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108 results for “vegetation pattern”
FIGURE 1 in Patterns of diet and body mass of large ungulates from the Pleistocene of Western Europe, and their relation to vegetation
FIGURE 1. The localities included in this study from England and Ireland (1.1) and from Germany (1.2). The maps (1.1) and (1.2) are not to the same scale.
FIGURE 4 in Patterns of diet and body mass of large ungulates from the Pleistocene of Western Europe, and their relation to vegetation
FIGURE 4. Linear regressions of mean mesowear values of Bovidae, Equus ferus and Rhinocerotidae from localities with pollen records, and minimum, maximum and mean NAP % in the pollen records of the localities. Numbers of specimens per locality are given in brackets after the locality names. Bison from Mauer is B. schoetensacki; from other localities, B. priscus.
Data from: Cryogenic land surface processes shape vegetation biomass patterns in northern European tundra
<p>Tundra ecosystems have experienced changes in vegetation composition, distribution, and productivity over the past century due to climate warming. However, the increase in above-ground biomass (AGB) may be constrained by cryogenic land surface processes (LSP) that cause topsoil disturbance and variable microsite conditions. These effects have remained unaccounted for in tundra biomass models, although they can impact multiple opposing feedbacks between the biosphere and atmosphere, ecosystem functioning and biodiversity. Here, by using field-quantified data from northern Europe, remote sensing, and machine learning, we show that LSP substantially constrain AGB in tundra. The three surveyed LSP (cryoturbation, solifluction and nivation) collectively reduced AGB by an average of 123.0 g m<sup>-2 </sup>(-30.0%). This effect was significant over landscape positions and was especially pronounced in snowbed environments, where the mean reduction in AGB was 57.3%. Our results imply that LSP are pivotal in shaping future patterns of tundra biomass, as long as cryogenic ground activity is retained by climate warming.</p> <p>These are the key data and codes related from Aalto et al., (2021).</p> <p> </p>
Data and model code for: Habitat use patterns suggest that climate-driven vegetation changes will negatively impact mammal communities in the Amazon (ACV)
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Soil Moisture and vegetation cover patterns after logging and burning an old-growth Douglas-fir forest in the Andrews Experimental Forest, 1960-1983
This soil moisture study was initiated in 1960 to investigate the effects of patch clearcut logging and slash burning (1962-63) in an old-growth Douglas-fir forest in the Oregon Cascade Range. Since soil moisture and vegetation sampling continued regularly until 1980, this is a unique data set that represents nearly two decades of post-treatment information. Plant cover exerts a profound influence on soil moisture levels through its effects on interception, infiltration, evaporation, and transpiration. In the Douglas-fir forests of the Pacific Northwest, clearcut logging and slash burning are common practices that can dramatically alter plant cover and soil moisture. Logging can increase soil moisture by temporarily reducing cover and associated water use, and burning may further augment soil moisture levels by suppressing the survival and regrowth of vegetation. Indeed, part of the rationale for slash burning in the region is to control shrubs and other vegetation that would otherwise compete with conifer seedlings for available moisture, light, and nutrients. Within a few years after burning, however, invading vegetation may deplete soil moisture to levels comparable to forested areas. Such observations point to the value of long-term information to better understand dynamic soil moisture and plant cover responses to forest practices.
Spatial patterns of understory vegetation and soil in an Alaskan upland boreal forest fire chronosequence. Three sites located in Delta Junction Alaska. Soil sampled during summer 2007
In this study we used geostatistics to characterize the spatial heterogeneity of soil carbon and nitrogen pools, microbial respiration, microbial biomass, nitrogen mineralization, soil moisture, soil pH, depth of organic horizon and forest floor covers and understory vegetation abundances in three sites (1999, 1987 and 1920 wildfires) of a boreal forest chronosequence of Interior Alaska (near Delta Junction). Soil sampling and vegetation measurements occured during summer 2007.
Bulk density, Soil:Effect of Burning Patterns on Vegetation in the Fish Lake Burn Compartments
This study examines the effects of long-term prescribed burning treatments on vegetation structure and composition, productivity, and nutrient cycling in upland oak savanna and woodland vegetation. The basis for the study is an ongoing, experimental prescribed burning program begun in 1964 at Cedar Creek, and a similar program operating since 1962 on the adjacent Helen Allison Savanna property (owned by The Nature Conservancy). These prescribed burning programs are designed to subject upland oak communities (and some old fields) to different burn frequencies and patterns of burning, with the ultimate objectives of 1) restoring and maintaining the historically important savanna and open woodland vegetation, and 2) providing information about the effects of different burning patterns on vegetation structure and composition. This study addresses the latter of these two purposes and expands on it by also investigating possible influences of fire on resource availability (nutrients, water, and light) and net primary productivity. This study represents a continuation and expansion of experiments 015 and 094.
