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1

Deil, Ulrich, and Javier Loidi. "Vegetation and climate - an introduction." Phytocoenologia 30, no. 3-4 (November 24, 2000): 275–77. http://dx.doi.org/10.1127/phyto/30/2000/275.

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2

He, Dong, Xianglin Huang, Qingjiu Tian, and Zhichao Zhang. "Changes in Vegetation Growth Dynamics and Relations with Climate in Inner Mongolia under More Strict Multiple Pre-Processing (2000–2018)." Sustainability 12, no. 6 (March 24, 2020): 2534. http://dx.doi.org/10.3390/su12062534.

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Inner Mongolia Autonomous Region (IMAR) is related to China’s ecological security and the improvement of ecological environment; thus, the vegetation’s response to climate changes in IMAR has become an important part of current global change research. As existing achievements have certain deficiencies in data preprocessing, technical methods and research scales, we correct the incomplete data pre-processing and low verification accuracy; use grey relational analysis (GRA) to study the response of Enhanced Vegetation Index (EVI) in the growing season to climate factors on the pixel scale; explo
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3

Webb, Thompson. "Climate and Vegetation." Ecology 69, no. 1 (February 1988): 294–95. http://dx.doi.org/10.2307/1943188.

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4

UCHIJIMA, Zenbei. "Climate and Vegetation." Journal of Geography (Chigaku Zasshi) 102, no. 6 (1993): 745–62. http://dx.doi.org/10.5026/jgeography.102.6_745.

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5

Brovkin, V. "Climate-vegetation interaction." Journal de Physique IV (Proceedings) 12, no. 10 (November 2002): 57–72. http://dx.doi.org/10.1051/jp4:20020452.

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6

Woodward, F. I., and I. F. McKee. "Vegetation and climate." Environment International 17, no. 6 (January 1991): 535–46. http://dx.doi.org/10.1016/0160-4120(91)90166-n.

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7

Loehle, C. "Predicting Pleistocene climate from vegetation." Climate of the Past Discussions 2, no. 5 (October 23, 2006): 979–1000. http://dx.doi.org/10.5194/cpd-2-979-2006.

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Abstract. Climates at the Last Glacial Maximum have been inferred from fossil pollen assemblages, but these inferred climates are colder than those produced by climate simulations. Biogeographic evidence also argues against these inferred cold climates. The recolonization of glaciated zones in eastern North America following the last ice age produced distinct biogeographic patterns. It has been assumed that a wide zone south of the ice was tundra or boreal parkland (Boreal-Parkland Zone or BPZ), which would have been recolonized from southern refugia as the ice melted, but the patterns in this
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8

An, Huicong, Xiaorong Zhang, and Jiaqi Ye. "Analysis of Vegetation Environmental Stress and the Lag Effect in Countries along the “Six Economic Corridors”." Sustainability 16, no. 8 (April 15, 2024): 3303. http://dx.doi.org/10.3390/su16083303.

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Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and chang
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9

Smith, H. Jesse. "The vegetation-climate loop." Science 356, no. 6343 (June 15, 2017): 1134.17–1136. http://dx.doi.org/10.1126/science.356.6343.1134-q.

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10

Du, Guoming, Shouhong Yan, Hang Chen, Jian Yang, and Youyue Wen. "Intra-Annual Cumulative Effects and Mechanisms of Climatic Factors on Global Vegetation Biomes’ Growth." Remote Sensing 16, no. 5 (February 23, 2024): 779. http://dx.doi.org/10.3390/rs16050779.

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Previous studies have shown that climate change has significant cumulative effects on vegetation growth. However, there remains a gap in understanding the characteristics of cumulative climatic effects on different vegetation types and the underlying driving mechanisms. In this study, using the normalized difference vegetation index data from 1982 to 2015, along with accumulated temperature, precipitation, and solar radiation data, we quantitatively investigated the intra-annual cumulative effects of climatic factors on global vegetation biomes across climatic zones. We also explored the under
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11

Whitlock, Cathy. "Postglacial Fire Frequency and its Relation to Long-Term Vegetational and Climatic Changes in Yellowstone Park." UW National Parks Service Research Station Annual Reports 16 (January 1, 1992): 212–18. http://dx.doi.org/10.13001/uwnpsrc.1992.3123.

