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Climate change is increasing the frequency and intensity of extreme events like drought and flooding, which threaten to amplify other global change drivers such as species invasion. We investigate the effect of wet and dry extreme precipitation regimes on invasive species' abundances in northern tallgrass prairies. Because soil moisture is a key determinant of prairie composition, theory and evidence suggest drought conditions will hinder invasion, whereas wetter conditions will enhance invasion. To test this hypothesis, we explored the effect of precipitation on invasive plant species abundance from 2010 to 2019 in 25 managed prairies using observations from 267 transects comprising 6675 plots throughout western Minnesota, USA. We estimated how increases in the number of extremely wet or dry months in a year altered overall invasive species abundance and the abundance of the highly invasive grasses Poa pratensis and Bromus inermis. We found that a greater occurrence of abnormally wet months increased invasive species abundance but found mixed evidence that abnormally dry conditions hindered invasion. Further, more moderately wet and dry months reduced native grass abundance. Together, these results suggest that more frequent extremely wet months may intensify invasive dominance and that dry months may not counterbalance these trends. Given the considerable uncertainty still surrounding the interactive effects of climate change and invasion on native plant communities, this research represents an important step toward quantifying the complex influence of precipitation extremes on invasion dynamics in managed ecosystems of critical conservation concern. [ABSTRACT FROM AUTHOR]

Drought events are projected to be more extreme and frequent in the future and have profound influences on the structure and functions of terrestrial ecosystems. Thus, better understanding the mechanisms of recovery is critical for predicting the future dynamics of terrestrial ecosystems. We performed a 7‐year field precipitation experiment to examine recovery of a grassland ecosystem from different magnitudes of sustained drought, from slight to extreme. The ecosystem was exposed to precipitation treatments in the first 3 years (2010–2012) and recovered during the last 4 years (2013–2016) without precipitation treatments. Overall, large reductions of aboveground net primary productivity (ANPP, −43.3%) and perennial forb biomass (−83.1%) were observed in the third year (2012) of extreme drought only. Nevertheless, ANPP fully recovered within 1 year after the drought treatments were terminated, and the rapid recovery was mainly due to increased soil total nitrogen and root biomass allocation after drought. Surprisingly, large increases of ANPP under the extreme drought treatment occurred during the recovery periods from 2013 to 2015 (+74.1, +88.5, and +119.8 g m−2 year−1) compared to the control. The overcompensation offset the extreme drought‐induced reduction of ANPP in the treatment years and was primarily ascribed to the enhanced biomass of perennial grasses (PG). Higher resistance to drought and fast resource acquisition strategy might drive the rapid recovery and expansion of PG. Our findings revealed the rapid recovery of grasslands and the critical role of community overcompensation in maintaining grassland ecosystem function and stability under future climate change scenarios. [ABSTRACT FROM AUTHOR]

• Combined application of CASA model and random forest regression models. • Precipitation was identified as a vital climatic factor. • The most important months for climatic factors were identified. • NPP exhibited nonlinear responses across the three analyzed temporal scales. Grassland, as highly vulnerable ecosystem, requires a comprehensive understanding of its dynamics and response patterns to climate factors in response to climate change challenges. While previous research has primarily centered on the influence of interannual climate variability on grassland Net Primary Productivity (NPP), knowledge of the impacts of seasonal or monthly climate variations on annual net primary productivity (ANPP) remains limited. This study investigated the climatic drivers of grassland NPP dynamics in Xinjiang's Altay region from 2000 to 2022 using the Carnegie-Ames-Stanford approach (CASA) model and the random forest regression model. The study examined the significance and patterns of precipitation, solar radiation, temperature, soil moisture, and snowmelt water on NPP at three temporal scales. The results revealed the following key findings: (1) Grassland NPP declined significantly from 2000 to 2009 but showed a gradual increase from 2009 to 2022. Spatially, higher values were observed in the northern region and lower values were observed in the southern region. (2) Precipitation was the primary influential climate factor affecting grassland NPP, followed by solar radiation, temperature, soil moisture, and snowmelt water. In determining the significance of climate factor timing on ANPP, June played a critical role particularly for precipitation, temperature, and soil moisture, while August was essential for solar radiation. Moreover, the importance of snowmelt water had a bimodal distribution, with peaks in April and October. (3) Grassland NPP exhibited diverse nonlinear response dynamics and spatial heterogeneity to various climate factors at different temporal scales. These findings highlight the importance of considering both the magnitude and the local conditions, as well as the timing of climate variations when studying grassland dynamic responses to climate change and predicting future impacts. These insights enhance the comprehension of the intricate dynamics of grassland ecosystems and enhance predictions of their responses to future climate change. [ABSTRACT FROM AUTHOR]

