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1. Green Vegetation Cover Has Steadily Increased since Establishment of Community Forests in Western Chitwan, Nepal

   https://doi.org/10.3390/rs12244071  

   Dai, Jie; Roberts, Dar A.; Stow, Douglas A.; An, Li; Zhao, Qunshan (December 2020, Remote Sensing)

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   Community forests have been established worldwide to sustainably manage forest ecosystem services while maintaining the livelihoods of local residents. The Chitwan National Park in Nepal is a world-renowned biodiversity hotspot, where community forests were consolidated in the park’s buffer zone after 1993. These western Chitwan community forests stand as the frontiers of human–environment interactions, nurturing endangered large mammal species while providing significant natural resources for local residents. Nevertheless, no systematic forest cover assessment has been conducted for these forests since their establishment. In this study, we examined the green vegetation dynamics of these community forests for the years 1988–2018 using Landsat surface reflectance products. Combining an automatic water extraction index, spectral mixture analysis and the normalized difference fraction index (NDFI), we developed water masks and quantified the water-adjusted green vegetation fractions and NDFI values in the forests. Results showed that all forests have been continuously greening up since their establishment, and the average green vegetation cover of all forests increased from approximately 30% in 1988 to above 70% in 2018. With possible contributions from the invasion of exotic understory plant species, we credit community forestry programs for some of the green-up signals. Monitoring of forest vegetation dynamics is critical for evaluating the effectiveness of community forestry as well as developing sustainable forest management policies. Our research will provide positive feedbacks to local community forest committees and users. 

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2. Assessing the effectiveness of vegetation indices in detecting forest disturbances in the southeast Amazon

   https://doi.org/10.1038/s41598-024-77924-3  

   Marques, Eduardo Q; Silvério, Divino V; Galvão, Lenio S; Aragão, Luiz_E_O C; Uribe, Maria R; Macedo, Marcia N; Rattis, Ludmila; Alencar, Ane_A C; Brando, Paulo M (December 2024, Scientific Reports)

   Amazon forests are becoming increasingly vulnerable to disturbances such as droughts, fires, windstorms, logging, and forest fragmentation, all of which lead to forest degradation. Nevertheless, quantifying the extent and severity of disturbances and their cumulative impact on forest degradation remains a significant challenge. In this study, we combined multispectral data from Landsat sensors with hyperspectral data from the Earth Observing-One (Hyperion/EO-1) sensor to evaluate the efficacy of multiple vegetation indices in detecting forest responses to disturbances in an experimentally burned forest in southeastern Amazonia. Our experimental area was adjacent to an agricultural field and consisted of three 50-ha treatments – an unburned Control, a plot burned every three years, and a plot burned annually from 2004 to 2010. All plots were monitored to assess vegetation recovery after fire disturbance. These areas were also affected by three drought events (2007, 2010, and 2016) over the study period. We evaluated a total of 18 Vegetation Indices (VI), one unique to Landsat, 12 unique to Hyperion/EO-1, and five commons to both satellites (i.e., 6 total from Landsat and 17 from Hyperion). We used linear models (LM) to evaluate how changes in ground observations of forest structure (biomass, leaf area index [LAI], and litter production) associated with fire were captured by the two VIs most sensitive to forest degradation. Our results indicate that the Plant Senescence Reflectance Index (PSRI) derived from Hyperion/EO-1 was the most sensitive to vegetation changes associated with forest fires, increasing by 94% in burned vs. unburned forests. Of the Landsat-derived VIs, we found that the Green-Red Normalized Difference (GRND) were the most sensitive to forest degradation by fire, showing a marked decline (87%) in the burned plots compared with the unburned Control. However, compared to PSRI, the GRND was a better predictor of changes associated with fire, both in the forest interior or forest edge, for the three ground variables: biomass stocks (r2 =0.5–0.8), LAI (r2=0.8–0.9), and litter production (r2=0.4–0.7). This study demonstrate that VIs can detect forest responses to fire and other disturbances over time, highlighting the relative strengths of each VI. In doing so, it shows how the integration of multispectral and hyperspectral data can be useful for monitoring tropical forest degradation and recovery. Moreover, it provides valuable insights into the limitations of existing approaches, which can inform the design of next-generation sensors for global forest monitoring. 