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The primary research objective has been to study the vegetational history of Yellowstone and its sensitivity to changes in climate and fire frequency. To establish a sequence of vegetational changes, a network of pollen records spanning the last 14,000 years has been studied from different types of vegetation within the Park. The relationship between modern pollen rain, modern vegetation and present­day climate in the northern Rocky Mountains has been the basis for interpreting past vegetation and climate from the fossil records. Changes in fire regime during the past 14,000 years have been i
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12

Troch, P. A., G. Carrillo, M. Sivapalan, T. Wagener, and K. Sawicz. "Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution." Hydrology and Earth System Sciences Discussions 10, no. 3 (March 7, 2013): 2927–54. http://dx.doi.org/10.5194/hessd-10-2927-2013.

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Abstract. Catchment hydrologic partitioning, regional vegetation composition and soil properties are strongly affected by climate, but the effects of climate-vegetation-soil interactions on river basin water balance are still poorly understood. Here we use a physically-based hydrologic model separately parameterized in 12 US catchments across a climate gradient to decouple the impact of climate and landscape properties to gain insight into the role of climate-vegetation-soil interactions in long-term hydrologic partitioning. The 12 catchment models (with different parameterizations) are subjec
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13

Wang, Qin, Qin Ju, Yueyang Wang, Quanxi Shao, Rongrong Zhang, Yanli Liu, and Zhenchun Hao. "Vegetation Changing Patterns and Its Sensitivity to Climate Variability across Seven Major Watersheds in China." International Journal of Environmental Research and Public Health 19, no. 21 (October 26, 2022): 13916. http://dx.doi.org/10.3390/ijerph192113916.

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Climate changes have profound impacts on vegetation and further alter hydrological processes through transpiration, interception, and evaporation. This study investigated vegetation’s changing patterns and its sensitivity to climate variability across seven major watersheds in China based on a hybrid regionalization approach and a novel, empirical index—Vegetation Sensitivity Index (VSI). Vegetation showed linearly increasing trends in most of the seven watersheds, while decreases in vegetation were mostly found in the source regions of the Yangtze River Basin (YZRB) and Yellow River Basin (YR
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14

Wang, Meng, Zhengfeng An, and Shouyan Wang. "The Time Lag Effect Improves Prediction of the Effects of Climate Change on Vegetation Growth in Southwest China." Remote Sensing 14, no. 21 (November 4, 2022): 5580. http://dx.doi.org/10.3390/rs14215580.

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Climate change is known to significantly affect vegetation development in the terrestrial system. Because Southwest China (SW) is affected by westerly winds and the South and East Asian monsoon, its climates are complex and changeable, and the time lag effect of the vegetation’s response to the climate has been rarely considered, making it difficult to establish a link between the SW region’s climate variables and changes in vegetation growth rate. This study revealed the characteristics of the time lag reaction and the phased changes in the response of vegetation to climate change across the
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15

Roebroek, Caspar T. J., Lieke A. Melsen, Anne J. Hoek van Dijke, Ying Fan, and Adriaan J. Teuling. "Global distribution of hydrologic controls on forest growth." Hydrology and Earth System Sciences 24, no. 9 (September 23, 2020): 4625–39. http://dx.doi.org/10.5194/hess-24-4625-2020.

