Evaluating the ability of community‐protected forests in Cambodia to prevent deforestation and degradation using temporal remote sensing data

Abstract

Community forests are known to play an important role in preserving forests in Cambodia, a country that has seen rapid deforestation in recent decades. The detailed evaluation of the ability of community‐protected forests to retain forest cover and prevent degradation in Cambodia will help to guide future conservation management. In this study, a combination of remotely sensing data was used to compare the temporal variation in forest structure for six different community forests located in the Phnom Kulen National Park (PKNP) in Cambodia and to assess how these dynamics vary between community‐protected forests and a wider study area. Medium‐resolution Landsat, ALOS PALSAR data, and high‐resolution LiDAR data were used to study the spatial distribution of forest degradation patterns and their impacts on above‐ground biomass (AGB) changes. Analysis of the remotely sensing data acquired at different spatial resolutions revealed that between 2012 and 2015, the community forests had higher forest cover persistence and lower rates of forest cover loss compared to the entire study area. Furthermore, they faced lower encroachment from cashew plantations compared to the wider landscape. Four of the six community forests showed a recovery in canopy gap fractions and subsequently, an increase in the AGB stock. The levels of degradation decreased in forests that had an increase in AGB values. However, all community forests experienced an increase in understory damage as a result of selective tree removal, and the community forests with the sharpest increase in understory damage experienced AGB losses. This is the first time multitemporal high‐resolution LiDAR data have been used to analyze the impact of human‐induced forest degradation on forest structure and AGB. The findings of this work indicate that while community‐protected forests can improve conservation outcomes to some extent, more interventions are needed to curb the illegal selective logging of valuable timber trees.

Studying Land Cover Changes in a Malaria-Endemic Cambodian District: Considerations and Constraints

“…First, selective logging might be one reason for the difficulty to formulate a relevant hypothesis. Forest goers create a situation arduous to measure and to model as selective logging induces very low-level to undetectable deforestation [54], while potentially maintaining high malaria prevalence [66]. This highlights the necessity of high geographical precision, attainable with a very fine scale of analysis.…”

“…Another form of forest exploitation that occurs at a slower pace is "selective logging," where forest goers search for and cut down specific trees without affecting the surrounding trees. This form of deforestation is more difficult to keep track of, particularly by remote sensing [54]. Beneficial effects have been observed from allowing local communities to own and manage nearby forests, compared to large land concessions [55].…”

Evaluating remote sensing datasets and machine learning algorithms for mapping plantations and successional forests in Phnom Kulen National Park of Cambodia

“…At 37,380 hectares, it covers the entire Kulen plateau which is a critical area for biodiversity and a significant component of the regional watershed. It is comprised mostly of regenerating and secondary forests along with severely degraded forests, cassava and cashew plantations, mostly located in the southern part (Singh et al, 2018).…”

“…LiDAR derived data also provides valuable information about the forest vertical structure that are useful in distinguishing different successional stages of regenerating tropical forests (Marselis et al, 2018). LiDAR data have been used with both Landsat and ALOS data to identify varying levels of forest degradation in Laos (Singh et al, 2017a) and for distinguishing between natural forests and cashew plantations in Cambodia (Singh et al, 2018).…”

“…Despite its protected status, PKNP has experienced high deforestation and degradation rates. As with other protected areas in Cambodia, faces significant threats from local resource extraction activities (Singh et al, 2018). This research seeks to: (a) examine the efficacy of different RS data sources: Landsat, ALOS and LiDAR (either alone or in conjunction with each other) to delineate the different land cover types; (b) compare the performance of three commonly used for land cover classifications ML algorithms (SVM, RF and ANN) in delineating and mapping forests that have undergone varying levels of degradation and cashew plantations; and (c) assess the structural and spectral properties of the different land use types in the area.…”