Plant growth and aboveground production respond differently to late-season deluges in a semi-arid grassland

Signatures of autumn deluges revealed during spring drought in a semi-arid grassland

Increases in extremely large precipitation events (deluges) and shifts in seasonal patterns of water availability with climate change will both have important consequences for ecosystem function, particularly in water-limited regions. While previous work in the semi-arid shortgrass steppe of northeastern Colorado has demonstrated this ecosystem's strong sensitivity to growing season deluges, our understanding of ecosystem responses to deluges during the dormant season is limited. Here, we imposed experimental 100 mm deluges (~ 30% of mean annual precipitation) in either September or October in a native C4-dominated shortgrass steppe ecosystem to evaluate the impact of this post-growing season shift in water availability during the autumn and the following growing season. Soil moisture for both deluge treatments remained elevated compared with ambient levels through April as spring precipitation was atypically low. Despite overall low levels of productivity with spring drought, these deluges from the previous autumn increased aboveground net primary production (ANPP), primarily due to increases with C4 grasses. C3 ANPP was also enhanced, largely due to an increase in the annual C3 grass, Vulpia octoflora, in the October deluge treatment. While spring precipitation has historically been the primary determinant of ecosystem function in this ecosystem, this combination of two climate extremes-an extremely wet autumn followed by a naturally-occurring spring drought-revealed the potential for meaningful carryover effects from autumn precipitation. With climate change increasing the likelihood of extremes during all seasons, experiments which create novel climatic conditions can provide new insight into the dynamics of ecosystem functioning in the future.

Traits that distinguish dominant species across aridity gradients differ from those that respond to soil moisture

Many plant traits respond to changes in water availability and might be useful for understanding ecosystem properties such as net primary production (NPP). This is especially evident in grasslands where NPP is water-limited and primarily determined by the traits of dominant species. We measured root and shoot morphology, leaf hydraulic traits, and NPP of four dominant North American prairie grasses in response to four levels of soil moisture in a greenhouse experiment. We expected that traits of species from drier regions would be more responsive to reduced water availability and that this would make these species more resistant to low soil moisture than species from wetter regions. All four species grew taller, produced more biomass, and increased total root length in wetter treatments. Each species reduced its leaf turgor loss point (TLP) in drier conditions, but only two species (one xeric, one mesic) maintained leaf water potential above TLP. We identified a suite of traits that clearly distinguished species from one another, but, surprisingly, these traits were relatively unresponsive to reduced soil moisture. Specifically, more xeric species produced thinner roots with higher specific root length and had a lower root mass fraction. This suggest that root traits are critical for distinguishing species from one another but might not respond strongly to changing water availability, though this warrants further investigation in the field. Overall, we found that NPP of these dominant grass species responded similarly to varying levels of soil moisture despite differences in species morphology, physiology, and habitat of origin.

Predicting spatial-temporal patterns of diet quality and large herbivore performance using satellite time series

Adaptive management of large herbivores requires an understanding of how spatial-temporal fluctuations in forage biomass and quality influence animal performance. Advances in remote sensing have yielded information about the spatial-temporal dynamics of forage biomass, which in turn have informed rangeland management decisions such as stocking rate and paddock selection for free-ranging cattle. However, less is known about the spatial-temporal patterns of diet quality and their influence on large herbivore performance. This is due to infrequent concurrent ground observations of forage conditions with performance (e.g., mass gain), and previously limited satellite data at fine spatial and temporal scales. We combined multi-temporal field observations of diet quality (weekly) and mass gain (monthly) with satellite-derived phenological metrics (pseudo-daily, using data fusion and interpolation) to model daily mass gains of free-ranging yearling cattle in shortgrass steppe. We used this model to predict grazing season (mid-May to October) mass gains, a key management indicator, across 40 different paddocks grazed over a 10-year period (n = 138). We found strong relationships between diet quality and the satellite-derived phenological metrics, especially metrics related to the timing and rate of green-up and senescence. Satellite-derived diet quality estimates were strong predictors of monthly mass gains (R²  = 0.68) across a wide range of aboveground net herbaceous production. Season-long predictions of average daily gain and cattle off-mass had mean absolute errors of 8.9% and 2.9%, respectively. The model performed better temporally (across repeated observations in the same paddock) than spatially (across all paddocks within a given year), highlighting the need for accurate vegetation maps and robust field data collection across both space and time. This study demonstrates that free-ranging cattle performance in rangelands is strongly affected by diet quality, which is related to the timing of vegetation green-up and senescence. Senescing vegetation suppressed mass gains, even if adequate forage was available. The satellite-based pseudo-daily approach presented here offers new opportunities for adaptive management of large herbivores, such as identifying within-season triggers to move livestock among paddocks, predicting wildlife herd health, or timing the grazing season to better match earlier spring green-up caused by climate change and plant species invasion.

