Characteristics and Drivers of Vegetation Change in Xinjiang, 2000–2020

Forests, Journal Year: 2024, Volume and Issue: 15(2), P. 231 - 231

Published: Jan. 25, 2024

Examining the features of vegetation change and analyzing its driving forces across an extensive time series in Xinjiang are pivotal for ecological environment. This research can offer a crucial point reference regional conservation endeavors. We calculated fractional cover (FVC) using MOD13Q1 data accessed through Google Earth Engine (GEE) platform. To discern characteristics changes forecast future trends, we employed analysis, coefficient variation, Hurst exponent. The correlation between climate factors FVC was investigated analysis. Simultaneously, to determine relative impact meteorological anthropogenic actions on FVC, utilized multiple regression residual Furthermore, adhering China’s functional zone classification, segmented into five zones: R1 Altai Mountains-Junggar West Mountain Forest Grassland Ecoregion, R2 Junggar Basin Desert R3 Tianshan Mountains R4 Tarim Basin-Eastern Frontier R5 Pamir-Kunlun Mountains-Altan Alpine Ecoregion. A comparative analysis these regions subsequently conducted. results showed following: (1) During first two decades 21st century, overall primarily exhibited trend growth, exhibiting rate increase 4 × 10−4 y−1. multi-year average 0.223. mean value 0.223, values different zones following order: > R4. (2) predominant spatial pattern Xinjiang’s landscape is characterized by higher coverage northwest lower southeast. In this region, 66.63% terrain exhibits deteriorating vegetation, while 11% region notable rise plant growth. Future will be dominated decreasing trend. Regarding variation outcomes, minor representing 42.12% total, noticeable; stands at 0.2786. stability varied follows R5. (3) Factors that have facilitating effect included humidity, daylight hours, precipitation, with humidity having greater influence, hindering air temperature wind speed, speed influence. (4) Vegetation alterations influenced change, human activities play secondary role, contributing 56.93% 43.07%, respectively. underscores necessity continued surveillance dynamics enhancement policies focused habitat renewal safeguarding Xinjiang.

Language: Английский

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Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(20), P. 4063 - 4063

Published: Oct. 11, 2021

Climate change has proven to have a profound impact on the growth of vegetation from various points view. Understanding how changes and its response climatic shift is vital importance for describing their mutual relationships projecting future land–climate interactions. Arid areas are considered be regions that respond most strongly climate change. Xinjiang, as typical dryland in China, received great attention lately unique ecological environment. However, comprehensive studies examining driving factors across Xinjiang rare. Here, we used remote sensing datasets (MOD13A2 TerraClimate) data meteorological stations investigate trends dynamic Normalized Difference Vegetation Index (NDVI) 2000 2019 based Google Earth platform. We found increment rates growth-season mean maximum NDVI were 0.0011 per year 0.0013 year, respectively, by averaging all pixels region. The results also showed that, compared with other land use types, cropland had fastest greening rate, which was mainly distributed among northern Tianshan Mountains Southern Junggar Basin margin Tarim Basin. browning primarily spread over Ili River Valley where grasslands distributed. Moreover, there trend warming wetting past 20 years; this determined analyzing data. Through correlation analysis, contribution precipitation (R2 = 0.48) greater than temperature 0.42) throughout Xinjiang. Standardized Precipitation Evapotranspiration (SPEI) computed better between arid areas. Our could improve local management ecosystems provide insights into complex interaction

Language: Английский

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Drought metrics and temperature extremes over the Okavango River basin, southern Africa, and links with the Botswana high

International Journal of Climatology, Journal Year: 2023, Volume and Issue: 43(14), P. 6463 - 6483

Published: Aug. 10, 2023

Abstract The Okavango River Basin (ORB), including the World Heritage site Delta, is a region of high biodiversity projected to suffer increased early summer drying under climate change. Little work has been done on drought over this sensitive region. Here, various metrics are analysed ORB. These include cumulative intensity index, based product maximum temperature anomaly and duration dry spell, Standardized Precipitation‐Evapotranspiration Index. Strong gradients in spell hot day frequencies shift south ORB from August November as tropical rain‐belt moves increasingly equator, Congo Air Boundary declines Botswana High strengthens southwestwards. By December, gradient vanished while that across Limpopo southern region, where centred, prominent. sub‐seasonal analyses highlight October–November 2013–2021 particularly Delta This epoch appears related stronger southward shifted reduced low‐level moisture convergence. On interannual scales, strong relationships were found with El Niño‐Southern Oscillation (ENSO). shows drying‐warming trend, significant strengthening High. trends, together Coupled Model Intercomparison Project Phase 6 Africa, may impact severely ecosystems agriculture, important implications for management agricultural activities, water resources biodiversity.