Abstract: Understanding ecosystem dynamics and predicting directional changes in ecosystem in response to global changes are ongoing challenges in ecology. Here we present a framework that links productivity dynamics and ecosystem state transitions based on a spatially continuous dataset of aboveground net primary productivity (ANPP) from the temperate grassland of China. Across a regional precipitation gradient, we quantified spatial patterns in ANPP dynamics (variability, asymmetry and sensitivity to rainfall) and related these to transitions from desert to semi‐arid to mesic steppe. We show that these three indices of ANPP dynamics displayed distinct spatial patterns, with peaks signalling transitions between grassland types. Thus, monitoring shifts in ANPP dynamics has the potential for predicting ecosystem state transitions in the future. Current ecosystem models fail to capture these dynamics, highlighting the need to incorporate more nuanced ecological controls of productivity in models to forecast future ecosystem shifts. [ABSTRACT FROM AUTHOR]

Climate change forecasts of more frequent climate extremes suggest that such events will become increasingly important drivers of future ecosystem dynamics and function. Because the rarity and unpredictability of naturally occurring climate extremes limits assessment of their ecological impacts, we experimentally imposed extreme drought and a mid-summer heat wave over two years in a central U.S. grassland. While the ecosystem was resistant to heat waves, it was not resistant to extreme drought, which reduced aboveground net primary productivity (ANPP) below the lowest level measured in this grassland in almost 30 years. This extreme reduction in ecosystem function was a consequence of reduced productivity of both C4 grasses and C3 forbs. However, the dominant forb was negatively impacted by the drought more than the dominant grass, and this led to a reordering of species abundances within the plant community. Although this change in community composition persisted post-drought, ANPP recovered completely the year after drought due to rapid demographic responses by the dominant grass, compensating for loss of the dominant forb. Overall, these results show that an extreme reduction in ecosystem function attributable to climate extremes (e.g., low resistance) does not preclude rapid ecosystem recovery. Given that dominance by a few species is characteristic of most ecosystems, knowledge of the traits of these species and their responses to climate extremes will be key for predicting future ecosystem dynamics and function. [ABSTRACT FROM AUTHOR]

In grassland ecosystems, where soil water most frequently controls ecosystem processes, expected changes in precipitation and temperature may have dramatic effects on ecosystem dynamics. Previous observational studies have reported that aboveground net primary production (ANPP) in grasslands is very sensitive to changes in precipitation. Yet, we lack experimentally based evidence to support these observations. Further, most of the studies have focused solely on ANPP, neglecting belowground production (BNPP). This is an important gap in our knowledge, as BNPP represents 50% or more of total net primary production (NPP) in grasslands. Here, we present results from a 3-year water manipulation experiment (2008-2010) at two sites in the central grassland region of North America, USA. We were successful in changing the soil water content in our treatments, but these changes resulted in different, but significant responses in ANPP and BNPP at our two sites. At the shortgrass steppe, we found that neither NPP nor ANPP were sensitive to treatment precipitation, and although we found BNPP was sensitive to changes in treatment precipitation, the direction of the response varied between years. In contrast, ANPP was very sensitive to treatment precipitation on the mixed-grass prairie, whereas BNPP was insensitive. Based on our finding that two grassland ecosystems showed dramatically different above and belowground production responses to soil water manipulations, we cannot assume that predicted changes in climate will cause similar above- and belowground production responses. Second, our results demonstrated that sites within the same region may differ markedly in the sensitivity of ANPP to changes in growing season precipitation. [ABSTRACT FROM AUTHOR]