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Abstract. Vegetation provides key ecosystem services and is an important component in the hydrological cycle. Traditionally, the global distribution of vegetation is explained through climatic water availability. Locally, however, groundwater can aid growth by providing an extra water source (e.g. oases) or hinder growth by presenting a barrier to root expansion (e.g. swamps). In this study we analyse the global correlation between humidity (expressing climate-driven water and energy availability), groundwater and forest growth, approximated by the fraction of absorbed photosynthetically activ
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16

Liu, Zhengyu. "Bimodality in a Monostable Climate–Ecosystem: The Role of Climate Variability and Soil Moisture Memory*." Journal of Climate 23, no. 6 (March 15, 2010): 1447–55. http://dx.doi.org/10.1175/2009jcli3183.1.

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Abstract The probabilistic modal response of vegetation to stochastic precipitation variability is studied in a conceptual climate–ecosystem model. It is found that vegetation can exhibit bimodality in a monostable climate–ecosystem under strong rainfall variability and with soil moisture memory comparable with that of the vegetation. The bimodality of vegetation is generated by a convolution of a nonlinear vegetation response and a colored stochastic noise. The nonlinear vegetation response is such that vegetation becomes insensitive to precipitation variability near either end state (green o
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17

Li, Z., and T. Zhou. "Responses of vegetation growth to climate change in china." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 28, 2015): 225–29. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-225-2015.

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Global warming-related climate changes have significantly impacted the growth of terrestrial vegetation. Quantifying the spatiotemporal characteristic of the vegetation’s response to climate is crucial for assessing the potential impacts of climate change on vegetation. In this study, we employed the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI) that was calculated for various time scales (1 to 12 months) from monthly records of mean temperature and precipitation totals using 511 meteorological stations in China to study the re
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18

Upchurch, Garland R., Bette L. Otto-Bliesner, and Christopher Scotese. "Vegetation–atmosphere interactions and their role in global warming during the latest Cretaceous." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 353, no. 1365 (January 29, 1998): 97–112. http://dx.doi.org/10.1098/rstb.1998.0194.

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Forest vegetation has the ability to warm Recent climate by its effects on albedo and atmospheric water vapour, but the role of vegetation in warming climates of the geologic past is poorly understood. This study evaluates the role of forest vegetation in maintaining warm climates of the Late Cretaceous by (1) reconstructing global palaeovegetation for the latest Cretaceous (Maastrichtian); (2) modelling latest Cretaceous climate under unvegetated conditions and different distributions of palaeovegetation; and (3) comparing model output with a global database of palaeoclimatic indicators. Simu
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19

Claussen*, M. "Late Quaternary vegetation-climate feedbacks." Climate of the Past 5, no. 2 (June 3, 2009): 203–16. http://dx.doi.org/10.5194/cp-5-203-2009.

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Abstract. Feedbacks between vegetation and other components of the climate system are discussed with respect to their influence on climate dynamics during the late Quaternary, i.e., the last glacial-interglacial cycles. When weighting current understanding based on interpretation of palaeobotanic and palaeoclimatic evidence by numerical climate system models, a number of arguments speak in favour of vegetation dynamics being an amplifier of orbital forcing. (a) The vegetation-snow albedo feedback in synergy with the sea-ice albedo feedback tends to amplify Northern Hemisphere and global mean t
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20

Pastor, John. "Vegetation Dynamics and Climate Change." Ecology 75, no. 7 (October 1994): 2145–46. http://dx.doi.org/10.2307/1941620.

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21

Claussen, M. "Late Quaternary vegetation – climate feedbacks*." Climate of the Past Discussions 5, no. 1 (February 24, 2009): 635–70. http://dx.doi.org/10.5194/cpd-5-635-2009.

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Abstract. Feedbacks between vegetation and other components of the climate system are discussed with respect to their influence on climate dynamics during the late Quaternary, i.e., the last glacial – interglacial cycles. When weighting current understanding based on interpretation of palaeobotanic and palaeoclimatic evidence by numerical climate system models, a number of arguments speak in favour of vegetation dynamics being an amplifier of orbital forcing. (a) The vegetation – snow albedo feedback in synergy with the sea ice – albedo feedback tends to amplify Northern Hemisphere and global
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22

Gray, Thomas I., and Byron D. Tapley. "Vegetation health: Nature's climate monitor." Advances in Space Research 5, no. 6 (January 1985): 371–77. http://dx.doi.org/10.1016/0273-1177(85)90343-6.

