scholarly journals The European Forest Condition Monitor: Using Remotely Sensed Forest Greenness to Identify Hot Spots of Forest Decline

2021 ◽  
Vol 12 ◽  
Author(s):  
Allan Buras ◽  
Anja Rammig ◽  
Christian S. Zang
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Environmental Stress ◽  
Forest Decline ◽  
Tree Mortality ◽  
Spring Phenology ◽  
Forest Condition ◽  
Late Frost ◽  
European Forest ◽  
Condition Monitor

Forest decline, in course of climate change, has become a frequently observed phenomenon. Much of the observed decline has been associated with an increasing frequency of climate change induced hotter droughts while decline induced by flooding, late-frost, and storms also play an important role. As a consequence, tree mortality rates have increased across the globe. Despite numerous studies that have assessed forest decline and predisposing factors for tree mortality, we still lack an in-depth understanding of (I) underlying eco-physiological mechanisms, (II) the influence of varying environmental conditions related to soil, competition, and micro-climate, and (III) species-specific strategies to cope with prolonged environmental stress. To deepen our knowledge within this context, studying tree performance within larger networks seems a promising research avenue. Ideally such networks are already established during the actual period of environmental stress. One approach for identifying stressed forests suitable for such monitoring networks is to assess measures related to tree vitality in near real-time across large regions by means of satellite-borne remote sensing. Within this context, we introduce the European Forest Condition monitor (EFCM)—a remote-sensing based, freely available, interactive web information tool. The EFCM depicts forest greenness (as approximated using NDVI from MODIS at a spatial resolution of roughly 5.3 hectares) for the pixel-specific growing season across Europe and consequently allows for guiding research within the context of concurrent forest performance. To allow for inter-temporal comparability and account for pixel-specific features, all observations are set in relation to normalized difference vegetation index (NDVI) records over the monitoring period beginning in 2001. The EFCM provides both a quantile-based and a proportion-based product, thereby allowing for both relative and absolute comparison of forest greenness over the observational record. Based on six specific examples related to spring phenology, drought, late-frost, tree die-back on water-logged soils, an ice storm, and windthrow we exemplify how the EFCM may help identifying hotspots of extraordinary forest greenness. We discuss advantages and limitations when monitoring forest condition at large scales on the basis of moderate resolution remote sensing products to guide users toward an appropriate interpretation.

Drought-induced tree mortality: ecological consequences, causes, and modeling

2012 ◽  
Vol 20 (2) ◽  
pp. 109-121 ◽  
Author(s):  
Weifeng Wang ◽  
Changhui Peng ◽  
Daniel D. Kneeshaw ◽  
Guy R. Larocque ◽  
Zhibin Luo
Keyword(s):  
Climate Change ◽  
Forest Decline ◽  
Tree Mortality ◽  
Current Knowledge ◽  
Species Turnover ◽  
Optimal Growth ◽  
Research Process ◽  
Future Research ◽  
Ecological Consequences ◽  
Carbon Demand

Drought-induced tree mortality, which rapidly alters forest ecosystem composition, structure, and function, as well as the feedbacks between the biosphere and climate, has occurred worldwide over the past few decades, and is expected to increase pervasively as climate change progresses. The objectives of this review are to (1) highlight the likely ecological consequences of drought-induced tree mortality, (2) synthesize the hypotheses related to drought-induced tree mortality, (3) discuss the implications of current knowledge for modeling tree mortality processes under climate change, and (4) highlight future research needs. First, we emphasize the likely ecological consequences of tree mortality from ecosystem to biome to continental scales. We then document and criticize multiple non-exclusive tree mortality hypotheses (e.g., carbon starvation — carbon supply is less than carbon demand; and hydraulic failure — desiccation from failed water transport) from a more comprehensive ecological perspective. Next, we extend a forest decline concept model, Manion’s framework, by considering new emerging environmental conditions, for a more thorough understanding of the effects of climate change on forest decline. We find that an increase in drought frequency and (or) climate-change-type droughts may trigger increased background tree mortality rates and severe forest dieback events, accelerating species turnover and ecological regime shifts. The contribution of CO2 fertilization, rising temperature within the optimal growth range, and increased nitrogen deposition may defer or reduce this trend in tree mortality, but such contributions will vary between locations, species, and tree sizes. Multiple hypotheses proposed for drought-induced tree mortality are discussed, but coupling carbon and water cycles could help resolve the debate. The absence of a physiological understanding of tree mortality mechanisms limits the predictive ability of current models from stand-level process-based models to dynamic global vegetation models. We thus suggest that long-term observations, experiments, and models should be tightly interwoven during the research process to better forecast future climate changes and evaluate their impacts on forests.

Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau

2021 ◽  
Vol 41 (6) ◽  
pp. 3725-3742
Author(s):  
Jie Peng ◽  
Chaoyang Wu ◽  
Xiaoyue Wang ◽  
Linlin Lu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Spring Phenology

scholarly journals Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2014
Author(s):  
Celina Aznarez ◽  
Patricia Jimeno-Sáez ◽  
Adrián López-Ballesteros ◽  
Juan Pablo Pacheco ◽  
Javier Senent-Aparicio
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Ecosystem Services ◽  
Water Resources ◽  
Swat Model ◽  
Remote Sensing Data ◽  
Erosion Control ◽  
Sensing Data ◽  
Extreme Precipitation Events ◽  
The Impact

Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment.

scholarly journals Phenological Analysis of Sub-Alpine Forest on Jeju Island, South Korea, Using Data Fusion of Landsat and MODIS Products

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 286
Author(s):  
Sang-Jin Park ◽  
Seung-Gyu Jeong ◽  
Yong Park ◽  
Sang-hyuk Kim ◽  
Dong-kun Lee ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Data Fusion ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Study Region ◽  
Modis Imagery ◽  
Increasing Temperature

Climate change poses a disproportionate risk to alpine ecosystems. Effective monitoring of forest phenological responses to climate change is critical for predicting and managing threats to alpine populations. Remote sensing can be used to monitor forest communities in dynamic landscapes for responses to climate change at the species level. Spatiotemporal fusion technology using remote sensing images is an effective way of detecting gradual phenological changes over time and seasonal responses to climate change. The spatial and temporal adaptive reflectance fusion model (STARFM) is a widely used data fusion algorithm for Landsat and MODIS imagery. This study aims to identify forest phenological characteristics and changes at the species–community level by fusing spatiotemporal data from Landsat and MODIS imagery. We fused 18 images from March to November for 2000, 2010, and 2019. (The resulting STARFM-fused images exhibited accuracies of RMSE = 0.0402 and R2 = 0.795. We found that the normalized difference vegetation index (NDVI) value increased with time, which suggests that increasing temperature due to climate change has affected the start of the growth season in the study region. From this study, we found that increasing temperature affects the phenology of these regions, and forest management strategies like monitoring phenology using remote sensing technique should evaluate the effects of climate change.

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