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Seasonality of soil moisture mediates responses of ecosystem phenology to elevated CO2 and warming in a semi-arid grassland
Journal of Ecology
Abstract
Vegetation greenness, detected using digital photography, is useful for monitoring phenology of plant growth, carbon uptake and water loss at the ecosystem level. Assessing ecosystem phenology by greenness is especially useful in spatially extensive, water‐limited ecosystems such as the grasslands of the western United States, where productivity is moisture dependent and may become increasingly vulnerable to future climate change.
We used repeat photography and a novel means of quantifying greenness in digital photographs to assess how the individual and combined effects of warming and elevated CO 2 impact ecosystem phenology (greenness and plant cover) in a semi‐arid grassland over an 8‐year period.
Climate variability within and among years was the proximate driver of ecosystem phenology. Individual and combined effects of warming and elevated CO 2 were significant at times, but mediated by variation in both intra‐ and interannual precipitation. Specifically, warming generally enhanced plant cover and greenness early in the growing season but often had a negative effect during the middle of the summer, offsetting the early season positive effects. The individual effects of elevated CO 2 on plant cover and greenness were generally neutral.
Opposing seasonal variations in the effects of warming and less so elevated CO 2 cancelled each other out over an entire growing season, leading to no net effect of treatments on annual accumulation of greenness. The main effect of elevated CO 2 dampened quickly, but warming continued to affect plant cover and plot greenness throughout the experiment. The combination of warming and elevated CO 2 had a generally positive effect on greenness, especially early in the growing season and in later years of the experiment, enhanced annual greenness accumulation. However, interannual precipitation variation had larger effect on greenness, with two to three times greater greenness in wet years than in dry years.
Synthesis . Seasonal variation in timing and amount of precipitation governs grassland phenology, greenness and the potential for carbon uptake. Our results indicate that concurrent changes in precipitation regimes mediate vegetation responses to warming and elevated atmospheric CO 2 in semi‐arid grasslands. Even small changes in vegetation phenology and greenness in response to warming and rising atmospheric CO 2 concentrations, such as those we report here, can have large consequences for the future of grasslands.
... The greenness indices derived from RGB images have been widely used to monitor the vegetation dynamics, such as plant development and phenology (Jorge et al., 2021;Kurc & Benton, 2010;Zelikova et al., 2015). These indices allow for the evaluation of net or gross carbon uptake, as the timing of annual photosynthetic activity and carbon absorption correlates directly with vegetation greenness (Piao et al., 2006). ...
... Alterations in vegetation greenness serve as a close approximation of the impacts of climate change on carbon uptake (Kurc & Benton, 2010). Vegetation greenness also proves valuable in monitoring ecosystem-level water loss (Zelikova et al., 2015). Several studies have demonstrated the utility of canopy greenness in quantifying in both GPP and the length of the photosynthetically active period in forests and grasslands (Toomey et al., 2015;Yan et al., 2019). ...
... Several studies have demonstrated the utility of canopy greenness in quantifying in both GPP and the length of the photosynthetically active period in forests and grasslands (Toomey et al., 2015;Yan et al., 2019). Variations in seasonal precipitation patterns govern the greenness of grasslands, and even subtle shifts due to climatic change can yield significant implications for their future (Zelikova et al., 2015). ...
Biocrusts are common living covers found across drylands worldwide, and their photosynthesis substantially contributes to carbon input in these ecosystems. However, direct monitoring of biocrusts’ photosynthetic carbon fixation is challenging due to their scattered distribution, dark pigments, and lower CO2 exchange rate. Current studies have limited monitoring frequency and the results are difficult to extend to a broader spatial scale. Greenness typically functions as an indicator of both vegetation cover and plant photosynthesis. Monitoring biocrust greenness is expected to be able to provide insights into their environmental responses and estimate carbon fixation rates, particularly for moss biocrusts. Here, we monitored greenness, soil moisture and temperature, and gross primary productivity (GPP) of moss biocrusts, as well as climatic factors over two years in the northern China’s Loess Plateau. The results indicated that moss biocrust greenness was highly sensitive to changing environmental conditions and exhibited significant temporal variability. Moss biocrust greenness exhibited a notably higher value in wet season (0.384) than in dry season (0.259). According to these greenness values, we proposed moss biocrust activity and classified it into high (>0.403), medium (0.334–0.403), low (0.271–0.333), and dormancy (<0.270). Soil moisture, relative humidity, and wind speed were the three main determinates of moss biocrust greenness. Higher soil moisture and relative humidity were linked to increased greenness, whereas elevated wind speed led to a reduction. In dry seasons, soil moisture contributed 23.4 % to the variation in moss biocrust greenness, while in wet seasons relative humidity contributed 16.1 %. A significant and positive correlation between moss biocrust greenness and GPP was found, and annual GPP prediction based on greenness using machine learning performed well. Our study highlights the significance of moss biocrust greenness and their potential as indicators for moss biocrust photosynthetic carbon fixation rates and possibly other ecological functions in drylands.
