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"Vegetation changes"
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Status and trends in Arctic vegetation
Changes in Arctic vegetation can have important implications for trophic interactions and ecosystem functioning leading to climate feedbacks. Plot-based vegetation surveys provide detailed insight into vegetation changes at sites around the Arctic and improve our ability to predict the impacts of environmental change on tundra ecosystems. Here, we review studies of changes in plant community composition and phenology from both long-term monitoring and warming experiments in Arctic environments. We find that Arctic plant communities and species are generally sensitive to warming, but trends over a period of time are heterogeneous and complex and do not always mirror expectations based on responses to experimental manipulations. Our findings highlight the need for more geographically widespread, integrated, and comprehensive monitoring efforts that can better resolve the interacting effects of warming and other local and regional ecological factors.
Journal Article
Climate change and plants : biodiversity, growth and interactions
\"Evidence raises every day of the varying climate and its impression on both plants and animals. Climatic changes influence all the agriculture factors, which can potentially adversely affect their productivity. Plant activities are intimately associated to climate and concentration of atmospheric carbon dioxide. The book Climate change and Plants Interactions: Complexities and Surprise examines how plant growth characters influences/influenced by the climate change both in past and present scenarios. The book cover papers present the cutting-edge research in key determinates of plant growth in response to atmospheric CO2 enhancement and global warming. Salient Features Discourses numerous goals of sustainable development goals projected by the UN as part of the 2030 agenda. Highlights the appropriate approaches for maintaining better plant growth under changing climatic conditions Presents diversity of techniques used across plant science. Design to cater to the needs of researchers, technologists, policy makers and undergraduates and postgraduates' students studying, sustainable crop production, crop protection. Addresses plant responses to atmospheric CO2 increase\"-- Provided by publisher.
Book
Long-term changes in regional vegetation cover along the west coast of southern Norway: The importance of human impact
Questions: How open was the landscape prior to agriculture? Did agriculture start earlier in the south than in the north? How did the vegetation change in different regions after the introduction of agriculture? Location: Coast of SW and W Norway. Methods: The REVEALS (Regional Estimates of VEgetation Abundance from Large Sites) model is applied for pollen-based vegetation reconstruction in 19 time windows over the last 9,000 years. Pollen data from 63 sites (lakes and bogs) are compiled and systematically used for data analysis so that the structure of vegetation change in space and time is captured. Results: Estimated cover of selected trees, shrubs, Calluna, graminids and herbs indicate a partly open outer coast throughout the Holocene. The highest tree cover is estimated for 8,200–6,200 cal. BP. Broad-leaved trees (Fraxinus, Quercus, Tilia and Ulmus) spread from south to north and were present in the whole region at the end of the Mesolithic (5,950 cal. BP). Larger spatial variation in tree cover and a step-wise reduction in deciduous trees after 5,700 cal. BP is concordant with increases in open-land taxa indicating human activity. Vegetation changes caused by agriculture are indicated in the very south from ca. 5,950 cal. BP. Distinct human-induced vegetation changes with spatial differentiation took place from 4,200 to 1,700 cal. BP, when most of the areas earlier covered by deciduous woodland had been transformed to cultivated fields, grasslands and heathlands. Increased Poaceae cover from 1,700 cal. BP probably reflects the expansion of mown meadows in addition to pastures. Conclusions: Capturing continuous changes of vegetation structure in space and time elucidates open areas along the western coast prior to the introduction of agriculture. Agriculture started earliest in the very south and spread rapidly along the whole coast prior to the Late Neolithic. Differences within the study area have existed in all time periods, reflecting different land-use practices adapted to different natural conditions.
Journal Article
Land Use Effects on Climate: Current State, Recent Progress, and Emerging Topics
Purpose of Review
As demand for food and fiber, but also for negative emissions, brings most of the Earth’s land surface under management, we aim to consolidate the scientific progress of recent years on the climatic effects of global land use change, including land management, and related land cover changes (LULCC).
Recent Findings
We review the methodological advances in both modeling and observations to capture biogeochemical and biogeophysical LULCC effects and summarize the knowledge on underlying mechanisms and on the strength of their effects. Recent studies have raised or resolved several important questions related to LULCC: How can we derive CO
2
fluxes related to LULCC from satellites? Why are uncertainties in LULCC-related GHG fluxes so large? How can we explain that estimates of afforestation/reforestation potentials diverge by an order of magnitude? Can we reconcile the seemingly contradicting results of models and observations concerning the cooling effect of high-latitude deforestation?