Soil pH: Effect of Burning Patterns on Vegetation in the Fish Lake Burn Compartments
This study examines the effects of long-term prescribed burning treatments on vegetation structure and composition, productivity, and nutrient cycling in upland oak savanna and woodland vegetation. The basis for the study is an ongoing, experimental prescribed burning program begun in 1964 at Cedar Creek, and a similar program operating since 1962 on the adjacent Helen Allison Savanna property (owned by The Nature Conservancy). These prescribed burning programs are designed to subject upland oak communities (and some old fields) to different burn frequencies and patterns of burning, with the ultimate objectives of 1) restoring and maintaining the historically important savanna and open woodland vegetation, and 2) providing information about the effects of different burning patterns on vegetation structure and composition. This study addresses the latter of these two purposes and expands on it by also investigating possible influences of fire on resource availability (nutrients, water, and light) and net primary productivity. This study represents a continuation and expansion of experiments 015 and 094.
Topographic heterogeneity mediates patterns of vegetation response to climate change across a mountain landscape, Niwot Ridge, Colorado, 1972-2008
The distributions of biomes worldwide are predicted to shift as vegetation tracks climate change. Ecologists often use coarse-scale climate models to predict these shifts along broad elevational and latitudinal gradients, but these assessments could fail to capture important dynamics by ignoring fine-scale heterogeneity. We ask how the elevational ranges of vegetation types have changed in a mountainous landscape, and investigate the influence of fine-scale topographic, snowpack, and soil properties on vegetation change. We manually classified vegetation from high-resolution repeat aerial photographs from 1972 and 2008 at Niwot Ridge, Colorado, USA, and generally found that trees and shrubs colonized tundra, while tundra colonized barren soils. Only shrubs expanded their elevational range. Several fine-scale topographic, soil and snow characteristics, including elevation, slope, solar radiation, soil bulk density, and interannual snowpack variability, modulated where plant establishment occurred. Each vegetation type had a unique suite of variables best predicting its establishment in new areas. We suggest that fine-scale heterogeneity may strongly control how plants in mountainous regions respond to climate change, and different vegetation types may be sensitive to different aspects of this heterogeneity. An improved understanding of the factors controlling vegetation change gives us a broader understanding of ecosystem response to climate change, nitrogen deposition, and release from grazing.
Data from: Global vegetation patterns of the past 140,000 years
<p>Aim Insight into global biome responses to climatic and other environmental changes is essential to address key questions about past and future impacts of such changes. By simulating global biome patterns 140 ka to present we aimed to address important questions about biome changes during this interval.<br> <br> Location Global.<br> <br> Taxon Plantae.<br> <br> Methods Using the LPJ-GUESS dynamic global vegetation model, we made 89 simulations driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 88 palaeoclimate experiments run using HadCM3. Experiments were run for 81 time slices between 1 ka and 140 ka, seven 'hosing' experiments also being run, using a 1 Sv freshwater flux to the North Atlantic, for time slices corresponding to Heinrich Events H0 – H7. Using a rule-based approach, based on carbon mass and leaf area index of the LPJ-GUESS plant functional types, the biome was inferred for each grid cell. Biomes were mapped, and the extent and total vegetation biomass of each biome, and total global vegetation biomass, estimated.<br> <br> Results Substantial changes in biome extents and locations were found on all vegetated continents. Although the largest-magnitude changes were in Eurasia, important changes were seen in tropical latitudes and the Southern Hemisphere. Total global extent of most biomes varied on multi-millennial (orbital) time scales, although some (e.g. Tropical Raingreen Forest) responded principally to the ca. 100 kyr glacial–interglacial cycle and others (e.g. Temperate Broad-leaved Evergreen Forest) mainly to the ca. 20 kyr precession cycle. Many also responded to millennial contrasts between stadial ('hosing') and interstadial climates, with some (e.g. Tropical Evergreen Forest) showing stronger responses than to the multi-millennial changes.<br> <br> Main conclusions No two time slices had identical biome patterns. Even equivalent Holocene and last interglacial time slices, and the last and penultimate glacial maxima, showed important differences. Only a small proportion of global land area experienced no biome change since 140 ka; many places experienced multiple biome changes. These modelling experiments provided little evidence for long-term biome stability.</p>
Data from: Emergence patterns of novelty in European vegetation assemblages over the past 15,000 years
Plant communities are not stable over time and biological novelty is predicted to emerge due to climate change, the introduction of exotic species and land-use change. However, the rate at which this novelty may arise over longer time periods has so far received little attention. We reconstruct the emergence of novelty in Europe for a set of baseline conditions over the past 15 000 years to assess past rates of emergence and investigate underlying causes. The emergence of novelty is baseline specific and, during the early-Holocene, was mitigated by the rapid spread of plant taxa. Although novelty generally increases as a function of time, climate and human-induced landscape changes contributed to a non-linear post-glacial trajectory of novelty with jumps corresponding to periods of rapid changes. Emergence of novelty accelerated during the past 1000 years. Historical cultural landscapes experienced a faster novelty development due to the contribution from anthropogenic land-cover changes.