Language: Английский

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Teleconnections of Atmospheric Circulations to Meteorological Drought in the Lancang-Mekong River Basin

Atmosphere, Journal Year: 2024, Volume and Issue: 15(1), P. 89 - 89

Published: Jan. 10, 2024

The Lancang-Mekong River Basin (LMRB) is one of the major transboundary basins globally, facing ongoing challenges due to flood and drought disasters. Particularly in past two decades, basin has experienced an increased frequency meteorological events, posing serious threats local socio-economic structures ecological systems. Thus, this study aimed analyze characteristics LMRB identify impact correlation atmospheric circulation on basin. Specifically, different levels events were defined using Run Theory based seasonal annual SPEI from 1980 2018. time lag between EI Nino-Southern Oscillation (ENSO), Arctic (AO), North Atlantic (NAO), Pacific Decadal (PDO), analyzed LMRB. Our results indicated that, a temporal perspective, period November April following year was particularly prone droughts In terms spatial distribution, primary agricultural regions within basin, including Thailand, Eastern Cambodia, Vietnam, highly susceptible droughts. Further analysis revealed teleconnection factors. sensitivity basin’s timing its response decreased order ENSO > AO NAO PDO. general, had most substantial influence with strongest relationship, while upper reaches displayed significant AO; occurrence progression area synchronized AO. These findings enhance our understanding drought-prone areas LMRB, factors driving mechanisms involved. This information valuable for effectively mitigating managing risks region.

Language: Английский

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Modeling and analyzing supply-demand relationships of water resources in Xinjiang from a perspective of ecosystem services

Journal of Arid Land, Journal Year: 2022, Volume and Issue: 14(2), P. 115 - 138

Published: Feb. 1, 2022

Language: Английский

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Assessment of Vegetation Dynamics in Xinjiang Using NDVI Data and Machine Learning Models from 2000 to 2023

Sustainability, Journal Year: 2025, Volume and Issue: 17(1), P. 306 - 306

Published: Jan. 3, 2025

This study utilizes NASA’s Normalized Difference Vegetation Index (NDVI) data from the Google Earth Engine (GEE) platform and employs methods such as mean analysis, trend Hurst index to assess NDVI dynamics in Xinjiang, with a particular focus on desert, meadow, grassland vegetation. Furthermore, multiple linear regression, random forest, support vector machines, XGBoost models are applied construct evaluate prediction models. The key driving forces identified ranked based results of optimal model. Changes vegetation cover response these analyzed using Mann–Kendall test partial correlation analysis. indicate following: (1) From 2000 2023, annual variation Xinjian fluctuates at rate 0.0012 per year. intra-annual follows an inverted U shape, meadow exhibiting highest monthly fluctuations. (2) During this period, average Xinjiang ranges 0 0.3, covering 74.74% region. Spatially, higher values observed north northwest, while lower concentrated south southeast. (3) overall slope between 2023 −0.034 0.047, indicating no significant upward trend. According index, future projections suggest shift improvement potential degradation. (4) Machine learning developed predict NDVI, forest showing precision. Soil moisture, runoff, evaporation drivers. In last 24 years, temperatures have generally increased, precipitation, soil runoff declined. There is negative both temperature evaporation, positive significant, distinct spatial variations throughout has been increasing, but outlook less promising. Enhanced environmental monitoring protective measures essential moving forward.

Language: Английский

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Andean grassland stability across spatial scales increases with camelid grazing intensity despite biotic homogenization

Journal of Ecology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 23, 2025

Abstract Intensive land use and changing environmental conditions are reshaping the biodiversity, functioning stability of local Andean grassland communities. It remains unclear whether these effects propagate to larger spatial scales that most relevant for policy conservation. Using a multiscale framework, we quantified influence grazing intensity factors on diversity temporal productivity in plant communities at both (within communities) (among neighbouring scales. We found higher soil total nitrogen were related greater (alpha stability) (gamma Higher gamma resulted from enhanced asynchrony among despite biotic homogenization. That is, while reduced compositional differences (beta diversity) which turn decreased asynchrony, this indirect effect was not strong enough counteract direct positive stability. Additionally, with increasing acidification but did alpha or Synthesis : Our results emphasize necessity considering complex influences different effective management grasslands.