Summary
Major progress has been achieved in understanding the complementarity of modeling, observations, and inventories for estimating the impacts of various LULCC practices on carbon, energy, and water fluxes. Emerging fields are the operationalization of the recently achieved integration of approaches, such as a full greenhouse gas balance of LULCC, mapping of emissions from global models to country-reported emissions data, or model evaluation against local biogeophysical observations. Fundamental challenges remain, however, e.g., in separating anthropogenic from natural land use dynamics and accurately quantifying the first. Recent progress has laid the foundation for future research to integrate the local to global scales at which the various effects act, to create co-benefits between global mitigation, including land-based carbon dioxide removal, and changes in local climate for effective adaptation strategies.
Journal Article
Monitoring and Mapping Vegetation Cover Changes in Arid and Semi-Arid Areas Using Remote Sensing Technology: A Review
Vegetation cover change is one of the key indicators used for monitoring environmental quality. It can accurately reflect changes in hydrology, climate, and human activities, especially in arid and semi-arid regions. The main goal of this paper is to review the remote sensing satellite sensors and the methods used for monitoring and mapping vegetation cover changes in arid and semi-arid. Arid and semi-arid lands are eco-sensitive environments with limited water resources and vegetation cover. Monitoring vegetation changes are especially important in arid and semi-arid regions due to the scarce and sensitive nature of the plant cover. Due to expected changes in vegetation cover, land productivity and biodiversity might be affected. Thus, early detection of vegetation cover changes and the assessment of their extent and severity at the local and regional scales become very important in preventing future biodiversity loss. Remote sensing data are useful for monitoring and mapping vegetation cover changes and have been used extensively for identifying, assessing, and mapping such changes in different regions. Remote sensing data, such as satellite images, can be obtained from satellite-based and aircraft-based sensors to monitor and detect vegetation cover changes. By combining remotely sensed images, e.g., from satellites and aircraft, with ground truth data, it is possible to improve the accuracy of monitoring and mapping techniques. Additionally, satellite imagery data combined with ancillary data such as slope, elevation, aspect, water bodies, and soil characteristics can detect vegetation cover changes at the species level. Using analytical methods, the data can then be used to derive vegetation indices for mapping and monitoring vegetation.
Journal Article
Separating direct and indirect effects of rising temperatures on biogenic volatile emissions in the Arctic
Volatile organic compounds (VOCs) are released from biogenic sources in a temperature-dependent manner. Consequently, Arctic ecosystems are expected to greatly increase their VOC emissions with ongoing climate warming, which is proceeding at twice the rate of global temperature rise. Here, we show that ongoing warming has strong, increasing effects on Arctic VOC emissions. Using a combination of statistical modeling on data from several warming experiments in the Arctic tundra and dynamic ecosystem modeling, we separate the impacts of temperature and soil moisture into direct effects and indirect effects through vegetation composition and biomass alterations. The indirect effects of warming on VOC emissions were significant but smaller than the direct effects, during the 14-y model simulation period. Furthermore, vegetation changes also cause shifts in the chemical speciation of emissions. Both direct and indirect effects result in large geographic differences in VOC emission responses in the warming Arctic, depending on the local vegetation cover and the climate dynamics. Our results outline complex links between local climate, vegetation, and ecosystem–atmosphere interactions, with likely local-to-regional impacts on the atmospheric composition.
Journal Article
Vegetation Cover Change and Its Attribution in China from 2001 to 2018
It is confirmed that China has been greening over the last two decades. Such greening and its driving factors are therefore significant for understanding the relationship between vegetation and environments. However, studies on vegetation changes and attribution analyses at the national scale are limited in China after 2000. In this study, fractional vegetation cover (FVC) data from Global Land Surface Satellite (GLASS) was used to detect vegetation change trends from 2001 to 2018, and the effects of CO2, temperature, shortwave radiation, precipitation, and land cover change (LCC) on FVC changes were quantified using generalized linear models (GLM). The results showed that (1) FVC in China increased by 14% from 2001 to 2018 with a greening rate of approximately 0.0019/year (p < 0.01), which showed an apparent greening trend. (2) On the whole, CO2, climate-related factors, and LCC accounted for 88% of FVC changes in China, and the drivers explained 82%, 89%, 90%, and 89% of the FVC changes in the Qinghai–Tibet region, northwest region, northern region, and southern region, respectively. CO2 was the major driving factor for FVC changes, accounting for 31% of FVC changes in China, indicating that CO2 was an essential factor in vegetation growth research. (3) The statistical results of pixels with land cover changes showed that LCC explained 12% of FVC changes, LCC has played a relatively important role and this phenomenon may be related to the ecological restoration projects. This study enriches the study of vegetation changes and its driving factors, and quantitatively describes the response relationship between vegetation and its driving factors. The results have an important significance for adjusting terrestrial ecosystem services.
