Valuing the Impact of Forest Disturbances on the Climate Regulation Service of Western U.S. Forests

The protection and expansion of forest carbon sinks are critical to achieving climate-change mitigation targets. Yet, the increasing frequency and severity of forest disturbances challenge the sustainable provision of forest services. We investigated patterns of forest disturbances’ impacts on carbon sinks by combining spatial datasets of forest carbon sequestration from biomass growth and emissions from fire and bark beetle damage in the western United States (U.S.) and valued the social costs of forest carbon losses. We also examined potential future trends of forest carbon sinks under two climate-change projections using a global vegetation model. We found that forest carbon losses from bark-beetle damage were larger than emissions from fires between 2003 and 2012. The cumulative social costs of forest carbon losses ranged from USD 7 billion to USD 72 billion, depending on the severity of global warming and the discount rate. Forest carbon stocks could increase around 5% under Representative Concentration Pathway (RCP) 4.5 or 7% under RCP 8.5 by 2091 relative to 2011 levels, mostly in forests with high net primary productivity. These results indicate that spatially explicit management of forest disturbances may increase forest carbon sinks, thereby improving opportunities to achieve critical climate-change mitigation goals.

Continuous Detection of Forest Loss in Vietnam, Laos, and Cambodia Using Sentinel-1 Data

In this study, we demonstrate the ability of a new operational system to detect forest loss at a large scale accurately and in a timely manner. We produced forest loss maps every week over Vietnam, Cambodia, and Laos (>750,000 km2 in total) using Sentinel-1 data. To do so, we used the forest loss detection method based on shadow detection. The main advantage of this method is the ability to avoid false alarms, which is relevant in Southeast Asia where the areas of forest disturbance may be very small and scattered and detection is used for alert purposes. The estimated user accuracy of the forest loss map was 0.95 for forest disturbances and 0.99 for intact forest, and the estimated producer’s accuracy was 0.90 for forest disturbances and 0.99 for intact forest, with a minimum mapping unit of 0.1 ha. This represents an important step forward compared to the values achieved by previous studies. We also found that approximately half of forest disturbances in Cambodia from 2018 to 2020 occurred in protected areas, which emphasizes the lack of efficiency in the protection and conservation of natural resources in protected areas. On an annual basis, the forest loss areas detected using our method are found to be similar to the estimations from Global Forest Watch. These results highlight the fact that this method provides not only quick alerts but also reliable detections that can be used to calculate weekly, monthly, or annual forest loss statistics at a national scale.

Forest disturbances and the attribution derived from yearly Landsat time series over 1990–2020 in the Hengduan Mountains Region of Southwest China

Background Natural forests in the Hengduan Mountains Region (HDMR) have pivotal ecological functions and provide diverse ecosystem services. Capturing long-term forest disturbance and drivers at a regional scale is crucial for sustainable forest management and biodiversity conservation. Methods We used 30-m resolution Landsat time series images and the LandTrendr algorithm on the Google Earth Engine cloud platform to map forest disturbances at an annual time scale between 1990 and 2020 and attributed causal agents of forest disturbance, including fire, logging, road construction and insects, using disturbance properties and spectral and topographic variables in the random forest model. Results The conventional and area-adjusted overall accuracies (OAs) of the forest disturbance map were 92.3% and 97.70% ± 0.06%, respectively, and the OA of mapping disturbance agents was 85.80%. The estimated disturbed forest area totalled 3313.13 km2 (approximately 2.31% of the total forest area in 1990) from 1990 to 2020, with considerable interannual fluctuations and significant regional differences. The predominant disturbance agent was fire, which comprised approximately 83.33% of the forest area disturbance, followed by logging (12.2%), insects (2.4%) and road construction (2.0%). Massive forest disturbances occurred mainly before 2000, and the post-2000 annual disturbance area significantly dropped by 55% compared with the pre-2000 value. Conclusions This study provided spatially explicit and retrospective information on annual forest disturbance and associated agents in the HDMR. The findings suggest that China’s logging bans in natural forests combined with other forest sustainability programmes have effectively curbed forest disturbances in the HDMR, which has implications for enhancing future forest management and biodiversity conservation.

ASSESSMENT OF FOREST DISTURBANCES AND CARBON STOCK IN PANTABANGAN-CARRANGLAN WATERSHED, PHILIPPINES USING REMOTE SENSING

Forest disturbances contribute to the decrease in carbon sequestration potential and ecosystem services in a watershed. One of the important watersheds that is affected by land use changes and disturbances is the Pantabangan-Carranglan Watershed. The ability of the watershed to provide ecosystem services is affected by the existing land use and land cover (LULC) and its future trends. Therefore, this study aims to assess the changes in the LULC, forest disturbances, and potential carbon stock in the watershed using satellite images. The LULC types and indices used in detecting forest disturbances were classified and generated from the Landsat 8 satellite images covering two different years. The potential carbon storage in the watershed was estimated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Carbon model. The information generated can be used in the conduct of valuation studies and land use planning in the watershed.

An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas

Current satellite remote sensing methods struggle to detect and map forest degradation, a critical issue as it is likely a major and growing source of carbon emissions and biodiveristy loss. TanDEM-X InSAR phase height (hϕ) is a promising variable for measuring forest disturbances, as it is closely related to mean canopy height, and thus should decrease if canopy trees are removed. However, previous research has focused on relatively flat terrain, despite the fact that much of the worlds’ remaining tropical forests are found in hilly areas, and this inevitably introduces artifacts in sideways imaging systems. In this paper, we find a relationship between hϕ and aboveground biomass change in four selectively logged plots in a hilly region of central Gabon. We show that minimising the level of multilooking in the interferometric processing chain strengthens this relationship, and that degradation estimates across steep slopes in the surrounding region are improved by selecting data from the most appropriate pass directions on a pixel-by-pixel basis. This shows that TanDEM-X InSAR can measure the magnitude of degradation, and that topographic effects can be mitigated if data from multiple SAR viewing geometries are available.

Spectroscopic detection of forest diseases: a review (1970–2020)

Sustainable forest management is essential to confront the detrimental impacts of diseases on forest ecosystems. This review highlights the potential of vegetation spectroscopy in improving the feasibility of assessing forest disturbances induced by diseases in a timely and cost-effective manner. The basic concepts of vegetation spectroscopy and its application in phytopathology are first outlined then the literature on the topic is discussed. Using several optical sensors from leaf to landscape-level, a number of forest diseases characterized by variable pathogenic processes have been detected, identified and quantified in many country sites worldwide. Overall, these reviewed studies have pointed out the green and red regions of the visible spectrum, the red-edge and the early near-infrared as the spectral regions most sensitive to the disease development as they are mostly related to chlorophyll changes and symptom development. Late disease conditions particularly affect the shortwave-infrared region, mostly related to water content. This review also highlights some major issues to be addressed such as the need to explore other major forest diseases and geographic areas, to further develop hyperspectral sensors for early detection and discrimination of forest disturbances, to improve devices for remote sensing, to implement long-term monitoring, and to advance algorithms for exploitation of spectral data. Achieving of these goals will enhance the capability of vegetation spectroscopy in early detection of forest stress and in managing forest diseases.