Language: Английский

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A Forecast Model Applied to Monitor Crops Dynamics Using Vegetation Indices (NDVI)

Applied Sciences, Journal Year: 2021, Volume and Issue: 11(4), P. 1859 - 1859

Published: Feb. 20, 2021

Vegetation dynamics is very sensitive to environmental changes, particularly in arid zones where climate change more prominent. Therefore, it important investigate the response of this those changes and understand its evolution according different climatic factors. Remote sensing techniques provide an effective system monitor vegetation on multiple scales using indices (VI), calculated from remote reflectance measurements visible infrared regions electromagnetic spectrum. In study, we use normalized difference index (NDVI), provided MOD13Q1 V006 at 250 m spatial resolution product derived MODIS sensor. NDVI frequent studies related mapping, crop state indicator, biomass estimator, drought monitoring evapotranspiration. paper, a combination forecasts perform time series models predict optical data. The proposed ensemble constructed forecasting based analysis, such as Double Exponential Smoothing autoregressive integrated moving average with explanatory variables for better prediction performance. method validated maize plots one olive plot. results after combining show positive influence several weather measures, namely, temperature, precipitation, humidity radiation.

Language: Английский

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Is There Spatial Dependence or Spatial Heterogeneity in the Distribution of Vegetation Greening and Browning in Southeastern China?

Forests, Journal Year: 2022, Volume and Issue: 13(6), P. 840 - 840

Published: May 28, 2022

Vegetation is an indispensable component of terrestrial ecosystems and plays irreplaceable role in mitigation climate change. Global vegetation changes (i.e., greening browning) still occur frequently, however, little known about the spatial relationships between these two processes. Based on normalized difference index (NDVI) dataset from 1998 to 2018 Fujian Province, China. The Theil-Sen Mann-Kendall tests were used explore temporal growing, then browning was distinguished with bivariate autocorrelation analysis, variation relationship driving factors explored by geographical detector. results showed that 2018, average NDVI value increased 0.75 0.83; 89.61% study area experienced greening, while 5.7% significant browning, active occurred along roads nearby cities. dominated heterogeneity high low H-L clusters accounting for 60% L-H 14%), but we also revealed there quite a few places (4%) dependence H-H clusters), occurring around urban areas roads. factor detector indicated nighttime light intensity among most dominant changes, followed elevation slope. Although individual effect distance relatively weak its indirect found be strongest interaction detector, which obtained interactions much larger than independent impact. Simultaneously, risk preferred lower (<1.1 nW cm−2sr−1), higher (>43.4 m) slope (>6.3°). Moreover, primarily within 1685.4 m Our findings could deepen understanding change patterns provide advice mitigating impact changes.

Language: Английский

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Andean peatlands at risk? Spatiotemporal patterns of extreme NDVI anomalies, water extraction and drought severity in a large-scale mining area of Atacama, northern Chile

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2022, Volume and Issue: 116, P. 103138 - 103138

Published: Dec. 12, 2022

In the Andes, multiple human and climatic factors threaten conservation of bofedales, a type high altitude peat forming wetland widely distributed in tropical subtropical Andes. northern Chile, climate change water extraction for industrial activities are among most significant threats to these relevant socio-hydrological systems hosting indigenous pastoral communities. this study, we present an integrated analysis Normalized Difference Vegetation Index (NDVI) anomalies, drought severity rights granted industry provide insight on status historical drivers their transformation, current threats. Using Landsat satellite imagery from 1986 2018, identify spatio-temporal NDVI changes 442 bofedales one leading copper producing regions world. The time series over 32 growing seasons was used detect extreme i.e. values outside 95 % reference frequency distribution, indicating periods productivity Andes wetlands. To evaluate relationship between continued activities, combine climate-based multi-temporal-scale index (SPEI) with geospatial latitudinal distribution extractive industries study area. Over period analysis, total amount increased 465 1,201 l/s recorded before 1985 5,584 2018. areas where highest concentrated, 21.3°S 22.1°S, "green" (NDVI>=0.23) practically absent. austral summer (JFM) highly correlated occurring during three months season peak. While our findings show bofedal is mostly influenced by precipitation temperature wet period, results also raise questions regarding possible loss previous 80 years prior record, wherein have significantly according official records.

Language: Английский

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