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23

Ritchie, J. C. "Climate change and vegetation response." Vegetatio 67, no. 2 (October 1986): 65–74. http://dx.doi.org/10.1007/bf00037358.

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24

Fang, Jing-yun, and Kyoji Yoda. "Climate and vegetation in China II. Distribution of main vegetation types and thermal climate." Ecological Research 4, no. 1 (April 1989): 71–83. http://dx.doi.org/10.1007/bf02346944.

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25

Yuan, Fei, Liliang Ren, Zhongbo Yu, Yonghua Zhu, Jing Xu, and Xiuqin Fang. "Potential natural vegetation dynamics driven by future long-term climate change and its hydrological impacts in the Hanjiang River basin, China." Hydrology Research 43, no. 1-2 (February 1, 2012): 73–90. http://dx.doi.org/10.2166/nh.2011.111.

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Vegetation and land-surface hydrology are intrinsically linked under long-term climate change. This paper aims to evaluate the dynamics of potential natural vegetation arising from 21st century climate change and its possible impact on the water budget of the Hanjiang River basin in China. Based on predictions of the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC-SRES) A1 scenario from the PRECIS (Providing Regional Climates for Impact Studies) regional climate model, changes in plant functional types (PFTs) and leaf area index (LAI) were simulated via th
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26

Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola, and M. Macchiato. "Estimation of vegetation cover resilience from satellite time series." Hydrology and Earth System Sciences Discussions 5, no. 1 (February 28, 2008): 511–46. http://dx.doi.org/10.5194/hessd-5-511-2008.

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Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation
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27

Simoniello, T., M. Lanfredi, M. Liberti, R. Coppola, and M. Macchiato. "Estimation of vegetation cover resilience from satellite time series." Hydrology and Earth System Sciences 12, no. 4 (July 30, 2008): 1053–64. http://dx.doi.org/10.5194/hess-12-1053-2008.

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Abstract. Resilience is a fundamental concept for understanding vegetation as a dynamic component of the climate system. It expresses the ability of ecosystems to tolerate disturbances and to recover their initial state. Recovery times are basic parameters of the vegetation's response to forcing and, therefore, are essential for describing realistic vegetation within dynamical models. Healthy vegetation tends to rapidly recover from shock and to persist in growth and expansion. On the contrary, climatic and anthropic stress can reduce resilience thus favouring persistent decrease in vegetation
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28

Xu, Haitao, Peng Hou, Zhengwei He, A. Duo, and Bing Zhang. "Spatiotemporal Variation Characteristics of Vegetative PUE in China from 2000 to 2015." Advances in Meteorology 2018 (August 28, 2018): 1–19. http://dx.doi.org/10.1155/2018/5636932.

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Vegetative precipitation-use efficiency (PUE) is a key indicator for evaluating the dynamic response of vegetation productivity to the spatiotemporal variation in precipitation. It is also an important indicator for reflecting the relationship between the water and carbon cycles in a vegetation ecosystem. This paper uses data from MODIS Net Primary Production (NPP) and China’s spatial interpolation data for precipitation from 2000 to 2015 to calculate the annual value, multiyear mean value, interannual standard deviation, and interannual linear trend of Chinese terrestrial vegetative PUE over
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29

Ruggiu, Dario, and Francesco Viola. "Linking Climate, Basin Morphology and Vegetation Characteristics to Fu’s Parameter in Data Poor Conditions." Water 11, no. 11 (November 7, 2019): 2333. http://dx.doi.org/10.3390/w11112333.