... Additionally, indirect effects of phenology on reproduction may occur when altered reproductive phenology influences the duration of a phenological event, which can also affect the number of flowers or fruits produced, as a longer flowering period might provide more opportunities for plants to reproduce (Dieringer, 1991;Nagahama et al., 2018). Most studies examining the effects of climate change on plant phenology have focused on climate warming Knapp & Smith, 2001;Cleland et al., 2012;Zelikova et al., 2015), but in many ecosystems precipitation is also likely to be a dominant factor. For example, precipitation is the primary driver shaping vegetation dynamics in grasslands due to the water-limited nature of this ecosystem, and seasonal variation in the timing and amount of precipitation appears to affect phenology (Knapp et al., 2008(Knapp et al., , 2020Zelikova et al., 2015). ...
... Most studies examining the effects of climate change on plant phenology have focused on climate warming Knapp & Smith, 2001;Cleland et al., 2012;Zelikova et al., 2015), but in many ecosystems precipitation is also likely to be a dominant factor. For example, precipitation is the primary driver shaping vegetation dynamics in grasslands due to the water-limited nature of this ecosystem, and seasonal variation in the timing and amount of precipitation appears to affect phenology (Knapp et al., 2008(Knapp et al., , 2020Zelikova et al., 2015). Therefore, the effects of altered precipitation on plant phenology deserve greater consideration, and precipitation is likely to affect species differently depending on their sensitivity to soil moisture (Cleland et al., 2006). ...
... As a result, altered precipitation can aggravate water stress for plant communities in an already watersensitive ecosystem. Even small shifts in phenology can disrupt phenological complementarity among species, with potentially large consequences for the future of grasslands (Cleland et al., 2006;Zelikova et al., 2015). Changes in grassland plant phenology have considerable implications for plant-pollinator interactions, herbivory, productivity, and carbon and energy balances (Beard et al., 2019). ...
Shifts in flowering phenology are important indicators of climate change. However, the role of precipitation in driving phenology is far less understood compared with other environmental cues, such as temperature.
We use a precipitation reduction gradient to test the direction and magnitude of effects on reproductive phenology and reproduction across 11 plant species in a temperate grassland, a moisture‐limited ecosystem. Our experiment was conducted in a single, relatively wet year. We examine the effects of precipitation for species, functional types, and the community.
Our results provide evidence that reduced precipitation shifts phenology, alters flower and fruit production, and that the magnitude and direction of the responses depend on functional type and species. For example, early‐blooming species shift toward earlier flowering, whereas later‐blooming species shift toward later flowering. Because of opposing species‐level shifts, there is no overall shift in community‐level phenology.
This study provides experimental evidence that changes in rainfall can drive phenological shifts. Our results additionally highlight the importance of understanding how plant functional types govern responses to changing climate conditions, which is relevant for forecasting phenology and community‐level changes. Specifically, the implications of divergent phenological shifts between early‑ and late‐flowering species include resource scarcity for pollinators and seed dispersers and new temporal windows for invasion.
... Panel (a) shows the daily trajectory of soil moisture prior to and between sampling events for leaf water potential, which occurred on day of year (DOY) 164 and 191 (dashed vertical lines). Weekly to biweekly measures of plot greenness are also shown in panel (a) using larger, open symbols (Zelikova et al., 2015). Panel (b) shows mean soil moisture integrated over two different time periods relevant to plant sampling. ...