Journal Article
Turning Down the Heat
Climate change is projected to dramatically increase boreal wildfire activity, with broad ecological and socioeconomic consequences. As global temperatures rise, periods with elevated fire weather are expected to increase in frequency and duration, which would be expected to increase the number and size of fires. Statistical forecasts or simulations of future fire activity often account for direct climatic effects only, neglecting other controls of importance, such as biotic feedbacks. This could result in overestimating the effects of climate change on fire activity, if the future distribution of vegetation or fuels were to change. We incorporated sensitivity to climate or fire weather and vegetation in a fire simulation model and represented explicitly two key biotic feedbacks linked to succession and regeneration processes. We used this model to forecast annual fire activity from 2011 to 2099 over a large region of boreal forest in Québec, Canada, dominated by balsam fir (Abies balsamea (L.) Mill) and yellow birch (Betula alleghaniensis Britt.) or paper birch (Betula papyrifera Marsh.), with and without the biotic feedbacks. Our simulations show that vegetation changes triggered by fire disturbance altered future fire activity and may even be as important a driver as climate change itself. Indeed, over the course of the century, vegetation changes were projected to offset much of the increase in fire activity that would be expected due to global warming as such. It follows that if biotic feedbacks are not included in statistical or simulation-based forecasts, the resultant projections of future fire activity could be biased upward to a very considerable degree. For the case of end-ofcentury mean annual burn rate, we estimated this positive bias to be as high as 400%. Accounting for biotic feedbacks in simulation models is therefore necessary for accurate projection of future wildfire activity and associated vegetation changes. Purely statistical forecasts based on current vegetation cannot be relied upon, in the presence of biotic feedbacks. Our results further suggest that vegetation management could reduce fire risk in some systems by altering the abundance and distribution of the most highly flammable fuels and thus mitigate the impact of climate change on fire activity.
Journal Article
Spatial and Temporal Analyses of Vegetation Changes at Multiple Time Scales in the Qilian Mountains
The Qilian Mountains (QLMs), an important ecological protective barrier and major water resource connotation area in the Hexi Corridor region, have an important impact on ecological security in western China due to their ecological changes. However, most existing studies have investigated vegetation changes and their main driving forces in the QLMs on the basis of a single scale. Thus, the interactions among multiple environmental factors in the QLMs are still unclear. This study was based on normalised difference vegetation index (NDVI) data from 2000 to 2019. We systematically analysed the spatial and temporal characteristics of the QLMs at multiple time scales using trend analysis, ensemble empirical mode decomposition, Geodetector, and correlation analysis methods. At different time scales under single-factor and multi-factor interactions, we examined the mechanisms of the vegetation changes and their drivers. Our results showed that the vegetation in the QLMs showed a trend of overall improvement in 2000–2019, at a rate of 0.88 × 10−3, mainly in the central western regions. The NDVI in the QLMs showed a short change cycle of 3 and 5 years and a long-term trend. Sunshine time and wind speed were the main drivers of the vegetation variation in the QLMs, followed by temperature. Precipitation affected the vegetation spatial variation within a certain altitude range. However, temperature and precipitation had stronger explanatory powers for the vegetation variation in the western QLMs than in the eastern part. Their interaction was the dominant factor in the regional differences in vegetation. The responses of the NDVI to temperature and precipitation were stronger in the long time series. The main drivers of vegetation variation were land surface temperature and precipitation in the east and temperature and evapotranspiration in the west. Precipitation was the main driver of vegetation growth in the northern and southwestern QLMs on both the short- and long-term scales. Vegetation changes were more significantly influenced by short-term temperature changes in the east but by a combination of temperature and precipitation in most parts of the QLMs on a 5-year time scale.
Journal Article