scholarly journals Root pathogen diversity and composition varies with climate in undisturbed grasslands, but less so in anthropogenically disturbed grasslands

2020 ◽  
Vol 15 (1) ◽  
pp. 304-317 ◽  
Author(s):  
Camille S. Delavaux ◽  
Josh L. Schemanski ◽  
Geoffrey L. House ◽  
Alice G. Tipton ◽  
Benjamin Sikes ◽  
...  
Keyword(s):  
Climate Change ◽  
Plant Community ◽  
Plant Pathogen ◽  
Fungal Pathogens ◽  
Community Response ◽  
Community Diversity ◽  
Plant Responses ◽  
Native Plant ◽  
The Impact ◽  
Precipitation And Temperature

AbstractSoil-borne pathogens structure plant communities, shaping their diversity, and through these effects may mediate plant responses to climate change and disturbance. Little is known, however, about the environmental determinants of plant pathogen communities. Therefore, we explored the impact of climate gradients and anthropogenic disturbance on root-associated pathogens in grasslands. We examined the community structure of two pathogenic groups—fungal pathogens and oomycetes—in undisturbed and anthropogenically disturbed grasslands across a natural precipitation and temperature gradient in the Midwestern USA. In undisturbed grasslands, precipitation and temperature gradients were important predictors of pathogen community richness and composition. Oomycete richness increased with precipitation, while fungal pathogen richness depended on an interaction of precipitation and temperature, with precipitation increasing richness most with higher temperatures. Disturbance altered plant pathogen composition and precipitation and temperature had a reduced effect on pathogen richness and composition in disturbed grasslands. Because pathogens can mediate plant community diversity and structure, the sensitivity of pathogens to disturbance and climate suggests that degradation of the pathogen community may mediate loss, or limit restoration of, native plant diversity in disturbed grasslands, and may modify plant community response to climate change.

scholarly journals From the Ground Up: Prairies on Reclaimed Mine Land—Impacts on Soil and Vegetation

Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 455
Author(s):  
Rebecca M. Swab ◽  
Nicola Lorenz ◽  
Nathan R. Lee ◽  
Steven W. Culman ◽  
Richard P. Dick
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Properties ◽  
Plant Community ◽  
Prairie Restoration ◽  
Native Plant ◽  
Soil Microbial ◽  
Prairie Restorations ◽  
Mine Lands ◽  
The Impact

After strip mining, soils typically suffer from compaction, low nutrient availability, loss of soil organic carbon, and a compromised soil microbial community. Prairie restorations can improve ecosystem services on former agricultural lands, but prairie restorations on mine lands are relatively under-studied. This study investigated the impact of prairie restoration on mine lands, focusing on the plant community and soil properties. In southeast Ohio, 305 ha within a ~2000 ha area of former mine land was converted to native prairie through herbicide and planting between 1999–2016. Soil and vegetation sampling occurred from 2016–2018. Plant community composition shifted with prairie age, with highest native cover in the oldest prairie areas. Prairie plants were more abundant in older prairies. The oldest prairies had significantly more soil fungal biomass and higher soil microbial biomass. However, many soil properties (e.g., soil nutrients, β-glucosoidase activity, and soil organic carbon), as well as plant species diversity and richness trended higher in prairies, but were not significantly different from baseline cool-season grasslands. Overall, restoration with prairie plant communities slowly shifted soil properties, but mining disturbance was still the most significant driver in controlling soil properties. Prairie restoration on reclaimed mine land was effective in establishing a native plant community, with the associated ecosystem benefits.

scholarly journals Uncertainty in runoff based on Global Climate Model precipitation and temperature data – Part 2: Estimation and uncertainty of annual runoff and reservoir yield

2014 ◽  
Vol 11 (5) ◽  
pp. 4579-4638 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) datasets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to approximate within-GCM uncertainty of monthly precipitation and temperature projections and assess its impact on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. To-date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2014) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), temperature (MAT) and runoff (MAR), the standard deviation of annual precipitation (SDP) and runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 world-wide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainty from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were: MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma procedure was applied to each annual runoff time-series for hypothetical reservoir capacities of 1× MAR and 3× MAR and the average uncertainty in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were: 25.1% (1× MAR) and 11.9% (3× MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1× MAR or 3× MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

