How Can Remote Sensing Help Monitor Tropical Moist Forest Degradation?—A Systematic Review

Forest conservation effectiveness of community forests may decline in the future: Evidence from Cambodia

Community forests (CFs) have been widely established in tropical countries as a tool to achieve forest conservation. Many studies have shown that CFs can contribute to the reduction of deforestation, yet studies that evaluate the contribution of CFs to reducing forest degradation and facilitating forest recovery remain scarce. We investigated the ability of CFs to prevent deforestation and forest degradation and to facilitate forest recovery by using a country-scale longitudinal tree canopy cover and forest cover data set in Cambodia. We found that CFs can prevent both forest degradation and deforestation, but we did not observe a forest recovery effect. We also found that recently established CFs are not effective for forest conservation compared with older CFs. We conclude that, to date, CFs are an effective forest conservation tool; however, this does not necessarily mean that new CFs will be as effective as established ones.

Habitat restoration is the greatest challenge for population recovery of Hainan gibbons (Nomascus hainanus)

Hainan gibbons are among the world's most critically endangered primates, with a remaining population of only 35 individuals distributed across 5 social groups in the Bawangling Branch of the Hainan Tropical Rainforest National Park, China. Habitat conversion and forest fragmentation over the past 40 years have reduced their geographical distribution by 95%. In the absence of a quantitative assessment of the availability of remaining suitable habitat, it is unclear whether this species can survive to the end of this century. We used behavioral observations, ArcGIS, remote sensing, stereo optical imagery, and MaxEnt modeling to identify patterns of Hainan gibbon range use and compare changes in the distribution of suitable forest types and areas of forest fragmentation over the past 20 years (2000-2020). The results indicate that the combined range of the 5 extant Hainan gibbon groups totaled 14.89 km² . The home range of the smallest group (Group E, 3 individuals) was 1.51 km² , which likely represents the minimum home range size for this species. The remaining area of highly suitable and moderately suitable habitat totals 26.9 km² . However, habitat connectivity across the gibbon range is very low (less than 0.5), limiting the ability of Hainan gibbons to move between forest patches. The results of this study indicate that the availability of suitable habitat in Bawangling is insufficient to allow for future Hainan gibbon population growth. Therefore, immediate action must be taken to restore, reforest, and establish ecological corridors to reconnect areas of suitable habitat for these critically endangered gibbons.

Using an unmanned aerial system to analyse environmental impacts of charcoal production on tropical savanna ecosystems in northwestern Kenya

In many regions of Sub-Saharan Africa, charcoal plays an important role as energy source but is widely perceived as a major driver of deforestation and forest degradation. This narrative, however, is mostly based on research within primary production regions. Though space-borne remote sensing applications can be useful in monitoring such large-scale production modes, environmental effects of household-level production are less easy to assess. Therefore, the present study employs an unmanned aerial system (UAS) to assess the impact of small-scale charcoal production on the vegetation density in the immediate vicinity of production sites. The UAS data was complemented by field measurements and very high-resolution WordView-2 satellite imagery. This approach revealed only small differences between charcoal production sites and reference plots which were usually evened out after 20-25-m distance to the plot centre using a concentric ring analysis. Results further show that a distinction between different land-use practices is difficult, even with the high spatial resolution provided by a UAS. Thus, more research and new approaches are needed to evaluate the role of small-scale charcoal production in deforestation and forest degradation processes against the background of other human activities. However, to exploit the full potential of UAS for monitoring environmental effects in charcoal producing areas, official regulations need to be clearer and more reliable.

Mapping the Spatial Distribution of Fern Thickets and Vine-Laden Forests in the Landscape of Bornean Logged-Over Tropical Secondary Rainforests

Forest degradation has been most frequently defined as an anthropogenic reduction in biomass compared with reference biomass in extant forests. However, so-defined “degraded forests” may widely vary in terms of recoverability. A prolonged loss of recoverability, commonly described as a loss of resilience, poses a true threat to global environments. In Bornean logged-over forests, dense thickets of ferns and vines have been observed to cause arrested secondary succession, and their area may indicate the extent of slow biomass recovery. Therefore, we aimed to discriminate the fern thickets and vine-laden forests from those logged-over forests without dense ferns and vines, as well as mapping their distributions, with the aid of Landsat-8 satellite imagery and machine learning modeling. During the process, we tested whether the gray-level co-occurrence matrix (GLCM) textures of Landsat data and Sentinel-1 C-band SAR data were helpful for this classification. Our study sites were Deramakot and Tangkulap Forest Reserves—commercial production forests in Sabah, Malaysian Borneo. First, we flew drones and obtained aerial images that were used as ground truth for the supervised classification. Subsequently, a machine-learning model with a gradient-boosting decision tree was iteratively tested in order to derive the best model for the classification of the vegetation. Finally, the best model was extrapolated to the entire forest reserve and used to map three classes of vegetation (fern thickets, vine-laden forests, and logged-over forests without ferns and vines) and two non-vegetation classes (bare soil and open water). The overall classification accuracy of the best model was 86.6%; however, by combining the fern and vine classes into the same category, the accuracy was improved to 91.5%. The GLCM texture variables were especially effective at separating fern/vine vegetation from the non-degraded forest, but the SAR data showed a limited effect. Our final vegetation map showed that 30.7% of the reserves were occupied by ferns or vines, which may lead to arrested succession. Considering that our study site was once certified as a well-managed forest, the area of degraded forests with a high risk of loss of resilience is expected to be much broader in other Bornean production forests.