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The prediction of long term water balance components is not a trivial issue, even when empirical Budyko’s type approaches are used, because parameter estimation is often hampered by missing or poor hydrological data. In order to overcome this issue, we provided regression equations that link climate, morphological, and vegetation parameters to Fu’s parameter. Climate is here defined as a specific seasonal pattern of potential evapotranspiration and rain: five climatic scenarios have been considered to mimic different conditions worldwide. A weather generator has been used to create stochastic
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30

Zhang, Xianliang, and Xuanrui Huang. "Human disturbance caused stronger influences on global vegetation change than climate change." PeerJ 7 (September 25, 2019): e7763. http://dx.doi.org/10.7717/peerj.7763.

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Global vegetation distribution has been influenced by human disturbance and climate change. The past vegetation changes were studied in numerous studies while few studies had addressed the relative contributions of human disturbance and climate change on vegetation change. To separate the influences of human disturbance and climate change on the vegetation changes, we compared the existing vegetation which indicates the vegetation distribution under human influences with the potential vegetation which reflects the vegetation distribution without human influences. The results showed that climat
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31

Wu, Minchao, Guy Schurgers, Markku Rummukainen, Benjamin Smith, Patrick Samuelsson, Christer Jansson, Joe Siltberg, and Wilhelm May. "Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change." Earth System Dynamics 7, no. 3 (July 26, 2016): 627–47. http://dx.doi.org/10.5194/esd-7-627-2016.

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Abstract. Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive ve
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32

Maxwald, Melanie, Markus Immitzer, Hans Peter Rauch, and Federico Preti. "Analyzing Fire Severity and Post-Fire Vegetation Recovery in the Temperate Andes Using Earth Observation Data." Fire 5, no. 6 (December 8, 2022): 211. http://dx.doi.org/10.3390/fire5060211.

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In wildfire areas, earth observation data is used for the development of fire-severity maps or vegetation recovery to select post-fire measures for erosion control and revegetation. Appropriate vegetation indices for post-fire monitoring vary with vegetation type and climate zone. This study aimed to select the best vegetation indices for post-fire vegetation monitoring using remote sensing and classification methods for the temperate zone in southern Ecuador, as well as to analyze the vegetation’s development in different fire severity classes after a wildfire in September 2019. Random forest
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33

Troch, P. A., G. Carrillo, M. Sivapalan, T. Wagener, and K. Sawicz. "Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution." Hydrology and Earth System Sciences 17, no. 6 (June 18, 2013): 2209–17. http://dx.doi.org/10.5194/hess-17-2209-2013.

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Abstract. Budyko (1974) postulated that long-term catchment water balance is controlled to first order by the available water and energy. This leads to the interesting question of how do landscape characteristics (soils, geology, vegetation) and climate properties (precipitation, potential evaporation, number of wet and dry days) interact at the catchment scale to produce such a simple and predictable outcome of hydrological partitioning? Here we use a physically-based hydrologic model separately parameterized in 12 US catchments across a climate gradient to decouple the impact of climate and
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34

Becker, Thorsten, and Norbert Jürgens. "Vegetation along climate gradients in Kaokoland, North-West Namibia." Phytocoenologia 30, no. 3-4 (November 24, 2000): 543–65. http://dx.doi.org/10.1127/phyto/30/2000/543.

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35

Lézine, Anne-Marie. "Late Quaternary Vegetation and Climate of the Sahel." Quaternary Research 32, no. 3 (November 1989): 317–34. http://dx.doi.org/10.1016/0033-5894(89)90098-7.

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AbstractPollen and phytogeographic evidence provides a vegetational history of the Sahel for the period 0–18,000 yr B.P. The zonal vegetation fluctuated latitudinally and its most extreme positions occurred at 18,000 and 8500 yr B.P. The first involved a southward shift of the Sahelian wooded grassland to 10°N under the arid conditions of the last glacial maximum. The second change shows a rapid northward migration of humid vegetation: Guinean elements reach 16°N and Sahelo-Sudanian elements extend to the southern margin of the modern Sahara (21°N) when the Atlantic monsoon flux increased. In
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36

Berrittella, C., and J. van Huissteden. "Uncertainties in modelling CH<sub>4</sub> emissions from northern wetlands in glacial climates: the role of vegetation parameters." Climate of the Past 7, no. 4 (October 11, 2011): 1075–87. http://dx.doi.org/10.5194/cp-7-1075-2011.

