Search Results (11)

The fragmented forests of the Kenya highlands, known for their exceptional species richness and endemism, are among the world’s most important biodiversity hotspots. However, detailed studies on the fauna of these ecosystems—especially specialist species that depend on moist forests, which are particularly threatened by habitat fragmentation—are still limited. In this study, we used mitochondrial genes (cytochrome b and the displacement loop) and a nuclear marker (retinol-binding protein 3) to investigate genetic and morphological diversity, phylogenetic associations, historical divergence, population dynamics, and phylogeographic patterns in two rodent species—the soft-furred mouse (Praomys jacksoni) and the African wood mouse (Hylomyscus endorobae)—across Kenya’s forest landscapes. We found a complex genetic structure, with P. jacksoni exhibiting greater genetic diversity than H. endorobae. The Mt. Kenya P. jacksoni populations are significantly genetically different from those in southwestern forests (Mau Forest, Kakamega Forest, and Loita Hills). In contrast, H. endorobae presented no observable biogeographic structuring across its range. The genetic diversity and geographic structuring patterns highlighted selectively strong effects of forest fragmentation and differing species’ ecological and evolutionary responses to these landscape changes. Our findings further underscore the need for expanded sampling across Kenya’s highland forests to better understand species’ changing diversity and distribution patterns in response to the impacts of human-mediated habitat changes. These insights are critical for informing conservation strategies to preserve biodiversity better in this globally important region. Full article

The Maasai Mara and the wider Mau River Basin in East Africa provide fundamental ecosystem services that support people, wildlife, livestock and agriculture. The historical indigenous land use of the Mara and wider Mau basin was wildlife conservation and pastoralism with highland agriculture. However, land policy changes, the rise of community conservancies and the increase in human populations have mediated unprecedented land use shifts over time. We analyze land use and land cover change (LULCC) trends from 1990 to 2040 in the Mara and the wider Mau River Basin landscape. The study examines land use and land cover change trends, establishes factors driving the trends, and assesses the implications of these trends on biodiversity. Multi-temporal satellite images, together with physical and social economic data, were collated to generate future scenarios for transitions for forest, shrubland, grassland, cropland, wetlands and built-up areas between 1990 and 2040. Agricultural expansion is the chief driver of LULCC in the Mara and the wider Mau River Basin, particularly since 2015. There was insignificant change to the forest cover after 2015, which was in part due to government intervention on forest encroachment and boundaries. The anthropogenic choice of tilling the land in the basin caused a decline in grasslands, forests and expanded shrublands, particularly where there was clear tree cutting in the Mau forest. Land use and land cover trends have generated undesirable impacts on ecosystem services that support wildlife conservation. Full article

The coastline of the Ca Mau and Kien Giang provinces in the Vietnamese Mekong Delta has been severely eroded in recent decades. Pile–Rock Breakwaters (PRBWs) are among the most widely adopted structures for controlling shoreline erosion in this region. These structures are effective for wave energy dissipation, stimulating sediment accumulation, and facilitating the restoration of mangrove forests. These breakwaters are generally considered to be the best-engineering practice; however, there is currently insufficient scientific evidence with regard to specific structural design aspects. This can lead to PRBW structures being compromised when deployed in the field. This study used a physical model of a PRBW in a laboratory to investigate several design parameters, including crest width and working states (i.e., submerged, transition, and emerged), and investigated their relationship with the wave transmission coefficient, wave reflection coefficient, and wave energy dissipation. To investigate these relationships further, empirical formulas were derived for PRBWs under different sea states and crest widths to aid the design process. The results showed that the PRBW width had a significant influence on the wave energy coefficients. The findings revealed that the crest width of the breakwater was inversely proportional to the wave transmission coefficient (K_t) under the emerged state. The crest width was also proportional to the wave reduction efficiency and wave energy dissipation in both working states (i.e., the submerged and emerged states). The front wave disturbance coefficient (K_f) was found to be proportional to the wave reflection coefficient, and the wave height in front of the structure was found to increase by up to 1.4 times in the emerged state. The wave reflection coefficient requires special consideration to reduce the toe erosion in the structure. Lastly, empirical equations including linear and non-linear formulas were compared with previous studies for different classes of breakwaters. These empirical equations will be useful for understanding the wave transmission efficiency of PRBWs. The findings of this study provide important guidance for PRBW design in the coastal area of the Mekong Delta. Full article