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3. Valuation of forest‐management and wildfire disturbance on water and carbon fluxes in mountain headwaters

   https://doi.org/10.1002/eco.2642  

   Chung, Min Gon; Guo, Han; Nyelele, Charity; Egoh, Benis N; Goulden, Michael L; Keske, Catherine M; Bales, Roger C (April 2024, Ecohydrology)

   Recent drought, wildfires and rising temperatures in the western US highlight the urgency of increasing resiliency in overstocked forests. However, limited valuation information hinders the broader participation of beneficiaries in forest management. We assessed how historical disturbances in California's Central Sierra Nevada affected live biomass, forest water use and carbon uptake and estimated marginal values of these changes. On average, low‐severity wildfire caused greater declines in forest evapotranspiration (ET), gross primary productivity (GPP) and live biomass than did commercial thinning. Low‐severity wildfires represent proxies for prescribed burns and both function as biomass removal to alleviate overstocked conditions. Increases in potential runoff over 15 years post‐disturbance were valued at $108,000/km²for commercial thinning versus $234,000/km²for low‐severity wildfire, based on historical water prices. Respective declines in GPP were valued at −$305,000 and −$1,317,000/km², based on an average social cost of carbon. Considering biomass levels created by commercial thinning and low‐severity fire as more‐sustainable management baselines for overstocked forests, carbon uptake over 15 years post‐disturbance can be viewed as a benefit rather than loss. Realizing this benefit upon management re‐entry may require sequestering thinned material. High‐severity wildfire and clearcutting resulted in greater declines in ET and thus greater potential water benefits but also substantial declines in GPP and live carbon. These lessons from historical disturbances indicate what benefit ranges from fuels treatments can be expected from more‐sustainable management of mixed‐conifer forests and the importance of setting an appropriate baseline. 

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4. Do actions reduce perceived risk? A longitudinal analysis of the relationship between risk perception and actions in response to forest disturbance in Colorado

   https://doi.org/10.1111/risa.14023  

   Qin, Hua; Vickery, Jamie; Brenkert‐Smith, Hannah; Bekee, Barituka; Prasetyo, Yanu (September 2022, Risk Analysis)

   As residents living in hazard-prone areas face on-going environmental threats, the actions they take to mitigate such risks are likely motivated by various factors. Whereas risk perception has been considered a key determinant of related behavioral responses, little is known about how risk mitigation actions influence subsequent perceived risk. In other words, do actions to prevent or mitigate risk reduce risk perception? This longitudinal study considers the dynamic relationships between risk perception and risk-mitigating behavior in the context of forest disturbance in north-central Colorado. Based on panel survey data collected in 2007 and 2018, the results provide a first look at changes in perceived forest risks as they relate to individual and community actions in response to an extensive mountain pine beetle outbreak. Analysis revealed that the perception of direct forest risks (forest fire and falling trees) increased, whereas indirect forest risk perception (concern on broader threats to local community) decreased across the two study phases. Higher individual or community activeness (level of actions) was associated with subsequent reductions in perceived forest fire risk, smaller increases in direct risk perception, and larger decreases in indirect risk perception. These findings contribute insights into the complex risk reappraisal process in forest hazard contexts, with direct implications for risk communication and management strategies. 

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5. Linking forest management to surrounding lands: a citizen-based approach towards the regional understanding of land-use transitions

   https://doi.org/10.3389/frsen.2023.1197523  

   Yang, Di; Fu, Chiung-Shiuan; Herrero, Hannah Victoria; Southworth, Jane; Binford, Michael (July 2023, Frontiers in Remote Sensing)

   The Southeastern United States has high landscape heterogeneity, with heavily managed forestlands, developed agriculture, and multiple metropolitan areas. The spatial pattern of land use is dynamic. Expansion of urban areas convert forested and agricultural land, scrub forests are converted to citrus groves, and some croplands transition to pine plantations. Previous studies have recognized that forest management is the predominant factor in structural and functional changes forests, but little is known about how forest management practices interact with surrounding land uses at the regional scale. The first step in studying the spatial relationships of forest management with surrounding landscapes is to be able to map management practices and describe their proximity to various land uses. There are two major difficulties in generating land use and land management maps at the regional scale by any method: the necessity of large training data sets and expensive computation. The combination of crowdsourced, citizen-science mapping and cloud-based computing may help overcome those difficulties. In this study, OpenStreetMap is incorporated into mapping land use and shows great potential for justifying and monitoring land use at a regional scale. Google Earth Engine enables large-scale spatial analysis and imagery processing by providing a variety of Earth observation datasets and computational resources. By incorporating the OpenStreetMap dataset into Earth observation images to map forest land management practices and determine the distribution of other nearby land uses, we develop a robust regional land-use mapping approach and describe the patterns of how different land uses may affect forest management and vice versa . We find that cropland is more likely to be near ecological forest management patches; few close spatial relationships exist between land uses and preservation forest management, which fulfills the preservation management strategy of sustaining the forests, and production forests have the strongest spatial relationships with croplands. This approach leads to increased understanding of land-use patterns and management practices at local to regional scales. 

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