Effect of Acacia mangium Canopy on Physicochemical Characteristics and Nutrient Concentrations of the Soil at Ayer Hitam Forest Reserve, Malaysia

The establishment of an Acacia mangium plantation often alters physicochemical characteristics and nutrient concentrations of soils. We aimed to evaluate the invasive potential of A. mangium forest on the soil in Ayer Hitam Forest Reserve, Peninsular, Malaysia. To achieve the mentioned target, four different regions, namely, the open ground region (OG), Acacia mangium region (AM), transition region (TZ), and native forest region (NF), were selected and each of the regions was divided into six plots. Composite samples were randomly taken from subplots at 0–15 cm depth (topsoil) and 15–30 cm depth (subsoil). Some physicochemical properties such as soil moisture and texture, textural classification, bulk density and particle density, pH, electric conductivity (EC), exchangeable bases (EB) (Ca, Mg and K), cation exchange capacity (CEC), organic matter (OM), total nitrogen (TN), and available phosphorous (Av. P) were analyzed. The results of our study showed that the soil of the AM region, which was clay loam, contained clay (51%), silt (32%), and sand (16%). The chemical analysis of topsoil showed significant differences in terms of OM%, exchangeable- Ca, Mg, K (molc kg−1), N (%), gravitational water content (GWC), and Avail. P between all four regions. Additionally, the highest pH and OM of topsoil were seen in the AM region with 4.5% and 4.33%, respectively. In the subsoil, there were significant differences (p ≤ 0.01) in terms of EC (ds/m), OM (%), Exchangeable- Ca, Mg and K (cmolc kg−1), GWC, available phosphorus, and N (%) between all four regions. The highest GWC, N (%), and Ca (cmolc kg−1) were observed in the AM region with 16.00, 0.14%, and 0.64 cmolc kg−1, respectively. These results showed that A. mangium changed some soil characteristics due to its invasion potential. In summary, A. mangium showed high adaptability on degraded forest land and high ability to accumulate the soil physicochemical properties to enhance its growth.

Above-ground carbon stock and REDD+ opportunities of community-managed forests in northern Thailand

This study aimed to investigate the structure of two deciduous forests and assess their above-ground carbon stock in order to promote community forest management (CFM) for REDD+ opportunities in the Ban Mae Chiang Rai Lum Community Forest in northern Thailand. A systematic sampling method was used to establish twenty-five sample plots of 40 m × 40 m (0.16 ha) each that were used to survey the entire 3,925 ha area of the community forest. Cluster analysis identified two different forest types: dry dipterocarp forest and mixed deciduous forest. It was determined that the above-ground carbon stock did not vary significantly between them. An analysis of carbon sequestration in the community forest indicates that carbon stock increased under CFM from 2007 to 2018 by an estimated 28,928 t C and participation in the carbon market would have yielded approximately US $339,730.43 or US $8.66 /ha/year to the community for that 10-year period. Projections for 2028 reflect that carbon stock will experience continual growth which indicates that maintaining CFM can increase carbon sequestration and reduce CO₂ emissions. However, though further growth of carbon stock in the community forest is expected into 2038, that growth would be at a lesser rate than during the preceding decade. This suggests that CFM management should address forest utilization practices with a focus on maintaining long term carbon stock growth. Additional measures to address the impact of drought conditions and to safeguard against forest fires are required to sustain tree species’ growth and expansion in order to increase their carbon accumulation potential. Thailand’s community forest involvement in REDD+ and participation in its international carbon market could create more economic opportunities for local communities.

Recent Advances in Unmanned Aerial Vehicles Forest Remote Sensing—A Systematic Review. Part II: Research Applications

Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community. Due to the progress in platforms and sensors and the opening of the dedicated market, unmanned aerial vehicle–remote sensing (UAV–RS) is improving its key role in the forestry sector as a tool for sustainable management. The use of UAV (Unmanned Aerial Vehicle) in precision forestry has exponentially increased in recent years, as demonstrated by more than 600 references published from 2018 until mid-2020 that were found in the Web of Science database by searching for “UAV” + “forest”. This result is even more surprising when compared with similar research for “UAV” + “agriculture”, from which emerge about 470 references. This shows how UAV–RS research forestry is gaining increasing popularity. In Part II of this review, analyzing the main findings of the reviewed papers (227), numerous strengths emerge concerning research technical issues. UAV–RS is fully applicated for obtaining accurate information from practical parameters (height, diameter at breast height (DBH), and biomass). Research effectiveness and soundness demonstrate that UAV–RS is now ready to be applied in a real management context. Some critical issues and barriers in transferring research products are also evident, namely, (1) hyperspectral sensors are poorly used, and their novel applications should be based on the capability of acquiring tree spectral signature especially for pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible and open-source tools that can foster researcher activities and support technology transfer among all forestry stakeholders, and (3) a clear lack exist in sensors and platforms interoperability for large-scale applications and for enabling data interoperability.