Grazing, fire, and climate shape mesic grassland communities. With global change altering all three factors, understanding how grasslands respond to changes in these combined drivers may aid in ...projecting future changes in grassland ecosystems. We manipulated rainfall and simulated grazing (clipping) in two long-term fire experiments in mesic grasslands in North America (NA) and South Africa (SA). Despite their common drivers, grasslands in NA and SA differ in evolutionary history. Therefore, we expected community structure and production in NA and SA to respond differently to fire, grazing, and drought. Specifically, we hypothesized that NA plant community composition and production would be more responsive than the SA plant communities to changes in the drivers and their interactions, and that despite this expected stability of SA grasslands, drought would be the dominant factor controlling production, but grazing would play the primary role in determining community composition at both sites. Contrary to our hypothesis, NA and SA grasslands generally responded similarly to grazing, drought, and fire. Grazing increased diversity, decreased grass cover and production, and decreased belowground biomass at both sites. Drought alone minimally impacted plant community structure, and we saw similar treatment interactions at the two sites. Drought was not the primary driver of grassland productivity, but instead drought effects were similar to or less than grazing and fire. Even though these grasslands differed in evolutionary history, they responded similarly to our fire, grazing, and climate manipulations. Overall, we found community and ecosystem convergence in NA and SA grasslands. Grazing and fire are as important as climate in controlling mesic grassland ecosystems on both continents.
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BFBNIB, FZAB, GIS, IJS, INZLJ, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZRSKP
Climate change is intensifying the hydrologic cycle and is expected to increase the frequency of extreme wet and dry years. Beyond precipitation amount, extreme wet and dry years may differ in other ...ways, such as the number of precipitation events, event size, and the time between events. We assessed 1614 long‐term (100 year) precipitation records from around the world to identify key attributes of precipitation regimes, besides amount, that distinguish statistically extreme wet from extreme dry years. In general, in regions where mean annual precipitation (MAP) exceeded 1000 mm, precipitation amounts in extreme wet and dry years differed from average years by ~40% and 30%, respectively. The magnitude of these deviations increased to >60% for dry years and to >150% for wet years in arid regions (MAP<500 mm). Extreme wet years were primarily distinguished from average and extreme dry years by the presence of multiple extreme (large) daily precipitation events (events >99th percentile of all events); these occurred twice as often in extreme wet years compared to average years. In contrast, these large precipitation events were rare in extreme dry years. Less important for distinguishing extreme wet from dry years were mean event size and frequency, or the number of dry days between events. However, extreme dry years were distinguished from average years by an increase in the number of dry days between events. These precipitation regime attributes consistently differed between extreme wet and dry years across 12 major terrestrial ecoregions from around the world, from deserts to the tropics. Thus, we recommend that climate change experiments and model simulations incorporate these differences in key precipitation regime attributes, as well as amount into treatments. This will allow experiments to more realistically simulate extreme precipitation years and more accurately assess the ecological consequences.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
1. Anthropocene defaunation is the global phenomenon of human-induced animal biodiversity loss. Understanding the patterns and process of defaunation is critical to predict outcomes for wildlife ...populations and cascading consequences for ecosystem function and human welfare. 2. We investigated a defaunation gradient in north-eastern Gabon by establishing 24 transects at varying distances (2-30 km) to rural villages and surveying the abundance and composition of vertebrate communities. Distance from village was positively correlated with observations of hunting (shotgun shells, campfires, hunters), making it a good proxy for hunting pressure. 3. Species diversity declined significantly with proximity to village, with mammal richness increasing by roughly 1-5 species every 10 km travelled away from a village. Compared to forest far from villages, the wildlife community near villages consisted of higher abundances of large birds and rodents and lower abundances of large mammals like monkeys and ungulates. 4. Distance to nearest village emerged as a key driver of the relative abundance of five of the six taxonomic guilds, indicating that the top-down force of hunting strongly influences large vertebrate community composition and structure. Several measures of vegetation structure also explained animal abundance, but these varied across taxonomic guilds. Forest elephants were the exception: no measured variable or combination of variables explained variation in elephant abundances. 5. Synthesis and applications. Hunting is concentrated within 10 km around villages, creating a hunting halo characterized by heavily altered animal communities composed of relatively small-bodied species. Although the strongest anthropogenic effects are relatively distance-limited, the linear increase in species richness shown here even at distances 30 km from villages suggests that hunting may have altered vertebrate abundances across the entire landscape. Central African forests store > 25% of the carbon in tropical forests and are home to 3000 endemic species, but roughly 53% of the region lies within the village hunting halo. Resource management strategies should take into account this hunting-induced spatial variation in animal communities. Near villages, resource management should focus on sustainable community-led hunting programmes that provide long-term supplies of wild meat to rural people. Resource management far from villages should focus on law enforcement and promoting industry practices that maintain remote tracts of land to preserve ecosystem services like carbon storage and biodiversity.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Abstract
Little is currently known about how climate modulates the relationship between plant diversity and soil organic carbon and the mechanisms involved. Yet, this knowledge is of crucial ...importance in times of climate change and biodiversity loss. Here, we show that plant diversity is positively correlated with soil carbon content and soil carbon-to-nitrogen ratio across 84 grasslands on six continents that span wide climate gradients. The relationships between plant diversity and soil carbon as well as plant diversity and soil organic matter quality (carbon-to-nitrogen ratio) are particularly strong in warm and arid climates. While plant biomass is positively correlated with soil carbon, plant biomass is not significantly correlated with plant diversity. Our results indicate that plant diversity influences soil carbon storage not via the quantity of organic matter (plant biomass) inputs to soil, but through the quality of organic matter. The study implies that ecosystem management that restores plant diversity likely enhances soil carbon sequestration, particularly in warm and arid climates.