Ecosystem services offered by mangrove forests are facing severe risks, particularly through land use change driven by human development. Remote sensing has become a primary instrument to monitor the land use dynamics surrounding mangrove ecosystems. Where studies formerly relied on bi-temporal assessments of change, the practical limitations concerning data-availability and processing power are slowly disappearing with the onset of high-performance computing (HPC) and cloud-computing services, such as in the Google Earth Engine (GEE). This paper combines the capabilities of GEE, including its entire Landsat-7 and Landsat-8 archives and state-of-the-art classification approaches, with a post-classification temporal analysis to optimize land use classification results into gap-free and consistent information. The results demonstrate its application and value to uncover the spatio-temporal dynamics of mangrove forests and land use changes in Ngoc Hien District, Ca Mau province, Vietnamese Mekong delta. The combination of repeated GEE classification output and post-classification optimization provides valid spatial classification (94–96% accuracy) and temporal interpolation (87–92% accuracy). The findings reveal that the net change of mangroves forests over the 2001–2019 period equals −0.01% annually. The annual gap-free maps enable spatial identification of hotspots of mangrove forest changes, including deforestation and degradation. Post-classification temporal optimization allows for an exploitation of temporal patterns to synthesize and enhance independent classifications towards more robust gap-free spatial maps that are temporally consistent with logical land use transitions. The study contributes to a growing body of work advocating full exploitation of temporal information in optimizing land cover classification and demonstrates its use for mangrove forest monitoring. Full article

Mangroves are adapted to coastal processes; however, mangrove species showed various responses to estuarian environments, leading to different structural characteristics at accretion and erosion areas. The species composition, structure and regeneration of mangrove forests were investigated to provide insight into mangrove forest development in response to shoreline accretion and erosion processes. The species composition and stand structure of mangrove forests were measured along the distance from the shoreline at accretion and erosion sites in Ca Mau, Vietnam. The hierarchical clustering of grouped stands based on species composition and tree size distribution was conducted. Grouped mangrove stands showed landward changes in species composition and stand structure from the shoreline (p < 0.05), reflecting the timescale of accretion or erosion at both accretion and erosion sites. Stand development patterns differed between accretion and erosion sites, and Avicennia alba and Rhizophora apiculata dominated seaward plots at accretion and erosion sites, respectively. Newer accredited sites were dominated by A. alba. Mangrove stands developed from dense A. alba dominant to R. apiculata dominant stands with increasing tree size at accretion sites. There were more species-colonized sites with a higher erosion rate or that were more recently eroded, implying that timescale of erosion and erosion rate affected species composition and regeneration on erosion sites. Accretion and erosion affected stand development of mangroves differently, implying that conservation and restoration strategies should be applied differently to accretion and erosion sites. Full article

Land cover and population is key in considering sustainable management of the environment. An assessment focusing on the two may aid planning for sustainable management of the ecosystems. This is particularly vital for the water tower ecosystems which are extremely vulnerable. This paper provides a scientific assessment on the extent of land cover change in Mau Water Tower Ecosystem from 1986 to 2015 using satellite images. It analyzes the implications of observed population dynamics and forecasts the extent of land cover change in this resource. The results indicate a sharp increase in the area covered by grassland with a drastic decline in forest cover. Cropland showed marked fluctuations during the entire period. The change in forest cover had a very strong significant negative relationship with the rapid population increase. Forecast on land cover change, based on a “Business as Usual” (BAU) scenario, indicated further decline in forest cover and an increase in the area covered by grassland. The results of the study suggest that land cover change and population growth within the water towers are closely interlinked and cause significant effects on these ecosystems. These findings lay the foundation for a review of conservation and agricultural policies in order to enhance sustainable management of Mau Water Tower. Full article

Deforestation and forest degradation (D&D) in the tropics have continued unabated and are posing serious threats to forests and the livelihoods of those who depend on forests and forest resources. Smallholder farmers are often implicated in scientific literature and policy documents as important agents of D&D. However, there is scanty information on why smallholders exploit forests and what the key drivers are. We employed behavioral sciences approaches that capture contextual factors, attitudinal factors, and routine practices that shape decisions by smallholder farmers. Data was collected using household surveys and focus group discussions in two case study forests—Menagesha Suba Forest in Ethiopia and Maasai Mau Forest in Kenya. Our findings indicate that factors that forced farmers to engage in D&D were largely contextual, i.e., sociodemographic, production factors constraint, as well as policies and governance issues with some influences of routine practices such as wood extraction for fuelwood and construction. Those factors can be broadly aggregated as necessity-driven, market-driven, and governance-driven. In the forests studied, D&D are largely due to necessity needs and governance challenges. Though most factors are intrinsic to smallholders’ context, the extent and impact on D&D were largely aggravated by factors outside the forest landscape. Therefore, policy efforts to reduce D&D should carefully scrutinize the context, the factors, and the associated enablers to reduce forest losses under varying socioeconomic, biophysical, and resource governance conditions. Full article