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Abstract. Marine Isotope Stage 3 (MIS 3) interstadials are marked by a sharp increase in the atmospheric methane (CH4) concentration, as recorded in ice cores. Wetlands are assumed to be the major source of this CH4, although several other hypotheses have been advanced. Modelling of CH4 emissions is crucial to quantify CH4 sources for past climates. Vegetation effects are generally highly generalized in modelling past and present-day CH4 fluxes, but should not be neglected. Plants strongly affect the soil-atmosphere exchange of CH4 and the net primary production of the vegetation supplies orga
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37

Dekker, S. C., H. J. de Boer, V. Brovkin, K. Fraedrich, M. J. Wassen, and M. Rietkerk. "Biogeophysical feedbacks trigger shifts in the modelled climate system at multiple scales." Biogeosciences Discussions 6, no. 6 (November 25, 2009): 10983–1004. http://dx.doi.org/10.5194/bgd-6-10983-2009.

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Abstract. Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilien
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38

Dekker, S. C., H. J. de Boer, V. Brovkin, K. Fraedrich, M. J. Wassen, and M. Rietkerk. "Biogeophysical feedbacks trigger shifts in the modelled vegetation-atmosphere system at multiple scales." Biogeosciences 7, no. 4 (April 12, 2010): 1237–45. http://dx.doi.org/10.5194/bg-7-1237-2010.

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Abstract. Terrestrial vegetation influences climate by modifying the radiative-, momentum-, and hydrologic-balance. This paper contributes to the ongoing debate on the question whether positive biogeophysical feedbacks between vegetation and climate may lead to multiple equilibria in vegetation and climate and consequent abrupt regime shifts. Several modelling studies argue that vegetation-climate feedbacks at local to regional scales could be strong enough to establish multiple states in the climate system. An Earth Model of Intermediate Complexity, PlaSim, is used to investigate the resilien
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39

Jiang, Liangliang, Bing Liu, and Ye Yuan. "Quantifying Vegetation Vulnerability to Climate Variability in China." Remote Sensing 14, no. 14 (July 21, 2022): 3491. http://dx.doi.org/10.3390/rs14143491.

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Climate variability has profound effects on vegetation. Spatial distributions of vegetation vulnerability that comprehensively consider vegetation sensitivity and resilience are not well understood in China. Furthermore, the combination of cumulative climate effects and a one-month-lagged autoregressive model represents an advance in the technical approach for calculating vegetation sensitivity. In this study, the spatiotemporal characteristics of vegetation sensitivity to climate variability and vegetation resilience were investigated at seasonal scales. Further analysis explored the spatial
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40

Wu, Rihan, Guozheng Hu, Hasbagan Ganjurjav, and Qingzhu Gao. "Sensitivity of Grassland Coverage to Climate across Environmental Gradients on the Qinghai-Tibet Plateau." Remote Sensing 15, no. 12 (June 19, 2023): 3187. http://dx.doi.org/10.3390/rs15123187.

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Grassland cover is strongly influenced by climate change. The response of grassland cover to climate change becomes complex with background climate. There have been some advances in research on the sensitivity of grassland vegetation to climate change around the world, but the differences in climate sensitivity among grassland types are still unclear in alpine grassland. Therefore, we applied MODIS NDVI data and trend analysis methods to quantify the spatial and temporal variation of grassland vegetation cover on the Qinghai-Tibet Plateau. Then, we used multiple regression models to analyze th
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41

Whitlock, Cathy. "Postglacial Fire Frequency and its Relation to Long-Term Vegetational and Climatic Changes in Yellowstone Park." UW National Parks Service Research Station Annual Reports 17 (January 1, 1993): 146–52. http://dx.doi.org/10.13001/uwnpsrc.1993.3173.