... During the sampling period, leaf senescence was evident for many but not all individuals of Carex duriuscula, and for some but not most individuals of the other four species. Above-ground biomass and greenness were lower in the sampling year (2013) than in any prior year of the experiment, reflecting the effect of two consecutive growing-seasons with low precipitation and soil moisture (Mueller et al., 2016;Zelikova et al., 2015). obtaining complete pressure-volume curves for every plot sometimes required a second or third sampling (e.g., due to leaf breakage from repeated Ψ measurements). ...
... loss point and osmotic potential was not correlated with variability in soil moisture among plots (p > .2); this relationship was assessed for mean soil moisture integrated over three time intervals of different length, all preceding leaf sampling (DOY 100 to 160, DOY 100 to 148, and DOY 117 to 148; for reference, greenness of ground cover did not exceed 10% until after DOY 117 and peak greenness was observed at DOY 148 [Zelikova et al., 2015]). Thus, as for leaf Ψ pd , the effects of eCO 2 on leaf turgor loss point and osmotic potential remained apparent and species specific when soil moisture was included as a covariate (Table S1). ...
The effects of climate change on plants and ecosystems are mediated by plant hydraulic traits, including interspecific and intraspecific variability of trait phenotypes. Yet, integrative and realistic studies of hydraulic traits and climate change are rare. In a semiarid grassland, we assessed the response of several plant hydraulic traits to elevated CO2 (+200 ppm) and warming (+1.5 to 3°C; day to night). For leaves of five dominant species (three graminoids, two forbs), and in replicated plots exposed to seven years of elevated CO2, warming, or ambient climate, we measured: stomatal density and size, xylem vessel size, turgor loss point, and water potential (pre‐dawn). Interspecific differences in hydraulic traits were larger than intraspecific shifts induced by elevated CO2 and/or warming. Effects of elevated CO2 were greater than effects of warming, and interactions between treatments were weak or not detected. The forbs showed little phenotypic plasticity. The graminoids had leaf water potentials and turgor loss points that were 10 to 50% less negative under elevated CO2; thus, climate change might cause these species to adjust their drought resistance strategy away from tolerance and toward avoidance. The C4 grass also reduced allocation of leaf area to stomata under elevated CO2, which helps explain observations of higher soil moisture. The shifts in hydraulic traits under elevated CO2 were not, however, simply due to higher soil moisture. Integration of our results with others’ indicates that common species in this grassland are more likely to adjust stomatal aperture in response to near‐term climate change, rather than anatomical traits; this contrasts with apparent effects of changing CO2 on plant anatomy over evolutionary time. Future studies should assess how plant responses to drought may be constrained by the apparent shift from tolerance (via low turgor loss point) to avoidance (via stomatal regulation and/or access to deeper soil moisture).
... If moisture is not limiting, carbon storage can increase significantly in response to warmer conditions and rising atmospheric CO 2 (see Section 10.3.3, p. 410). In part, this increase results from flexible timing of grassland plant growth and photosynthesis (Ryan et al., 2016;Zelikova et al., 2015). For example, drought decreased the growing season length and led to reductions in NPP and carbon sequestration in the Canadian Great Plains (Flanagan and Adkinson 2011). ...
... The lengthening of the growing season was dependent on a mix of C 3 and C 4 species adapted to different climate conditions. In the same experiment, greenness was enhanced (i.e., indicating increased aboveground biomass and cover) with warming and elevated CO 2 , but the effects of seasonal and interannual rainfall variability were much stronger (Zelikova et al., 2015). High-precipitation years had two to three times greater vegetation greenness than dry years. ...
... Plant nutrient uptake can decrease soil nutrients, which may be made available during SOM decomposition. [Figure conceptionderived from numerous studies, includingHufkens et al., 2016;Morgan et al., 2011; Mueller et al., 2016;Reich and Hobbie 2013;Reyes-Fox et al., 2014;and Zelikova et al., 2015.] U.S. Global Change Research Program November 2018 ...
... weeks) (Migliavacca et al., 2011;Morgan et al., 2004;Pathare et al., 2017). Consequently, high-frequency measures of ecosystem productivity are required to adequately capture climate and eCO 2 effects on grassland productivity (Migliavacca et al., 2011;Zelikova et al., 2015), and will provide greater value for the development and testing of process-based ecosystem models (Hufkens et al., 2016). Near-surface remote sensing using time-lapse digital photography provides an ideal tool for the quantification of trends in grassland growth at fine temporal scales (Hufkens et al., 2016;Migliavacca et al., 2011;Zelikova et al., 2015). ...
