Search

Soil degradation is one of the greatest environmental issues our planet faces today, with over 33% of Earth's soils currently degraded. Drylands are especially vulnerable to soil degradation given their history of intensive land use and desertification. Active soil restoration has been identified as a leading strategy to combat soil degradation and promote ecosystem recovery. However, soil‐based dryland restoration techniques have shown varying success, potentially due to a lack of understanding of the ecological contexts in which soil‐based treatments are most beneficial.To improve our understanding of how to best use active soil restoration to restore degraded drylands, we conducted a global meta‐analysis of soil treatment effectiveness at improving soil health across varying environmental gradients. The soil health metrics we analysed were aggregate stability, bulk density, soil moisture, soil organic carbon (SOC), soil nitrogen, mycorrhizal colonization and basal respiration. For this meta‐analysis we collected 155 publications, yielding 1403 unique studies spanning six continents.We found that overall, soil restoration had a beneficial effect on all measures of soil health ranging from a +11% increase in bulk density (inverse) to a +6967% increase in mycorrhizal colonization. Aridity and soil texture greatly influenced restoration effectiveness for certain soil health metrics. Specifically, for soil carbon and nitrogen, restoration was found to be most effective in arid, fine‐textured soils and mesic, coarse‐textured soils. Additionally, we found that organic amendments were most effective at increasing SOC, while fungi inoculation was most effective at increasing mycorrhizal colonization.Synthesis and applications: Our findings indicate that active soil restoration is an effective tool for increasing soil health and provide information on optimal treatments and site conditions for improving certain aspects of soil health. This could greatly help inform decision‐making, and thus improve outcomes, in dryland restoration worldwide. [ABSTRACT FROM AUTHOR]

Aim: Grasslands cover a third of Earth's landmass and provide critical ecosystem services. Anticipating how perennial C3 (cool‐season) and C4 (warm‐season) grasses respond to climate change will be key to predicting future composition and functioning of grasslands. Here, we evaluate environmental drivers of C3 and C4 perennial distributions and assess how C3 and C4 grass distributions shift in response to future climate change. Location: Western United States. Methods: We developed integrated species distribution models to identify climate and soil drivers of relative abundance of C3 and C4 perennial grasses. We then created projections of species abundances under future climate and evaluated when and where projected shifts in relative abundance were robust across climate models. Results: Historically, C3 grasses occupied areas with lower temperature and more variable precipitation regimes, while C4 grasses occupied areas of higher temperature, greater temperature variability and greater warm‐season precipitation. C4 species also occupied narrower soil texture niches. In response to future climate change, C3 grass abundance declined across 74% of areas, while C4 abundance increased across 66% of areas. C3 grasses expanded in mid‐ to higher‐latitude areas with increasing temperature and decreasing seasonality of precipitation. In contrast, C4 grasses increased in higher‐latitude regions, but declined in lower‐latitude, dryer regions. Results were surprisingly robust across climate scenarios, suggesting high confidence in the direction of these future changes. Main Conclusions: Findings imply C3 and C4 perennial grasses will have highly divergent responses to climate change that may result in grassland functional compositional changes. Increasing temperatures and precipitation variability may favour some C4 grasses, but C4 habitat expansion may be constrained by soil conditions in western USA. Results provide actionable insights for anticipating the impacts of climate change on grass‐dominated and co‐dominated ecosystems and improving large‐scale conservation and restoration efforts. [ABSTRACT FROM AUTHOR]

The match between species trait values and local abiotic filters can restrict community membership. An often‐implicit assumption of this relationship is that abiotic filters select for a single locally optimal strategy, though difficulty in isolating effects of the abiotic environment from those of dispersal limitation and biotic interactions has resulted in few empirical tests of this assumption. Similar constraints have made it difficult to assess whether the type and intensity of abiotic filters shift along gradients of environmental harshness, as predicted by the stress‐dominance hypothesis.We planted 9,216 plants of 29 perennial grass and forb species that had a range of functional trait values and were assigned to a warm, intermediate or cool temperature tolerance pool across eight sites on the Colorado Plateau. We compared the distributions of traits of surviving individuals to null distributions to evaluate whether there were shifts in trait means and variation. Borrowing from phenotypic selection concepts in evolutionary biology, we assessed support for stabilizing, directional and disruptive abiotic filtering of trait distributions and whether these types of filtering varied with initial species pool.Functional composition was significantly different from null distributions for nearly all traits at all sites, with trait variation more restricted in harsher abiotic conditions, supporting the stress‐dominance hypothesis. Contrary to expectations, we primarily found evidence for directional selection, which increased in frequency in warm species pools while disruptive selection was found more often in cool and intermediate species pools.Synthesis. This study provides a controlled experimental approach to test the effect of the abiotic environment on plant trait filtering. We found that opportunistic strategies allowing for rapid water acquisition during favourable periods improved survival at warmer sites. Species with these strategies may be expected to benefit from increasing aridity and may be selected for active management efforts. More generally, the prevalence of directional selection may have important implications for dynamic vegetation models that rely on trait distributions for translating environmental variation into ecosystem processes. [ABSTRACT FROM AUTHOR]

Non-forest ecosystems, dominated by shrubs, grasses and herbaceous plants, provide ecosystem services including carbon sequestration and forage for grazing, and are highly sensitive to climatic changes. Yet these ecosystems are poorly represented in remotely sensed biomass products and are undersampled by in situ monitoring. Current global change threats emphasize the need for new tools to capture biomass change in non-forest ecosystems at appropriate scales. Here we developed and deployed a new protocol for photogrammetric height using unoccupied aerial vehicle (UAV) images to test its capability for delivering standardized measurements of biomass across a globally distributed field experiment. We assessed whether canopy height inferred from UAV photogrammetry allows the prediction of aboveground biomass (AGB) across low-stature plant species by conducting 38 photogrammetric surveys over 741 harvested plots to sample 50 species. We found mean canopy height was strongly predictive of AGB across species, with a median adjusted R 2 of 0.87 (ranging from 0.46 to 0.99) and median prediction error from leave-one-out cross-validation of 3.9%. Biomass per-unit-of-height was similar within but different among, plant functional types. We found that photogrammetric reconstructions of canopy height were sensitive to wind speed but not sun elevation during surveys. We demonstrated that our photogrammetric approach produced generalizable measurements across growth forms and environmental settings and yielded accuracies as good as those obtained from in situ approaches. We demonstrate that using a standardized approach for UAV photogrammetry can deliver accurate AGB estimates across a wide range of dynamic and heterogeneous ecosystems. Many academic and land management institutions have the technical capacity to deploy these approaches over extents of 1-10 ha -1 . Photogrammetric approaches could provide much-needed information required to calibrate and validate the vegetation models and satellite-derived biomass products that are essential to understand vulnerable and understudied non-forested ecosystems around the globe., (© 2021 The Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London.)