1: Given the predictions of increased drought probabilities under various climate change scenarios, there have been numerous experimental field studies simulating drought using transparent roofs in different ecosystems and regions. Such roofs may, however, have unknown side effects, called artifacts, on the measured variables potentially confounding the experimental results. A roofed control allows the quantification of potential artifacts, which is lacking in most experiments. 2: We conducted a drought experiment in experimental grasslands to study artifacts of transparent roofs and the resulting effects of artifacts on ecosystems relative to drought on three response variables (aboveground biomass, litter decomposition and plant metabolite profiles). We established three drought treatments, using (1) transparent roofs to exclude rainfall, (2) an unroofed control treatment receiving natural rainfall and (3) a roofed control, nested in the drought treatment but with rain water reapplied according to ambient conditions. 3: Roofs had a slight impact on air (+0.14°C during night) and soil temperatures (−0.45°C on warm days, +0.25°C on cold nights), while photosynthetically active radiation was decreased significantly (−16%). Aboveground plant community biomass was reduced in the drought treatment (−41%), but there was no significant difference between the roofed and unroofed control, i.e., there were no measurable roof artifact effects. 4: Compared to the unroofed control, litter decomposition was decreased significantly both in the drought treatment (−26%) and in the roofed control treatment (−18%), suggesting artifact effects of the transparent roofs. Moreover, aboveground metabolite profiles in the model plant species Medicago x varia were different from the unroofed control in both the drought and roofed control treatments, and roof artifact effects were of comparable magnitude as drought effects. 5: Our results stress the need for roofed control treatments when using transparent roofs for studying drought effects, because roofs can cause significant side effects. [ABSTRACT FROM AUTHOR]

Background: Little is known about the combined impacts of global environmental changes and ecological disturbances on ecosystem functioning, even though such combined impacts might play critical roles in shaping ecosystem processes that can in turn feed back to climate change, such as soil emissions of greenhouse gases. Methodology/Principal Findings: We took advantage of an accidental, low-severity wildfire that burned part of a long-term global change experiment to investigate the interactive effects of a fire disturbance and increases in CO2 concentration, precipitation and nitrogen supply on soil nitrous oxide (N2O) emissions in a grassland ecosystem. We examined the responses of soil N2O emissions, as well as the responses of the two main microbial processes contributing to soil N2O production - nitrification and denitrification - and of their main drivers. We show that the fire disturbance greatly increased soil N2O emissions over a three-year period, and that elevated CO2 and enhanced nitrogen supply amplified fire effects on soil N2O emissions: emissions increased by a factor of two with fire alone and by a factor of six under the combined influence of fire, elevated CO2 and nitrogen. We also provide evidence that this response was caused by increased microbial denitrification, resulting from increased soil moisture and soil carbon and nitrogen availability in the burned and fertilized plots. Conclusions/Significance: Our results indicate that the combined effects of fire and global environmental changes can exceed their effects in isolation, thereby creating unexpected feedbacks to soil greenhouse gas emissions. These findings highlight the need to further explore the impacts of ecological disturbances on ecosystem functioning in the context of global change if we wish to be able to model future soil greenhouse gas emissions with greater confidence. [ABSTRACT FROM AUTHOR]

Abstract: Predicting future carbon (C) dynamics in grassland ecosystems requires knowledge of how grazing and global climate change (e.g., warming, elevated CO2, increased precipitation, drought and N fertilization) interact to influence C storage and release. Here, we synthesized data from 223 grassland studies to quantify the individual and interactive effects of herbivores and climate change on ecosystem C pools and soil respiration (Rs). Our results showed that grazing overrode global climate change factors in regulating grassland C storage and release (i.e., Rs). Specifically, grazing significantly decreased aboveground plant C pool (APCP), belowground plant C pool (BPCP), soil C pool (SCP), and Rs by 19.1%, 6.4%, 3.1%, and 4.6%, respectively, while overall effects of all global climate change factors increased APCP, BPCP and Rs by 6.5%, 15.3%, and 3.4% but had no significant effect on SCP. However, the combined effects of grazing with global climate change factors also significantly decreased APCP, SCP and Rs by 4.0%, 4.7% and 2.7%, respectively, but had no effect on BPCP. Most of the interactions between grazing and global climate change factors on APCP, BPCP, SCP and Rs were additive instead of synergistic or antagonistic. Our findings highlight the dominant effects of grazing on C storage and Rs when compared with the suite of global climate change factors. Therefore, incorporating the dominant effect of herbivore grazing into Earth System Models is necessary to accurately predict climate-grassland feedbacks in the Anthropocene. [ABSTRACT FROM AUTHOR]