... Consequently, high-frequency measures of ecosystem productivity are required to adequately capture climate and eCO 2 effects on grassland productivity (Migliavacca et al., 2011;Zelikova et al., 2015), and will provide greater value for the development and testing of process-based ecosystem models (Hufkens et al., 2016). Near-surface remote sensing using time-lapse digital photography provides an ideal tool for the quantification of trends in grassland growth at fine temporal scales (Hufkens et al., 2016;Migliavacca et al., 2011;Zelikova et al., 2015). Greenness indices derived from digital photographs are highly correlated with projected foliage cover and gross primary productivity in grasslands (Hufkens et al., 2016;Migliavacca et al., 2011;Moore et al., 2016;Toomey et al., 2015;Zelikova et al., 2015). ...
... Near-surface remote sensing using time-lapse digital photography provides an ideal tool for the quantification of trends in grassland growth at fine temporal scales (Hufkens et al., 2016;Migliavacca et al., 2011;Zelikova et al., 2015). Greenness indices derived from digital photographs are highly correlated with projected foliage cover and gross primary productivity in grasslands (Hufkens et al., 2016;Migliavacca et al., 2011;Moore et al., 2016;Toomey et al., 2015;Zelikova et al., 2015). Stereo imaging techniques are also effective at characterising vegetation structure and can provide estimates of vegetation biomass (Yoon & Thai, 2010). ...
Rising atmospheric [CO2] and associated climate change are expected to modify primary productivity across a range of ecosystems globally. Increasing aridity is predicted to reduce grassland productivity, though rising [CO2] and associated increases in plant water use efficiency may partially offset the effect of drying on growth. Difficulties arise in predicting the direction and magnitude of future changes in ecosystem productivity, due to limited field experimentation investigating climate and CO2 interactions. We use repeat near-surface digital photography to quantify the effects of water availability and experimentally manipulated elevated [CO2] (eCO2) on understorey live foliage cover and biomass over three growing seasons in a temperate grassy woodland in south-eastern Australia. We hypothesised that (i) understorey herbaceous productivity is dependent upon soil water availability, and (ii) that eCO2 will increase productivity, with greatest stimulation occurring under conditions of low water availability. Soil volumetric water content (VWC) determined foliage cover and growth rates over the length of the growing season (August - March), with low VWC (< 0.1 m³ m⁻³) reducing productivity. However, eCO2 did not increase herbaceous cover and biomass over the duration of the experiment, or mitigate the effects of low water availability on understorey growth rates and cover. Our findings suggest that projected increases in aridity in temperate woodlands are likely to lead to reduced understorey productivity, with little scope for eCO2 to offset these changes.
... In some cases, seasonal timing of extreme drought is a better predictor of ecosystem CO 2 flux responses than drought magnitude Powell et al., 2013). While seasonal shifts in the degree and timing of drought directly affect ecosystem CO 2 fluxes Li, Zuo, et al., 2021;Zelikova et al., 2015), such shifts can also indirectly but strongly drive ecosystem CO 2 fluxes responses via effects on plant community composition (Hao et al., 2018;Kuiper et al., 2014;Pastore et al., 2020). Thus, a better understanding of drought's effects with different seasonal timing on multiple plant community compositions and, consequently, ecosystem CO 2 fluxes is necessary for more accurate predictions of the future climate-C cycle. ...
... plant community or climate condition). Specifically, water availability during particular windows of time may affect ecosystem CO 2 fluxes, as well as when peak ecosystem CO 2 flux occurs and how long it lasts (Zelikova et al., 2015). Droughts occurring in spring or early-growing season, the green-up period of the majority of species, may suppress ecosystem CO 2 fluxes mainly by delaying green-up date and inhibiting canopy development (Ciais et al., 2005;Misson et al., 2011). ...
Droughts can affect ecosystem CO2 fluxes directly or indirectly by changing plant community composition. However, it is unknown whether shifts in plant community composition buffer or amplify the response of ecosystem CO2 fluxes to droughts with different seasonal timing, as plant phenology and physiology of the different plant functional types respond differently to droughts.