Aims
Foliar nutrient resorption is a critical process for considerations of ecosystem nutrient cycles. Previous studies have described the independent effects of climatic factors, plant and soil ...nutrient status on nutrient resorption. However, little is known about the comprehensive effects of these factors on nutrient resorption, especially based on observations in
situ
.
Methods
In a semi-arid grassland of the Loess Plateau, China, we conducted an eight-year field survey and sampled leaves and soils separately in 2013, 2016, and 2020. We explored interannual variation in foliar nutrient resorption efficiency (NuRE, including nitrogen and phosphorus resorption efficiency, i.e., NRE and PRE) and the driving factors in graminoids and forbs.
Results
The NuRE in graminoids varied significantly, but in forbs varied insignificantly among years, indicating a more flexible nutrient resorption strategy in graminoids. Further, climatic variables showed stronger effects on NuRE than soil nutrients. Specifically, growing-season temperature and precipitation controlled NuRE of graminoids and forbs by regulating green leaf N:P ratio (N:Pg), while soil nutrients did not affect NuRE. The regulation of N:Pg on NuRE was explained by foliar stoichiometric control in which N and P were resorbed proportionally with N:Pg. Meanwhile, the positive relationships between NRE and PRE and between NRE:PRE and N:Pg confirmed stoichiometric control on NuRE.
Conclusion
Our findings suggested that growing season hydro-thermal factors affected the interannual variations of NuRE through a foliar stoichiometric control strategy. Meanwhile, more NuRE plasticity and positive responses to climatic factors in graminoids (the dominant group here) could explain their dominance in this grassland.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Climatic changes are altering Earth's hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation ...events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta‐analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.
Future changes in precipitation will strongly impact ecosystem functioning and services through changes in plant growth. Here, we synthesize 83 precipitation experiments to look at responses of above and belowground plant growth (ANPP and BNPP) across climatic gradients and levels of precipitation change extremity. Overall, we found that (1) ANPP was more responsive to precipitation increases than decreases, and this was especially evident in dry ecosystems; (2) BNPP responses were similar under precipitation increases vs. decreases; (3) under extreme wet conditions, NPP responses leveled off, creating a saturating function of NPP response vs. the magnitude of precipitation change. Based on these findings, we suggest that future research focus on BNPP and plant responses to extreme precipitation change.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Questions
Restoration of ecosystems is complex, with multiple targets that can work in concert or conflict with each other, such as biodiversity, species dominance and biomass. When properly managed, ...longleaf pine (LLP) savannas are among the most biologically diverse habitats in the world. However, anthropogenic influences, such as fire suppression, have decimated this ecosystem and its biodiversity, making restoration a priority. Here, we describe the biodiversity and community dynamics seen in the understory layer across xeric LLP savannas in North Carolina and then answer the following questions: What are the predictors of (1) biodiversity, (2) dominance and (3) biomass at multiple spatial scales?
Location
Fifteen observational study sites in North Carolina spanning from the Sandhills to the Coastal Plain.
Methods
At each of the 15 sites, 25 sampling plots were established where above‐ground herbaceous biomass, species presence and abundance, soil characteristics and light availability were measured along with numerous other environmental variables.
Results
Considerable variation exists across study plots within and across sites, with plant species richness ranging from 1 to 17 per m2. The relative cover of the dominant grass species, Aristida stricta (wiregrass), also varied greatly within and across sites, with a median of ca. 30% relative cover per plot. Wiregrass was a significant predictor of biomass and biodiversity at small scales. With increasing wiregrass abundance, richness decreases, with 25% relative wiregrass cover leading to the highest levels of biodiversity. Likewise, because wiregrass abundance is one of the stronger predictors of above‐ground biomass, we also found a unimodal richness–biomass relationship.
Conclusions
Our results indicate that at lower ends of the productivity and richness gradients, land managers can increase all three restoration targets in the understory at the same time; however, at more diverse and productive sites, restoration practitioners may need to prioritize one target or find a balance between all three.