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The Paleoecologic recod provides unique insights into the response of communities to environmental perturbations of different duration and intensity. Climate is a primary agent of environmental change and its long-term effect on the vegetation of the Yellowstone/Grand Teton region is revealed in a network of pollen records (Whitlock, 1993). Fire frequency is controlled by climate, and as climate changes so too does the importance of fire in shaping spatial patterns of vegetation. The prehistoric record of Yellowstone's Northern Range, for example, shows the response of vegetation to the absenc
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42

Liu, Zhengyu, M. Notaro, J. Kutzbach, and Naizhuang Liu. "Assessing Global Vegetation–Climate Feedbacks from Observations*." Journal of Climate 19, no. 5 (March 1, 2006): 787–814. http://dx.doi.org/10.1175/jcli3658.1.

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Abstract The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes
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Wyrwoll, K. H., F. H. McRobie, M. Notaro, and G. Chen. "Indigenous vegetation burning practices and their impact on the climate of the northern Australian monsoon region." Hydrology and Earth System Sciences Discussions 10, no. 8 (August 13, 2013): 10313–32. http://dx.doi.org/10.5194/hessd-10-10313-2013.

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Abstract. Here we pose the question: was there a downturn in summer monsoon precipitation over northern Australia due to Aboriginal vegetation practices over prehistoric time scales? In answering this question we consider the results from a global climate model incorporating ocean, land, ice, atmosphere and vegetation interactions, reducing the total vegetation cover over northern Australia by 20% to simulate the effects of burning. The results suggest that burning forests and woodlands in the monsoon region of Australia led to a shift in the regional climate, with a delayed monsoon onset and
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Hu, Ling, Wenjie Fan, Wenping Yuan, Huazhong Ren, and Yaokui Cui. "Spatiotemporal Variation of Vegetation Productivity and Its Feedback to Climate Change in Northeast China over the Last 30 Years." Remote Sensing 13, no. 5 (March 3, 2021): 951. http://dx.doi.org/10.3390/rs13050951.

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Gross primary productivity (GPP) represents total vegetation productivity and is crucial in regional or global carbon balance. The Northeast China (NEC), abundant in vegetation resources, has a relatively large vegetation productivity; however, under obvious climate change (especially warming), whether and how will the vegetation productivity and ecosystem function of this region changed in a long time period needs to be revealed. With the help of GPP products provided by the Global LAnd Surface Satellite (GLASS) program, this paper gives an overview of the regional feedback of vegetation prod
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Schmid, Manuel, Todd A. Ehlers, Christian Werner, Thomas Hickler, and Juan-Pablo Fuentes-Espoz. "Effect of changing vegetation and precipitation on denudation – Part 2: Predicted landscape response to transient climate and vegetation cover over millennial to million-year timescales." Earth Surface Dynamics 6, no. 4 (October 8, 2018): 859–81. http://dx.doi.org/10.5194/esurf-6-859-2018.

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Abstract. We present a numerical modeling investigation into the interactions between transient climate and vegetation cover with hillslope and detachment limited fluvial processes. Model simulations were designed to investigate topographic patterns and behavior resulting from changing climate and the associated changes in surface vegetation cover. The Landlab surface process model was modified to evaluate the effects of temporal variations in vegetation cover on hillslope diffusion and fluvial erosion. A suite of simulations were conducted to represent present-day climatic conditions and sate
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Wijekoon, Sithmini, Izni Zahidi, Badronnisa Yusuf, and Helmi Zulhaidi Mohd Shafri. "Spatiotemporal correlation and multivariate analysis between vegetation health, terrestrial water storage and precipitation." IOP Conference Series: Earth and Environmental Science 1136, no. 1 (January 1, 2023): 012016. http://dx.doi.org/10.1088/1755-1315/1136/1/012016.