To identify the interaction of drought timing and plant community composition in regulating ecosystem CO2 fluxes, we conducted a three‐year manipulative experiment in which extreme droughts occurring in the early, mid and late growing seasons were separately imposed on experimental plot communities comprising graminoids, shrubs and their combination in a semi‐arid grassland of Inner Mongolia, China.
Overall, mid‐season drought caused the largest negative effects regardless of plant community composition. In addition to decreasing aboveground biomass, mid‐season drought suppressed fluxes by reducing leaf photosynthetic rate, while early‐season and late‐season drought reduced fluxes mainly by shortening growing season length. All three community compositions had consistent responses to early‐season and mid‐season droughts. However, ecosystem CO2 fluxes in the combination community were less negatively affected by late‐season drought than in either shrub or graminoid communities because the growing season length was shortened less.
Synthesis. Our results highlight that it is important to account for interactions of seasonal timing and plant community composition when predicting magnitude and pathways of drought effects on ecosystem carbon cycling.
... Agriculture processes like soil moisture change and crop growth development were replicated in dynamic variation. This is especially significant for showing the coevolution of soil moisture and crop growth within irrigated agricultural fields and identifying the critical events and stages of crop growth, as they affect the timing and scheduling of management inputs [35]. Various surface conditions (e.g., irrigated and non-irrigated, bare and vegetated) can be distinguished using dynamic STR-NDVI spaces, and vital agronomic events and crop growth stages (e.g., start and halt of irrigation, crop emergence and maturity, and harvesting time) can be identified. ...
... The use of remote sensing and ancillary data for identifying and quantifying irrigation patterns has been the subject of numerous research efforts over the past few decades [2,[35][36][37][38]. Most of these studies focus on parametric and nonparametric statistical techniques, which require long, complicated training processes and may have limited generalisation. ...
This study extensively examines the estimation of irrigation water requirements using different methodologies based on Earth Observation data. Specifically, two distinct methods inspired by recent remote sensing and satellite technology developments are examined and compared. The first methodology, as outlined by Maselli et al. (2020), focuses on using Sentinel-2 MSI data and a water stress scalar to estimate the levels of actual evapotranspiration and net irrigation water (NIW). The second methodology derives from the work of D’Urso et al. (2021), which includes the application of the Penman–Monteith equation in conjunction with Sentinel-2 data for estimating key parameters, such as crop evapotranspiration and NIW. In the context of the Bekaa Valley in Lebanon, this study explores the suitability of both methodologies for irrigated potato crops (nine potato fields for the early season and eight for the late season). The obtained NIW value was compared with measured field data, and the root mean square errors were calculated. The results of the comparison showed that the effectiveness of these methods varies depending on the growing season. Notably, the Maselli method exhibited better performance during the late season, while the D’Urso method proved more accurate during the early season. This comparative assessment provided valuable insights for effective agricultural water management in the Bekaa Valley when estimating NIW in potato cultivation.
... Phenology is the timing of periodic biological events of plants, and it is an important indicator of ecosystem dynamics, determining to a large extent community productivity and providing insight into species distribution (Estiarte and Peñuelas, 2015;Zelikova et al., 2015;Li et al., 2016a;Zhou et al., 2016). As globally widespread ecosystems (Ren et al., 2019), grasslands provide critical ecosystem functions and services (Smith and Knapp, 2003); understanding how climate change may shift the phenology of these ecosystems will be critical for predicting future functions. ...
... Consistent with previous results in this study area, increased late growing season precipitation weakened the effects of water deficit on the plant photosynthetic efficiency, reduced leaf senescence, extended the growing season length, and increased the above-ground biomass (Liu et al., 2016;Ren et al., 2019). Intra-annual precipitation patterns determine the availability of soil moisture at critical plant growth stages, suggesting that soil moisture at specific times may have outsized impacts on the annual above-ground biomass Preveý and Seastedt, 2014;Zelikova et al., 2015;Wang et al., 2019). Whether these additional water additions increase biomass by causing different dominant species root growth, higher mineralization, or just by an increase in diffusive nitrogen transport through the large amount of water in the soil pore, given the tight coupling of water and nitrogen availability (Fanselow et al., 2011;Gong et al., 2011), is unclear from this study. ...