Living landscapes: Muddy and vegetated floodplain effects on fluvial pattern in an incised river
<p>The matlab data consists of 14 model runs (lab numbers in filenames), each for two timesteps in separate files, namely one for low river flow (ecological timestep 12, which is in month 6) and one for high river flow (ecological timestep 24, which is in month 12). The hydromorphological model is Delf3D, which is coupled to a riparian vegetation model 24 times per year for 150 years (some for 300 years). Each matlab file contains all variables stored by Delft3D and by the vegetation model. The most relevant variables are three-dimensional matrices containing the yearly maps. The various model runs are permutations on only sand, including mud (at various concentrations and erosion thresholds) and/or riparian vegetation.</p> <table> <caption>Table: Model runs with lab number, number in the publication, and keyworks describing the model</caption> <thead> <tr> <th scope="col">lab run number</th> <th scope="col">run number in Kleinhans et al. 2018</th> <th scope="col">properties</th> </tr> </thead> <tbody> <tr> <td>153</td> <td>4</td> <td>only sand</td> </tr> <tr> <td>149</td> <td>3</td> <td>mud added default concentration default erosion threshold</td> </tr> <tr> <td>131</td> <td>2</td> <td>vegetation added</td> </tr> <tr> <td>132</td> <td>1</td> <td>mud and vegetation</td> </tr> <tr> <td>139</td> <td>5</td> <td>5 mg/L mud</td> </tr> <tr> <td>140</td> <td>6</td> <td>50 mg/L</td> </tr> <tr> <td>141</td> <td>7</td> <td>100 mg/L</td> </tr> <tr> <td>162</td> <td>8</td> <td>500 mg/L</td> </tr> <tr> <td>144</td> <td>9</td> <td>0.1 N/m2 critical shear stress</td> </tr> <tr> <td>145</td> <td>10</td> <td>0.5 N/m2</td> </tr> <tr> <td>161</td> <td>12</td> <td>500 mg/L 0.5 N/m2 vegetation</td> </tr> <tr> <td>160</td> <td>14</td> <td>500 mg/L 0.5 N/m2</td> </tr> <tr> <td>158</td> <td>13</td> <td>800 mg/L 0.5 N/m2 vegetation</td> </tr> <tr> <td>159</td> <td>11</td> <td>100 mg/L 0.5 N/m2 vegetation</td> </tr> </tbody> </table> <p>The open access paper describing the data and its method of production is:<br> Living landscapes: Muddy and vegetated floodplain effects on fluvial pattern in an incised river</p> <p>Maarten G. Kleinhans, Bente de Vries, Lisanne Braat, Mijke van Oorschot<br> Earth Surf. Process. Landforms 43(14), 2018<br> <a href="https://doi.org/10.1002/esp.4437">https://doi.org/10.1002/esp.4437</a></p> <p>The modelling was conducted by Bente de Vries under supervision of Maarten Kleinhans as part of her MSc thesis research, which was embedded in the ERC Consolidator project of Kleinhans.</p>
Figure 1 in Circadian activity patterns and temporal overlap among cracids (Aves: Cracidae) within a vegetation mosaic in the Pantanal of Rio Negro, Brazil
Figure 1. Study area and location of the 90 camera trap stations in the Pantanal of Rio Negro, Aquidauana, Mato Grosso do Sul, Brazil.
Figure 2 in Circadian activity patterns and temporal overlap among cracids (Aves: Cracidae) within a vegetation mosaic in the Pantanal of Rio Negro, Brazil
Figure 2. Circadian activity patterns of three cracid species in the Pantanal of Rio Negro, Aquidauana, Mato Grosso do Sul. The red line represents the mean circular vector (mμ) with CI95% of the distributions.