Arctic Plant Responses to Climate Warming: It’s Not all about Nitrogen

2018 ◽  
Author(s):  
Sanna Masud
Keyword(s):  
Climate Change ◽  
The Arctic ◽  
Plant Responses ◽  
Experimental Warming ◽  
Nutrient Pools ◽  
Research Attention ◽  
Low Arctic ◽  
Total Plant ◽  
The Impact ◽  
Deciduous Shrub

Climate change is increasing air and soil temperatures in the Arctic, likely enhancing microbial activity. Consequently, increased decomposition rates of soil organic matter and increasing nutrient supply to tundra vegetation can be expected. The impacts of experimental warming and fertilization on growth have been investigated by studying the availability of macronutrients such as N, P and C. However, other   macronutrients such as S, Ca, Mg, K, and micronutrients such as Fe, Mn, Cu, and Zn have received little research attention to determine their function, biogeochemical cycling, and effect on vegetation growth in response to warming. This study investigated the impact of experimental warming responses on availability and accumulation of the latter nutrients in the principal plant species located in mesic birch hummock tundra near Daring Lake, Northwest Territories in the Canadian Low Arctic Tundra. Plants were sampled in 2011 from the replicated summer greenhouse treatment that was established in 2004. In response to warming, the principal evergreen shrub (Rhododendron) had the most enhanced growth, followed by the deciduous shrub (Birch). Since the total plant pools of these nutrients were also enhanced in the evergreen, my results strongly suggest that availability of these nutrients was not limiting growth. By contrast, the birch total plant nutrient pools were not enhanced and significant decreases in Mg, S, and K leaf concentrations were observed, suggesting that these elements may be limiting birch growth. Together, our results suggest that plant growth response to climate change in the low Arctic may depend on previously overlooked nutrient elements, and that deciduous shrub growth may be constrained relative to the evergreen response as the arctic climate warms.

scholarly journals Human Skin Bacterial Community Response to Probiotic (Lactobacillus reuteri DSM 17938) Introduction

2020 ◽  
Vol 8 (8) ◽  
pp. 1223
Author(s):  
Marie Frerejacques ◽  
Camille Rousselle ◽  
Loüen Gauthier ◽  
Salomé Cottet-Emard ◽  
Léa Derobert ◽  
...  
Keyword(s):  
Bacterial Community ◽  
Lactobacillus Reuteri ◽  
Community Response ◽  
Community Diversity ◽  
Colonization Rate ◽  
Bacterial Strains ◽  
Skin Microbiota ◽  
Potential Health ◽  
The Impact

The introduction of a strain or consortium has often been considered as a potential solution to restore microbial ecosystems. Extensive research on the skin microbiota has led to the development of probiotic products (with live bacterial strains) that are likely to treat dysbiosis. However, the effects of such introductions on the indigenous microbiota have not yet been investigated. Here, through a daily application of Lactobacillus reuteri DSM 17938 on volunteers’ forearm skin, we studied in vivo the impact of a probiotic on the indigenous skin bacterial community diversity using Terminal-Restriction Fragment Length Polymorphism (T-RFLP) for 3 weeks. The results demonstrate that Lactobacillus reuteri DSM 17938 inoculum had a transient effect on the indigenous community, as the resilience phenomenon was observed within the skin microbiota. Moreover, Lactobacillus reuteri DSM 17938 monitoring showed that, despite a high level of detection after 2 weeks of application, thereafter the colonization rate drops drastically. The probiotic colonization rate was correlated significantly to the effect on the indigenous microbial community structure. These preliminary results suggest that the success of probiotic use and the potential health benefits resides in the interactions with the human microbiota.

scholarly journals Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

2015 ◽  
Vol 19 (4) ◽  
pp. 1615-1639 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), mean annual temperature (MAT), mean annual runoff (MAR), the standard deviation of annual precipitation (SDP), standard deviation of runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 worldwide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainties from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma (G-DG) procedure was applied to each annual runoff time series for hypothetical reservoir capacities of 1 × MAR and 3 × MAR and the average uncertainties in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were 25.1% (1 × MAR) and 11.9% (3 × MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1 × MAR or 3 × MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

scholarly journals Short-Term Plant Community Responses to Warming and Defoliation in a Northern Temperate Grassland