The longleaf pine ecosystem once dominated the southeastern United States, but because of anthropogenic influences, the ecosystem and its biodiverse understory are in need of restoration. This study explored the relationship between three restoration targets—biodiversity, dominant species and productivity—to help land managers determine how to balance potentially conflicting restoration targets.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Plants, soils and microorganisms play important roles in maintaining stable terrestrial stoichiometry. Studying how nutrient balances of these biotic and abiotic players vary across temperature ...gradients is important when predicting ecosystem changes on a warming planet. The respective responses of plant, soil and microbial stoichiometric ratios to warming have been observed, however, whether and how the stoichiometric correlations among the three components shift under warming has not been clearly understood and identified. In the present study, we have performed a meta-analysis based on 600 case studies from 74 sites or locations to clarify whether and how warming affects plant, soil and microbial stoichiometry, respectively, and their correlations. Our results indicated that: (1) globally, plants had higher C:N and C:P values compared to soil and microbial pools, but their N:P distributions were similar; (2) warming did not significantly alter plant, soil and microbial C:N and C:P values, but had a noticeable effect on plant N:P ratios. When ecosystem types, duration and magnitude of warming were taken into account, there was an inconsistent and even inverse warming response in terms of the direction and magnitude of changes in the C:N:P ratios occurring among plants, soils and microorganisms; (3) despite various warming responses of the stoichiometric ratios detected separately for plants, soils and microorganisms, the stoichiometric correlations among all three parts remained constant even under different warming scenarios. Our study highlighted the complexity of the effect of warming on the C:N:P stoichiometry, as well as the absence and importance of simultaneous measurements of stoichiometric ratios across different components of terrestrial ecosystems, which should be urgently strengthened in future studies.
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•600 case studies from 74 sites were selected to test terrestrial C:N:P correlations.•Plants had higher C:N and C:P values compared to soil and microbial pools.•Warming has only exerted obvious impacts on plant N:P ratios.•C:N:P ratios responded inconsistently in different ecosystems and warming scenarios.•C:N correlations among three parts remained stable under different warming scenarios.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Univariate and multivariate methods are commonly used to explore the spatial and temporal dynamics of ecological communities, but each has limitations, including oversimplification or ion of ...communities. Rank abundance curves (RACs) potentially integrate these existing methodologies by detailing species‐level community changes. Here, we had three goals: first, to simplify analysis of community dynamics by developing a coordinated set of R functions, and second, to demystify the relationships among univariate, multivariate, and RACs measures, and examine how each is influenced by the community parameters as well as data collection methods. We developed new functions for studying temporal changes and spatial differences in RACs in an update to the R package library(“codyn”), alongside other new functions to calculate univariate and multivariate measures of community dynamics. We also developed a new approach to studying changes in the shape of RAC curves. The R package update presented here increases the accessibility of univariate and multivariate measures of community change over time and difference over space. Next, we use simulated and real data to assess the RAC and multivariate measures that are output from our new functions, studying (1) if they are influenced by species richness and evenness, temporal turnover, and spatial variability and (2) how the measures are related to each other. Lastly, we explore the use of the measures with an example from a long‐term nutrient addition experiment. We find that the RAC and multivariate measures are not sensitive to species richness and evenness and that all the measures detail unique aspects of temporal change or spatial differences. We also find that species reordering is the strongest correlate of a multivariate measure of compositional change and explains most community change observed in long‐term nutrient addition experiment. Overall, we show that species reordering is potentially an understudied determinant of community changes over time or differences between treatments. The functions developed here should enhance the use of RACs to further explore the dynamics of ecological communities.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Seasonal, not annual climate variability drives grassland productivity.•Heat waves and drought in summer dominate the temporal variation in productivity.•Impacts of winter and spring warming may ...increase as warming trends continue.•Long-term (20 yr) grassland ANPP data were related with daily climate factors.
Strong correlations between aboveground net primary productivity (ANPP) of grasslands and mean annual temperature or precipitation have been widely reported across regional or continental scales; however, inter-annual variation in these climate factors correlates poorly with site-specific ANPP. We hypothesize that the reason for these weak correlations is that the impacts of climatic variation on grassland productivity depend on the timing and intensity of variation in temperature and precipitation. In this study, long-term records of grassland productivity on the Loess Plateau in China were related with daily temperature and precipitation during 1992–2011 using Partial Least Squares (PLS) regression to test the above-mentioned hypothesis. Our results suggested that temperature increases during the early stage of the growing season (April–May) were positively correlated with ANPP. However, these effects were canceled out when this phase was followed by a hot and dry summer (June–July). Impacts of drought and heat in August on productivity were negligible. Increased temperature and precipitation during the senescence period (September–October) and a warmer dormancy phase (November–March) were negatively correlated with productivity in the following year, while precipitation during the dormancy period had no detectable effects. Climatic variability in summer has thus far been the dominant driver of temporal variation in grassland productivity. Warming during winter and spring currently play minor roles, but it seems likely that the importance of these secondary impacts may increase as warming trends continue. This evaluation of climate variability impacts on ecosystem function (e.g. grassland productivity) implies that not only the magnitude but also the timing of changes in temperature and precipitation determines how the impacts of climate changes on ecosystems will unfold.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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