A model quantifying global vegetation resistance and resilience to short-term climate anomalies and their relationship with vegetation cover

2015 ◽  
Vol 24 (5) ◽  
pp. 539-548 ◽  
Author(s):  
Wanda De Keersmaecker ◽  
Stef Lhermitte ◽  
Laurent Tits ◽  
Olivier Honnay ◽  
Ben Somers ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Short Term ◽  
Climate Anomalies ◽  
Global Vegetation

scholarly journals Abiotic disturbances affect forest short-term vegetation cover and phenology in Southwest China

2021 ◽  
Vol 124 ◽  
pp. 107393
Author(s):  
Ying Deng ◽  
Ming Wang ◽  
Rasoul Yousefpour ◽  
Marc Hanewinkel
Keyword(s):  
Vegetation Cover ◽  
Southwest China ◽  
Short Term

Effects of fire, food availability and vegetation on the distribution of the rodent Bolomys lasiurus in an Amazonian savanna

2004 ◽  
Vol 20 (2) ◽  
pp. 183-187 ◽  
Author(s):  
Viviane Maria Guedes Layme ◽  
Albertina Pimentel Lima ◽  
William Ernest Magnusson
Keyword(s):  
Spatial Variation ◽  
Food Availability ◽  
Significant Relationship ◽  
Habitat Suitability ◽  
Vegetation Cover ◽  
Vegetation Structure ◽  
Short Term ◽  
Tall Grass ◽  
Insect Abundance ◽  
Habitat Suitability Models

We investigated the relative influences of vegetation cover, invertebrate biomass as an index of food availability and the short-term effects of fires on the spatial variation in densities of the rodent Bolomys lasiurus in an Amazonian savanna. Densities were evaluated in 31 plots of 4 ha distributed over an area of approximately 10×10 km. The cover of the tall grass (Trachypogon plumosus), short grass (Paspalum carinatum), shrubs and the extent of fire did not explain the variance in densities of Bolomys lasiurus. Food availability alone explained about 53% of the variance in B. lasiurus densities, and there was no significant relationship between insect abundance and vegetation structure. Fires had little short-term impact on the density of Bolomys lasiurus in the area we studied. As the species appears to respond principally to food availability, habitat suitability models based on easily recorded vegetation-structure variables, or the frequency of disturbance by fire, may not be effective in predicting the distribution of the species within savannas.

scholarly journals Improving the representation of high-latitude vegetation distribution in dynamic global vegetation models

2021 ◽  
Vol 18 (1) ◽  
pp. 95-112
Author(s):  
Peter Horvath ◽  
Hui Tang ◽  
Rune Halvorsen ◽  
Frode Stordal ◽  
Lena Merete Tallaksen ◽  
...  
Keyword(s):  
High Latitude ◽  
Vegetation Cover ◽  
Land Surface ◽  
Snow Water Equivalent ◽  
Radiative Properties ◽  
Community Land Model ◽  
Precipitation Seasonality ◽  
Dynamic Global Vegetation Models ◽  
Vegetation Models ◽  
Global Vegetation

Abstract. Vegetation is an important component in global ecosystems, affecting the physical, hydrological and biogeochemical properties of the land surface. Accordingly, the way vegetation is parameterized strongly influences predictions of future climate by Earth system models. To capture future spatial and temporal changes in vegetation cover and its feedbacks to the climate system, dynamic global vegetation models (DGVMs) are included as important components of land surface models. Variation in the predicted vegetation cover from DGVMs therefore has large impacts on modelled radiative and non-radiative properties, especially over high-latitude regions. DGVMs are mostly evaluated by remotely sensed products and less often by other vegetation products or by in situ field observations. In this study, we evaluate the performance of three methods for spatial representation of present-day vegetation cover with respect to prediction of plant functional type (PFT) profiles – one based upon distribution models (DMs), one that uses a remote sensing (RS) dataset and a DGVM (CLM4.5BGCDV; Community Land Model 4.5 Bio-Geo-Chemical cycles and Dynamical Vegetation). While DGVMs predict PFT profiles based on physiological and ecological processes, a DM relies on statistical correlations between a set of predictors and the modelled target, and the RS dataset is based on classification of spectral reflectance patterns of satellite images. PFT profiles obtained from an independently collected field-based vegetation dataset from Norway were used for the evaluation. We found that RS-based PFT profiles matched the reference dataset best, closely followed by DM, whereas predictions from DGVMs often deviated strongly from the reference. DGVM predictions overestimated the area covered by boreal needleleaf evergreen trees and bare ground at the expense of boreal broadleaf deciduous trees and shrubs. Based on environmental predictors identified by DM as important, three new environmental variables (e.g. minimum temperature in May, snow water equivalent in October and precipitation seasonality) were selected as the threshold for the establishment of these high-latitude PFTs. We performed a series of sensitivity experiments to investigate if these thresholds improve the performance of the DGVM method. Based on our results, we suggest implementation of one of these novel PFT-specific thresholds (i.e. precipitation seasonality) in the DGVM method. The results highlight the potential of using PFT-specific thresholds obtained by DM in development of DGVMs in broader regions. Also, we emphasize the potential of establishing DMs as a reliable method for providing PFT distributions for evaluation of DGVMs alongside RS.

Vegetation Cover, Tidal Amplitude and Land Area Predict Short-Term Marsh Vulnerability in Coastal Louisiana

Ecosystems ◽  
2018 ◽  
Vol 21 (7) ◽  
pp. 1335-1347 ◽  
Author(s):  
Donald R. Schoolmaster ◽  
Camille L. Stagg ◽  
Leigh Anne Sharp ◽  
Tommy E. McGinnis ◽  
Bernard Wood ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Tidal Amplitude ◽  
Land Area ◽  
Short Term ◽  
Coastal Louisiana

Short and long-term effects of fire and vegetation cover on four lizard species in Amazonian savannas

2020 ◽  
Author(s):  
Erika dos Santos Souza ◽  
Albertina P. Lima ◽  
William E. Magnusson ◽  
RICARDO ALEXANDRE KAWASHITA-RIBEIRO ◽  
Rodrigo Ferreira Fadini ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Long Term Effects ◽  
Short Term ◽  
Lizard Species ◽  
Random Factor ◽  
Positive Effects ◽  
Temporal Sampling ◽  
Short And Long Term ◽  
Main Effects

Ecological succession in tropical savannas is limited by seasonal fire, which affects habitat quality. Although fire may cause negligible or positive effects on animals occupying savannas, most short-term studies (months to a few years) are based on a single temporal sampling snapshot, and long-term studies (decades) are rare. We sampled four lizard species in Amazonian savannas to test the effects of fire and vegetation cover on lizard densities at two temporal scales. In the short-term, we use three sampling snapshots to test the effects of fire and vegetation cover on estimated lizard densities over the subsequent 1–5 years. In the long-term, we test the effects of fire and changes in vegetation cover over 21 years on current lizard density differences. In the short-term, species responses were usually consistent with foraging and thermoregulation modes. However, the results were not consistent among species and years, although the variances in species density explained by year as a random factor were generally low. In the long-term, the main effects of fire and vegetation cover show that lizard densities may change spatially, but not necessarily temporarily. Wildfire is a natural resource of savannas and apparently have little impact on resident lizards of that ecosystem.

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