ISRN Ecology ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Eliza S. Deutsch ◽  
Edward W. Bork ◽  
James F. Cahill ◽  
Scott X. Chang
Keyword(s):  
Plant Community ◽  
Community Dynamics ◽  
Plant Biomass ◽  
Temperate Grassland ◽  
Community Diversity ◽  
Native Plant ◽  
Short Term ◽  
Canadian Prairies ◽  
Growing Seasons ◽  
Second Year

Little is known about the short-term impacts of warming on native plant community dynamics in the northern Canadian prairies. This study examined the immediate effects of elevated temperature and defoliation on plant community diversity, composition, and biomass within a native rough fescue (Festuca hallii (Vasey) Piper) grassland over two growing seasons. We used open-top chambers to simulate climate change and defoliated vegetation in midsummer of the first year to simulate biomass loss associated with periodic ungulate grazing. Warming marginally increased plant species diversity and changed community composition shortly after treatment, but effects were not apparent the second year, and there were no apparent impacts on plant biomass. Nonetheless, warming may have impacted community diversity indirectly through reduced soil moisture content, a pattern that persisted into the second year. Overall, this northern temperate grassland demonstrated limited community-level changes to warming even in the presence of defoliation.

scholarly journals Impact of Climate Change on the Streamflow Modulated by Changes in Precipitation and Temperature in the North Latitude Watershed of Nepal

Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 117
Author(s):  
Manisha Maharjan ◽  
Anil Aryal ◽  
Rocky Talchabhadel ◽  
Bhesh Raj Thapa
Keyword(s):  
Climate Change ◽  
Temperature Distribution ◽  
Assessment Tool ◽  
Rate Of Change ◽  
Maximum Temperature ◽  
Water Yield ◽  
Impact Of Climate Change ◽  
Northern Latitudes ◽  
The Impact ◽  
Precipitation And Temperature

It is unambiguous that climate change alters the intensity and frequency of precipitation and temperature distribution at the global and local levels. The rate of change in temperature in the northern latitudes is higher than the worldwide average. The annual distribution of precipitation over the Himalayas in the northern latitudes shows substantial spatial and temporal heterogeneity. Precipitation and temperature are the major driving factors that impact the streamflow and water availability in the basin, illustrating the importance of research on the impact of climate change on streamflow by varying the precipitation and temperature in the Thuli Bheri River Basin (TBRB). Multiple climate models were used to project and evaluate the precipitation and temperature distribution changes in temporal and spatial domains. To analyze the potential impact of climate change on the streamflow in the basin, the Soil and Water Assessment Tool (SWAT) hydrological model was used. The climate projection was carried out in three future time windows. The result shows that the precipitation fluctuates between approximately +12% and +50%, the maximum temperature varies between −7% and +7%, and the minimum temperature rises from +0.7% to +5% in intermediate- and high-emission scenarios. In contrast, the streamflow in the basin varies from −40% to +85%. Thus, there is a significant trend in the temperature increase and precipitation reduction in the basin. Further, the relationship between precipitation and temperature with streamflow shows a substantial dependency between them. The variability in precipitation and streamflow is successfully represented by the water yield in the basin, which plays an important role in the sustainability of the water-related projects in the basin and downstream to it. This also helps quantify the amount of water available for hydropower generation, agricultural production, and the water ecosystem in the TBRB.

scholarly journals Short-term climate-induced change in French plant communities

2019 ◽  
Vol 15 (7) ◽  
pp. 20190280 ◽  
Author(s):  
Gabrielle Martin ◽  
Vincent Devictor ◽  
Eric Motard ◽  
Nathalie Machon ◽  
Emmanuelle Porcher
Keyword(s):  
Climate Change ◽  
Community Composition ◽  
Plant Community ◽  
Plant Communities ◽  
Thermal Preference ◽  
Plant Community Composition ◽  
Large Area ◽  
High Dispersal ◽  
Short Period ◽  
The Impact