This paper is a summary of the findings of research work conducted in two case studies in the Rift Valley, Kenya. This study used the Neo-Institutional theory to interrogate how the rules and regulations (institutions involved) of the agrarian reform process in Kenya are constantly changing and helping to shape the livelihoods of social actors around Mau Forest. The first case study—Ndungulu, is a settlement scheme where the Ogiek ethnic community were resettled between 1995 and 1997 after the land clashes of 1992. The second case study is the Kamuyu cooperative farm, a post-colonial settlement scheme owned by a cooperative society that was founded in 1965 by members from the Kikuyu ethnic group. This study employed qualitative data collection methods intermittently between 2012 and 2017 for a total of two years. A total of 60 interviews were conducted for this research. Thirteen (13) of these were key informant interviews with experts on land. The qualitative interviews were complemented by participant observations and nine focus group discussions. The qualitative data from the interviews and focus group discussions were transcribed, coded and analyzed thematically. Observations documented as field notes were also analyzed to complement the study findings. In this paper, the challenges, bargaining position and power play between social actors and government institutions implicated in the agrarian reform process in Kenya has been brought to the forefront. For instance, due to the structural issues that date back to the colonial period, the Ogiek have found innovative ways to maintain their daily existence (e.g., maintaining traditional methods of apiculture in Mau Forest). However, constraints in accessing forest land has resulted in them taking desperate measures, namely; selling off land to the Kalenjin in what is called “distress land sales”. On the contrary, the neighboring Kikuyu have maintained their land ownership status despite recurrent ethnic clashes that have occurred during general election years. Full article

Drought is considered a serious disaster after floods and typhoons and is tending to increase frequency and intensity due to climate change on a global scale. In addition, droughts also cause large and small fires that occur daily around the world, damaging forests and forest ecosystems and having a significant impact on the economy, society, and people. This paper presents the situation of forest fires in U Minh Ha forest of Ca Mau province, which is the southernmost province of Vietnam. The study used satellite imagery processing, which combined spatial analysis to identify areas of fire sensitivity, in the face of drought risk associated with climate change in the dry season in 2016. AHP hierarchy analysis was performed using factors such as surface temperature, leaf moisture, vegetation cover, vegetation density, the distance to water sources, the distance to residential areas, and the distance to fire protection establishments. The results show that the zone with average fire sensitivity accounted for nearly half of the forest area and is distributed in the south and southwest. The high fire sensitivity area is negligible. The study results are useful for planning strategies to protect forest resources against the drought risk caused by climate change, which is becoming increasingly harsh. Full article

The main objective of this study is to assess the spatio-temporal dynamics of land cover/land use changes in the lower Mekong Delta over the last 40 years with the coastal Tran Van Thoi District of Ca Mau Province, Vietnam as a case study. Land cover/land use change dynamics are derived from moderate to high spatial resolution (Landsat and SPOT) satellite imagery in six time intervals ranging from 1973 to 2011. Multi-temporal satellite images were collected, georeferenced, classified using per-pixel method, validated, and compared in post classification for the land use/land cover change detection in decades. Seven major land cover/land use classes were obtained, including cultivated lands, aquaculture ponds, mangrove forest, melaleuca forest, built up areas, bare lands, and natural water bodies. The accuracies of the land cover/land use maps for 1973, 1979, 1989, 1995, 2004, and 2011 were 81%, 82%, 86%, 87%, 89%, and 89%, respectively. The results show that the area of cultivated lands reduced over the period 1973–2011, however, it still represents the dominant land use in the case study. Aquaculture ponds were almost absent in 1973 but greatly increased from 1995 to 2004, to represent 20% of the land surface in 2011. Overall, from 1973 to 2011, bare lands, cultivated lands, mangrove forest, and melaleuca forest decreased by 104 km², 77 km², 61 km², and 5 km², respectively. In contrast, aquaculture lands and built up areas increased by 123 km² and 120 km², respectively. Temporal analysis highlights that these changes took place mostly between 1995 and 2004. This study is a first step to identify the main drivers of land use changes in this delta region, which include economical policies as well as demographic, socio-economic, and environmental changes. Full article

Over the past few decades, clearing for shrimp farming has caused severe losses of mangroves in the Mekong Delta (MD) of Vietnam. Although the increasing importance of shrimp aquaculture in Vietnam has brought significant financial benefits to the local communities, the rapid and largely uncontrolled increase in aquacultural area has contributed to a considerable loss of mangrove forests and to environmental degradation. Although different approaches have been used for mangrove classification, no approach to date has addressed the challenges of the special conditions that can be found in the aquaculture-mangrove system in the Ca Mau province of the MD. This paper presents an object-based classification approach for estimating the percentage of mangroves in mixed mangrove-aquaculture farming systems to assist the government to monitor the extent of the shrimp farming area. The method comprises multi-resolution segmentation and classification of SPOT5 data using a decision tree approach as well as local knowledge from the region of interest. The results show accuracies higher than 75% for certain classes at the object level. Furthermore, we successfully detect areas with mixed aquaculture-mangrove land cover with high accuracies. Based on these results, mangrove development, especially within shrimp farming-mangrove systems, can be monitored. However, the mangrove forest cover fraction per object is affected by image segmentation and thus does not always correspond to the real farm boundaries. It remains a serious challenge, then, to accurately map mangrove forest cover within mixed systems. Full article