Ecogeographical patterns in owl plumage colouration: climate and vegetation cover predict global colour variation
<p>Aim: Ecogeographical rules link animal colours, especially those produced by melanin pigments, with variation in environmental conditions over wide geographical scales. In particular, Gloger's rule, coined in two versions for endothermic animals, suggests that tegument darkness would increase at high temperature, as well as in highly humid environments. On the other hand, the thermal melanism hypothesis, predicts that darker colourations should be more frequent in colder areas given their thermoregulation benefits.</p> <p>Location: Global</p> <p>Time period: Contemporary</p> <p>Major taxa studied: Strigiformes</p> <p>Methods: Here, we provide a global comparative test of these contrasting expectations in all extant owls (n = 198 species), a group of nocturnal birds displaying huge variability in the degree of melanin-based plumage colouration and environmental specialization. Combining analyses at both species and assemblage level, we assessed the climatic and environmental variables explaining variation in plumage lightness and redness across broad geographical gradients.</p> <p>Results: Darker and redder owl phenotypes are more likely found near the equator. Species and assemblage level analyses reveal that owls have more frequently darker and redder plumages in warmer regions. In addition, owl species living in more vegetated areas are darker, and owl assemblages show darker colours in wetter areas.</p> <p>Main conclusions: Global patterns of colour variation in owls do not fit expectations from the thermal melanism hypothesis but supports Gloger´s rule. Our findings also stresses that several alternative selective forces may explain climatic effects on colouration over large geographical scales. Experimental work is urged to uncover the possible mechanisms behind the detected associations between owl colour and environmental variables.</p>
Data for: Biogeographic pattern of living vegetation carbon turnover time in mature forests across continents
<p class="MsoNormal"><strong><span>Aim: </span></strong><span>Theoretically, woody biomass turnover time (τ</span><span>) </span><span>quantified using </span><span>outflux (i.e., tree mortality)</span><span> predicts biomass dynamics better than using influx (i.e., productivity).</span> <span>This study aims at using forest inventory data to empirically test the outflux approach and generate a spatially explicit understanding of woody </span><span>τ</span><span> </span><span>in mature forests. We further compared woody τ</span><span> </span><span>estimates with dynamic global vegetation models (DGVMs) and with a data assimilation product of C stocks and fluxes - CARDAMOM.</span></p> <p class="MsoNormal"><strong><span>Location:</span></strong> <span>Continents</span></p> <p class="MsoNormal"><strong><span>Time period:</span></strong> <span>Historic from </span><span>1951 to 2018</span></p> <p class="MsoNormal"><strong><span>Major taxa studied:</span></strong> <span>Trees and Forests</span></p> <p class="MsoNormal"><strong><span>Methods: </span></strong><span>We compared the approaches of using outflux vs. influx for estimating woody <span>τ</span></span><span> and predicting biomass accumulation rates. We investigated abiotic and biotic drivers of spatial woody <span>τ</span></span><span> and generated a spatially explicit map of woody <span>τ</span></span><span> at a 0.25-degree resolution across continents using machine learning. We further examined whether six DGVMs and CARDAMOM generally captured the observational pattern of woody <span>τ</span></span><span>. </span></p> <p class="MsoNormal"><strong><span>Results: </span></strong><span>Woody <span>τ</span></span><span> quantified by the </span><span>outflux approach </span><span>better (with R<sup>2</sup> 0.4-0.5) predicted the biomass accumulation rates than the influx approach (with R<sup>2</sup> 0.1-0.4) across continents. We found large spatial variations of woody <span>τ</span></span><span> for mature forests, with highest values </span><span>in temperate forests (</span><span>98.8 ± 2.6 y</span><span>) followed by boreal forests (73</span><span>.9 ± </span><span>3</span><span>.</span><span>6</span><span> y</span><span>) and tropical forests. The map of woody <span>τ</span></span><span> extrapolated from plot data showed higher values in wetter eastern and pacific coast USA, Africa and eastern Amazon. Climate (temperature and aridity index) and vegetation structure (tree density and forest age) were the dominant drivers of woody <span>τ</span></span><span> across continents. The highest woody <span>τ</span></span><span> in temperate forests were not captured by either DGVMs or CARDAMOM. </span></p> <p class="MsoNormal"><strong><span>Main conclusions:</span></strong><span> Our study </span><span>empirically demonstrated the preference of using outflux over influx to estimate woody <span>τ</span></span><span> for predicting biomass accumulation rates. The spatially explicit map of woody </span><span>τ</span><span> and the underlying drivers provide </span><span>valuable information to improve the representation of </span><span>forest demography and </span><span>carbon turnover processes in DGVMs.</span></p>
Data from: Global vegetation patterns of the past 140,000 years
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Spatial patterns and ecological drivers of soil nematode β-diversity in natural grasslands vary among vegetation types and trophic position
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Data from: Hydrodynamics and aquatic vegetation drive spatial patterns of environmental DNA in ponds
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Emergence patterns of novelty in European vegetation assemblages over the past 15 000 years
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Allen Brain Atlas
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