Latitudinal and altitudinal range shifts in response to climate change have been reported for numerous animal species, especially those with high dispersal capacities. In plants, the impact of climate change on species distribution or community composition has been documented mainly over long periods (decades) and in specific habitats, often forests. Here, we broaden the results of such long-term, focused studies by examining climate-driven changes in plant community composition over a large area (France) encompassing multiple habitat types and over a short period (2009–2017). To this end, we measured mean community thermal preference, calculated as the community-weighted mean of the Ellenberg temperature indicator value, using data from a standardized participatory monitoring scheme. We report a rapid increase in the mean thermal preference of plant communities at national and regional scales, which we relate to climate change. This reshuffling of plant community composition corresponds to a relative increase in the abundance of warm- versus cold-adapted species. However, support for this trend was weaker when considering only the common species, including common annuals. Our results thus suggest for the first time that the response of plant communities to climate change involves subtle changes affecting all species rare and common, which can nonetheless be detected over short time periods. Whether such changes are sufficient to cope with the current climate warming remains to be ascertained.

Exploring the role of lags and legacies in the productivity of Australian ecosystems

2021 ◽  
Author(s):  
Jon Page ◽  
Martin De Kauwe ◽  
Gab Abramowitz
Keyword(s):  
Climate Change ◽  
Climate Extremes ◽  
Multiple Time Scales ◽  
Plant Responses ◽  
Multiple Time ◽  
Legacy Effects ◽  
Ecological Memory ◽  
Using Data ◽  
The Impact

<p>The vegetation’s response to climate change is a major source of uncertainty in terrestrial biosphere model (TBM) projections. Constraining carbon cycle feedbacks to climate change requires improving our understanding of both the direct plant physiological responses to global change, as well as the role of legacy effects (e.g. reductions in plant growth, damage to the plant’s hydraulic transport system), that drive multi-timescale feedbacks. In particular, the role of these legacy effects - both the timescale and strength of the memory effect - have been largely overlooked in the development of model hypotheses. This is despite the knowledge that plant responses to climatic drivers occur across multiple time scales (seconds to decades), with the impact of climate extremes (e.g. drought) resonating for many years. Using data from 13 eddy covariance sites, covering two rainfall gradients in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales of influence of antecedent drivers on fluxes of net carbon exchange and evapotranspiration. Using our data assimilation approach we were able to partition the influence of ecological memory into both biological and environmental components. Overall, we found that the importance of ecological memory to antecedent conditions increased as water availability declines. Our results therefore underline the importance of capturing legacy effects in TBMs used to project responses in water limited ecosystems.</p>

A model for predicting invasive weed and grass dynamics. II. Accuracy evaluation

Weed Science ◽  
2005 ◽  
Vol 53 (5) ◽  
pp. 605-614 ◽  
Author(s):  
Matthew J. Rinella ◽  
Roger L. Sheley
Keyword(s):  
Community Composition ◽  
Plant Community ◽  
Weed Management ◽  
Null Hypothesis ◽  
Leafy Spurge ◽  
Community Response ◽  
Stem Length ◽  
Plant Community Composition ◽  
Invasive Weed ◽  
The Impact

The impact of invasive weed management on plant community composition is highly dependent on location-specific factors. Therefore, treatment means from experiments conducted at a given set of locations will not reliably predict community response to weed management elsewhere. We developed a model that rescales treatment means to better match local conditions. The goal of this paper was to determine if this rescaling improves predictions. We used our model to predict leafy spurge stem length density and grass biomass data from field experiments. The experiments consisted of herbicide-treated plots, untreated controls, and, in some cases, grass seeding treatments. When herbicides suppressed leafy spurge, the model explained 21 to 48% more variation in grass response than did mean grass response to the same or similar herbicide treatments applied at other sites. When herbicides killed grass, the model explained 53% more variation in leafy spurge response than did mean leafy spurge response to the same herbicide treatment applied at other sites. We regressed model predictions against observed data and tested the null hypothesis that resulting slope terms were equal to 1.0. Because the null hypothesis was rejected in two of four tests, the model may systematically over- or underpredict in some situations. However, measurement error in the observed data, unintended herbicide injury, or an inaccurate allometric relationship may account for a major proportion of the systematic deviations, and these factors would not cause prediction error in some management applications. Because the model tends to be better than the means from experiments at predicting plant community composition, we conclude that the model could advance managers' ability to predict plant community responses to invasive weed management.

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