Error Propagation in Microwave Soil Moisture and Vegetation Optical Depth Retrievals

Satellite soil moisture and vegetation optical depth [(VOD); related to the total vegetation water mass per unit area] are increasingly being used to study water relations in the soil-plant continuum across the globe. However, soil moisture and VOD are typically jointly estimated, where errors in the optimization approach can cause compensation between both variables and confound such studies. It is thus critical to quantify how satellite microwave measurement errors propagate into soil moisture and VOD. Such a study is especially important for VOD given limited investigations of whether VOD reflects in situ plant physiology. Furthermore, despite new approaches that constrain (or regularize) VOD dynamics to reduce soil moisture errors, there is limited study of whether regularization reduces VOD errors without obscuring true vegetation temporal dynamics. Here, we find that, across the globe, VOD is less robust to measurement error (more difficult for optimization methods to find the true solution) than soil moisture in their joint estimation. However, a moderate degree of regularization (via time-constrained VOD) reduces errors in VOD to a greater degree than soil moisture and reduces spurious soil moisture-VOD coupling. Furthermore, despite constraining VOD time dynamics, regularized VOD variations on subweekly scales are both closer to simulated true VOD time series and have global VOD post-rainfall responses with reduced error signatures compared to VOD retrievals without regularization. Ultimately, we recommend moderately regularized VOD for use in large scale studies of soil-plant water relations because it suppresses noise and spurious soil moisture-VOD coupling without removing the physical signal.

Semiarid grasslands and extreme precipitation events: do experimental results scale to the landscape?

The frequency and magnitude of deluges (extremely large rain events) are increasing globally as the atmosphere warms. Small-scale experiments suggest that semiarid grasslands are particularly sensitive to both the timing and size of deluge events. However, the assumption that plot-scale results can be extrapolated across landscapes with variable soil textures, plant communities, and grazing regimes has seldom been tested, despite being key to forecasting regional consequences of precipitation extremes. We used precipitation data from an extensive rain gauge network to identify natural deluges (mean size = 60 ± 31 mm, 1984-2012) that occurred across a ˜60-km² heterogeneous native shortgrass steppe landscape in Colorado. We then related spatial variation in deluge precipitation to postdeluge responses in canopy greenness (normalized difference vegetation index, NDVI) via satellite imagery. Consistent with results from experiments, this semiarid grassland was most sensitive to mid-growing-season deluges, and postdeluge canopy greenness usually increased linearly (67% of the time) with increasing deluge size. This suggests that aboveground productivity in these semiarid systems will likely increase, rather than asymptote, with forecasted increases in deluge size. Importantly, differences in grazing regime did not significantly alter deluge responses, indicating that these patterns are robust to this widespread management practice.

How big is big enough? Surprising responses of a semiarid grassland to increasing deluge size

Climate change has intensified the hydrologic cycle globally, increasing the magnitude and frequency of large precipitation events, or deluges. Dryland ecosystems are expected to be particularly responsive to increases in deluge size, as their ecological processes are largely dependent on distinct soil moisture pulses. To better understand how increasing deluge size will affect ecosystem function, we conducted a field experiment in a native semiarid shortgrass steppe (Colorado, USA). We quantified ecological responses to a range of deluge sizes, from moderate to extreme, with the goal of identifying response patterns and thresholds beyond which ecological processes would not increase further (saturate). Using a replicated regression approach, we imposed single deluges that ranged in size from 20 to 120 mm (82.3rd to >99.9th percentile of historical event size) on undisturbed grassland plots. We quantified pre- and postdeluge responses in soil moisture, soil respiration, and canopy greenness, as well as leaf water potential, growth, and flowering of the dominant grass species (Bouteloua gracilis). We also measured end of season above- and belowground net primary production (ANPP, BNPP). As expected, this water-limited ecosystem responded strongly to the applied deluges, but surprisingly, most variables increased linearly with deluge size. We found little evidence for response thresholds within the range of deluge sizes imposed, at least during this dry year. Instead, response patterns reflected the linear increase in the duration of elevated soil moisture (2-22 days) with increasing event size. Flowering of B. gracilis and soil respiration responded particularly strongly to deluge size (14- and 4-fold increases, respectively), as did ANPP and BNPP (~60% increase for both). Overall, our results suggest that this semiarid grassland will respond positively and linearly to predicted increases in deluge size, and that event sizes may need to exceed historical magnitudes, or occur during wet years, before responses saturate.

Effects of Water Addition on Reproductive Allocation of Dominant Plant Species in Inner Mongolia Steppe

Extreme events such as extreme drought and precipitation are expected to increase in intensity and/or duration in the face of climate change. Such changes significantly affect plant productivity and the biomass allocation between reproductive and vegetation organs (i.e., reproductive allocation). Our aims are to test the effects of water addition on the trade-offs in allocation of plant biomass and whether such effects are modified by species. A manipulative experiment was conducted from May 2000 to October 2001, where four dominant plant species (i.e., Leymus chinensis, Stipa grandis, Artemisia frigida, and Potentilla acaulis) in the Inner Mongolia steppe in China were treated with 8 levels of water addition. Results demonstrated that water addition significantly affected the reproductive allocation of plants, and such effects were modified by species. Specifically, with increasing water availability, L. chinensis was not impacted, while A. frigida allocated more biomass to reproductive organs than to vegetative organs, while such allocation in S. grandis and P. acaulis first decreased, and then increased after reaching a peak. Our results indicated that plant species can adjust their reproductive allocation patterns to deal with water availability gradients. Climatic factors such as rainfall and temperature usually co-appearing, thus future research should explore the joint effects of several climate change factors on grasslands in order to maintain the health and sustainability of grasslands.