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Abstract Vegetation health is an essential indicator in the global hydrologic cycle as it is interrelated with the hydrological components. In tropical areas where vegetation dominates, analysing their correlation at a regional scale helps forecast the hydrologic cycle and understand vegetation’s response to climate change. However, the interactions between vegetation, terrestrial water storage and climate factors such as precipitation remain poorly understood in this region. Therefore, using Landsat and Gravity Recovery and Climate Experiment (GRACE) remote sensing and observed precipitation
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Yadav, Brijesh, Lal Chand Malav, Shruti V. Singh, Sushil Kumar Kharia, Md Yeasin, Ram Narayan Singh, Mahaveer Nogiya, et al. "Spatiotemporal Responses of Vegetation to Hydroclimatic Factors over Arid and Semi-arid Climate." Sustainability 15, no. 21 (October 24, 2023): 15191. http://dx.doi.org/10.3390/su152115191.

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Understanding the dynamics of vegetative greenness and how it interacts with various hydroclimatic factors is crucial for comprehending the implications of global climate change. The present study utilized the MODIS-derived normalized difference vegetation index (NDVI) to understand the vegetation patterns over 21 years (2001–2021) in Rajasthan, India. The rainfall, land surface temperature (LST), and evapotranspiration (ET) were also analyzed. The changes, at a 30 m pixel resolution, were evaluated using Mann–Kendall’s trend test. The results reveal that the NDVI, ET, and rainfall had increas
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Masson, Valéry, Aude Lemonsu, Julia Hidalgo, and James Voogt. "Urban Climates and Climate Change." Annual Review of Environment and Resources 45, no. 1 (October 17, 2020): 411–44. http://dx.doi.org/10.1146/annurev-environ-012320-083623.

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Cities are particularly vulnerable to extreme weather episodes, which are expected to increase with climate change. Cities also influence their own local climate, for example, through the relative warming known as the urban heat island (UHI) effect. This review discusses urban climate features (even in complex terrain) and processes. We then present state-of-the-art methodologies on the generalization of a common urban neighborhood classification for UHI studies, as well as recent developments in observation systems and crowdsourcing approaches. We discuss new modeling paradigms pertinent to c
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Loehle, C. "Predicting Pleistocene climate from vegetation in North America." Climate of the Past 3, no. 1 (February 12, 2007): 109–18. http://dx.doi.org/10.5194/cp-3-109-2007.

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Abstract. Climates at the Last Glacial Maximum have been inferred from fossil pollen assemblages, but these inferred climates are colder for eastern North America than those produced by climate simulations. It has been suggested that low CO2 levels could account for this discrepancy. In this study biogeographic evidence is used to test the CO2 effect model. The recolonization of glaciated zones in eastern North America following the last ice age produced distinct biogeographic patterns. It has been assumed that a wide zone south of the ice was tundra or boreal parkland (Boreal-Parkland Zone or
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Zhang, Yong, Chengbang An, Lai Jiang, Liyuan Zheng, Bo Tan, Chao Lu, Wensheng Zhang, and Yanzhen Zhang. "Increased Vegetation Productivity of Altitudinal Vegetation Belts in the Chinese Tianshan Mountains despite Warming and Drying since the Early 21st Century." Forests 14, no. 11 (November 3, 2023): 2189. http://dx.doi.org/10.3390/f14112189.

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Gaining a deep understanding of how climate change affects the carbon cycle in dryland vegetation is of utmost importance, as it plays a pivotal role in shaping the overall carbon cycle in global ecosystems. It is currently not clear how plant communities at varying elevations in arid mountainous regions will respond to climate change in terms of their productivity. The aim of this study was to investigate the effect of climate change on vegetation productivity in different altitudinal vegetation belts of the Tianshan Mountains between 2000 and 2021, utilizing satellite-derived vegetation prod
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