Phenology and productivity are important functional indicators of grassland ecosystems. However, our understanding of how intra-annual precipitation patterns affect plant phenology and productivity in grasslands is still limited. Here, we conducted a two-year precipitation manipulation experiment to explore the responses of plant phenology and productivity to intra-annual precipitation patterns at the community and dominant species levels in a temperate grassland. We found that increased early growing season precipitation enhanced the above-ground biomass of the dominant rhizome grass, Leymus chinensis, by advancing its flowering date, while increased late growing season precipitation increased the above-ground biomass of the dominant bunchgrass, Stipa grandis, by delaying senescence. The complementary effects in phenology and biomass of the dominant species, L. chinensis and S. grandis, maintained stable dynamics of the community above-ground biomass under intra-annual precipitation pattern variations. Our results highlight the critical role that intra-annual precipitation and soil moisture patterns play in the phenology of temperate grasslands. By understanding the response of phenology to intra-annual precipitation patterns, we can more accurately predict the productivity of temperate grasslands under future climate change.
... NEP max is the maximum value of daily NEP during the whole growing season. Fu et al., 2017;Liu et al., 2021a;Zelikova et al., 2015;Zhang et al., 2021). In this study, we found NEP max was positively correlated with SWC sp and SWC wheat for the wheat season, and SWC significantly correlated with NEP max of wheat. ...
... According to various responses of maize ecosystem carbon balance to environmental changes in the different phenological phases , agroecosystems were more significantly impacted by changes in temperature and mid-month precipitation during the growing season than grassland ecosystems (Du et al., 2019). Seasonality of soil moisture mediated vegetation phenology and carbon uptake capacity in water-limited ecosystem (Zelikova et al., 2015). The IAV of NEP was thus more sensitive to changes in seasonal precipitation and SWC under climate change conditions . ...
Investigating the response of net ecosystem productivity (NEP) to phenological variation for crop ecosystems is important for deeply understanding the impact of climate change on agriculture. However, its main controlling mechanisms have not been well understood for rotation cropland ecosystems. Using a 16 year (2003-2018) eddy covariance flux observation in a typical wheat-maize rotation system in the North China Plain (NCP), we explore the potential of carbon flux phenology (CFP) and abiotic factors in interpreting the interannual variability (IAV) of NEP. The results showed that the NEP of the wheat season (NEP wheat) was significantly controlled by the carbon uptake period (CUP), the end date of CUP (ECUP) and the peak value of NEP (NEP max). The increase in spring temperature reduced soil water content (SWC) in the wheat season, leading to shorter CUP, earlier ECUP and lower NEP max. However, NEP of the maize season (NEP maize) was mainly affected by CUP, the start date of CUP (SCUP) and NEP max. ECUP and CUP were negatively correlated with air temperature (T a) and soil temperature (T s) of the maize season, and NEP max had a significant negative correlation with mean summer temperature (MT su) and T a. In addition, we found that NEP max contributed the most to the IAV of NEP wheat (63%). However, CUP showed the most contributions in maize ecosystems, interpreting 30% IAV of NEP maize. When considering the export of harvested biomass, the wheat season carbon budgets were close to neutral of 21±26 g C m − 2 , the maize season was a carbon source of 102±18 g C m − 2 , and the whole year behaved as a carbon source of 129±41 g C m − 2 during our study period. The study provides important insights into the response of carbon budget of cropland ecosystems to vegetation phenology shifts in the North China Plain under future climate change.
... Thus, intra-annual precipitation patterns-not only how much precipitation occurs, but when-may predict within-site productivity responses better than total annual precipitation alone (Knapp et al., 2002(Knapp et al., , 2008. While seasonal swings in the timing and amount of precipitation directly affect the timing of plant production (e.g., phenology, Zelikova et al., 2015), such swings can also indirectly drive production responses via effects on plant community composition (Suttle et al., 2007). As substantial shifts in precipitation regimes including increased seasonal rainfall variability and the frequency of extreme events such as severe storms and droughts is expected globally (Groisman et al., 2012;IPCC, 2007;Tebaldi et al., 2006), a better understanding of intra-annual precipitation's effects on phenology, community composition and, consequently, withinsite productivity is needed. ...
... Intra-annual precipitation patterns directly determine soil water availability to plants during key growth stages, affecting ecosystem productivity in ways not reflected by total annual precipitation (Knapp et al., 2008). Specifically, water availability during particular windows of time may affect annual net primary productivity (ANPP; Epstein et al., 1999), as well as when peak productivity occurs and how long it lasts (Zelikova et al., 2015). For example, early growing season precipitation impacts ANPP (Chelli et al., 2016;Craine et al., 2012;Hossain & Beierkuhnlein, 2018) due to the critical need for water to initiate and support early growth. ...
