Meta-Analysis and Modelling to Explore Soil-Water Partitioning of Bioactive Chemical Pollutants

2022 ◽  
Author(s):  
Rachel Louise Gomes ◽  
Andrea-Lorena Garduño-Jiménez ◽  
Juan-Carlos Duran-Alavrez
2021 ◽  
Author(s):  
Javier de la Casa ◽  
Adrià Barbeta ◽  
Asun Rodriguez-Uña ◽  
Lisa Wingate ◽  
Jérôme Ogeé ◽  
...  

<p> </p><p>Long-standing ecological theory establishes that the isotopic composition of the plant water reflects that of the root-accessed sources, at least in non-saline or non-xeric environments. However, a growing number of studies challenge this assumption by reporting plant-source offsets in water isotopic composition, for a wide range of ecosystems. We conducted a global meta-analysis to systematically quantify the magnitude of this plant-source offset in water isotopic composition and its potential explanatory factors. We compiled 108 studies reporting dual water isotopic composition (δ<sup>2</sup>H and δ<sup>18</sup>O) of plant and source water. From these studies, we extracted the δ<sup>2</sup>H and δ<sup>18</sup>O of both plant and source waters for 223 plant species from artic to tropical biomes. For each species and sampling campaign, within each study, we calculated the mean line conditioned excess (LC-excess), with the slope and intercept of the local meteoric water line, and the mean soil water line conditioned excess (SWL-excess), from the slope and intercept of the soil water evaporation line. For each study site and sampling campaign, we obtained land surface temperature and volumetric soil water from the ERA5 database. For each study species, we recorded the functional type, leaf habit and for those available wood density. We found, on average, a significantly negative SWL-excess: plant water was systematically more depleted in δ<sup>2</sup>H than soil water. In > 90% of the cases with significantly negative SWL-excess, we also found negative LC-excess values, meaning that access to sources alternative to soil water was unlikely to explain negative SWL-excess values. </p><p>Calculated SWL-excess was affected by temperature and humidity: there were larger mismatches between plant and source water in isotopic composition in colder and wetter sites. Angiosperms, broadleaved and deciduous species exhibited more negative SWL-excess values than gymnosperms, narrow-leaved and evergreen species. Our results suggest that when using the dual isotopic approach, potential biases in the adscription of plant water sources are more likely in broadleaved forests in humid, and cold regions. Potential underlying mechanism for these isotopic mismatches will be discussed.</p><p> </p>


2019 ◽  
Vol 7 (2) ◽  
pp. 84
Author(s):  
Oluwafemi Benjamin Adeleke

<p>The study identified factors responsible for wetland dynamics and negative marks produced on the environment in the area.  It equally suggested efforts aimed at reducing effects of the factors on the environment. The study incorporated both meta-analysis of case studies and questionnaires distribution and administration to the respondents who are mainly members of the Fadama User Group (FUG). The results showed changes in rainfall intensity as the major factor responsible for wetland loss; followed by settlement developments and loss of soil water due to river drainage. The results further revealed the effects of the factors to include siltation of drainages, destruction of ecosystem and loss of wetness, and emergent of heavy flooding. The study concluded by suggesting efforts aimed at reducing the influence of the factors on the environment.</p>


2020 ◽  
Author(s):  
Femke Lutz ◽  
Stephen DelGrosso ◽  
Stephen Ogle ◽  
Stephen Williams ◽  
Sara Minoli ◽  
...  

Abstract. No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to large uncertainties, as the processes producing the emissions are complex and strongly non-linear. Previous findings have shown deviations between the LPJmL5.0-tillage model and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA, to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management and/or the representation of soil water dynamics. Model results were compared to observational data and outputs from field-scale DayCent simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer data base for comparison than non-continuous measurements at the experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions as well as the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to over-estimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water as well as the N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management as well as improvements in soil moisture highlight the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.


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