this only applies in the case of top-down interventions with mutually exclusive actor interests regarding use of the same land. Where interests are compatible or a mediator supports smallholders in negotiations, actors are likely to develop a collaboration despite unequal means, leading to smallholders’ inclusion in decision-making. Transformation of current land governance towards sustainable development could be promoted by providing mediators to actors with few means, ensuring equal access for all to formal land tenure, engaging with brokers in the land governance network, and improving access to knowledge and financial capital for actors with few means. Full article

Robust quantitative estimates of land use and land cover change are necessary to develop policy solutions and interventions aimed towards sustainable land management. Here, we evaluated the combination of Landsat and L-band Synthetic Aperture Radar (SAR) data to estimate land use/cover change in the dynamic tropical landscape of Tanintharyi, southern Myanmar. We classified Landsat and L-band SAR data, specifically Japan Earth Resources Satellite (JERS-1) and Advanced Land Observing Satellite-2 Phased Array L-band Synthetic Aperture Radar-2 (ALOS-2/PALSAR-2), using Random Forests classifier to map and quantify land use/cover change transitions between 1995 and 2015 in the Tanintharyi Region. We compared the classification accuracies of single versus combined sensor data, and assessed contributions of optical and radar layers to classification accuracy. Combined Landsat and L-band SAR data produced the best overall classification accuracies (92.96% to 93.83%), outperforming individual sensor data (91.20% to 91.93% for Landsat-only; 56.01% to 71.43% for SAR-only). Radar layers, particularly SAR-derived textures, were influential predictors for land cover classification, together with optical layers. Landscape change was extensive (16,490 km²; 39% of total area), as well as total forest conversion into agricultural plantations (3214 km²). Gross forest loss (5133 km²) in 1995 was largely from conversion to shrubs/orchards and tree (oil palm, rubber) plantations, and gross gains in oil palm (5471 km²) and rubber (4025 km²) plantations by 2015 were mainly from conversion of shrubs/orchards and forests. Analysis of combined Landsat and L-band SAR data provides an improved understanding of the associated drivers of agricultural plantation expansion and the dynamics of land use/cover change in tropical forest landscapes. Full article

We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar’s Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area) and lowland evergreen forest (21.6%). However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover <80%), 66.0% of mangrove forest and 47.5% of the region’s biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi’s unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning. Full article

Industrial forest plantations are expanding rapidly across Monsoon Asia and monitoring extent is critical for understanding environmental and socioeconomic impacts. In this study, new, multisensor imagery were evaluated and integrated to extract the strengths of each sensor for mapping plantation extent at regional scales. Two distinctly different landscapes with multiple plantation types were chosen to consider scalability and transferability. These were Tanintharyi, Myanmar and West Kalimantan, Indonesia. Landsat-8 Operational Land Imager (OLI), Phased Array L-band Synthetic Aperture Radar-2 (PALSAR-2), and Sentinel-1A images were fused within a Classification and Regression Tree (CART) framework using random forest and high-resolution surveys. Multi-criteria evaluations showed both L-and C-band gamma nought γ° backscatter decibel (dB), Landsat reflectance ρ_λ, and texture indices were useful for distinguishing oil palm and rubber plantations from other land types. The classification approach identified 750,822 ha or 23% of the Taninathryi, Myanmar, and 216,086 ha or 25% of western West Kalimantan as plantation with very high cross validation accuracy. The mapping approach was scalable and transferred well across the different geographies and plantation types. As archives for Sentinel-1, Landsat-8, and PALSAR-2 continue to grow, mapping plantation extent and dynamics at moderate resolution over large regions should be feasible. Full article