Within ecosystems, intra‐annual precipitation patterns—the variability and timing of rainfall—may be a stronger driver of net primary productivity than total annual precipitation. In particular, the amount and timing of precipitation directly affects the amount and timing of plant production, but also indirectly affects productivity via changes to plant community composition. Community response patterns may either buffer or amplify productivity responses to precipitation, as different species respond to different conditions.
In a semi‐arid California grassland, we experimentally tested how plant communities respond to intra‐annual precipitation using rainout shelters in which we manipulated drought amount and timing (early season drought, late season drought, continuous drought and ambient precipitation) over 3 years and assessed plant responses: annual net primary productivity (ANPP), phenological timing of peak production and senescence, and community composition.
Overall, early season and consistent drought treatments had lowest productivity, while late season and consistent drought treatments senesced earlier. Plots with functionally diverse communities shifted community composition and had a significant ANPP response to precipitation treatments. In contrast, communities dominated by a single resource‐acquisitive grass species did not change in community composition over time and had no ANPP response to precipitation treatments.
The timing of production also differed by community, however, where functionally diverse communities remained green longer (particularly under the early season drought treatment) compared to communities dominated by one grass species, which senesced earlier (particularly under the late season drought treatment).
Synthesis. Our study demonstrates that drought patterns may indirectly drive ANPP via plant community responses in composition and phenology. This suggests that the combination of species composition and vegetation phenology could jointly alter ecosystem‐level sensitivity to precipitation seasonality under future climate change. We show that both functional diversity and dominant stability mechanisms are in operation simultaneously, highlighting the need to understand both the context and variation in community structure to predict ANPP responses to intra‐annual precipitation.
... However, in a semiarid creosote shrubland in Arizona, an index derived from phenocam data tracked the "green-up" of the evergreen vegetation, showing good agreement with increases in the net ecosystem exchange (NEE) of CO 2 (Kurc & Benton, 2010). Also, Zelikova et al. (2015) found significant associations between an index of the "greening" of vegetation and total biomass in a temperature and CO 2 enrichment experiment in a C3-dominated prairie in Wyoming. Thus, information produced by phenocams can be used as an input for process-based models to estimate gross primary productivity (GPP). ...
... We found a moderate agreement between the Ig and GPP EC (Figure 2c), supporting the trend to apply a vegetation index from RGB intensities of repeat digital photographs as a proxy to monitor the timing and level of primary production. This proxy has been tested in various temperate ecosystems, some with noticeable changes in leaf coloration and defoliation, but there are few examples of this application of phenocams in drylands (Kurc & Benton, 2010;Moore et al., 2017;Zelikova et al., 2015). Phenocams are a feasible technology for terrestrial monitoring of vegetation despite the logistical challenges of drylands (Browning et al., 2017). ...
Although drylands cover >40% of the land surface, models of ecosystem gross primary productivity (GPP) generally have been designed for mesic temperate ecosystems. Arguably, GPP models often lack a good representation of vegetation phenology, particularly not estimating the ecosystem effects of the prolonged foliage senescence which may be common in drylands. To estimate daily GPP for a water‐limited Mediterranean shrubland, we propose a simple framework (GPPmod) using light use efficiency, a spectral vegetation index derived from digital cameras, and five meteorological variables, including an index of functional senescence of foliage (i.e., heat degree‐days). We tested the model with different combinations of meteorological variables but without senescence, using 1 year's data. The best formulation showed good agreement with GPP derived from eddy covariance (GPPEC; r² = 0.53, RMSE = 0.77). However, including the foliage senescence parameter significantly improved model performance (r² = 0.74, RMSE = 0.49), especially during the fall season. In the following year, we validated the parameters: The overall GPPmod and GPPEC comparison yielded an r² = 0.78. We postulate that models that mainly rely on meteorological variables or greenness indices could yield an overestimation of annual GPP between 24% and 90%, while models including the foliage senescence parameter reduced that bias by 10% to 34%. Our results highlight the importance of incorporating the phenology of foliage senescence in models regarding productivity in drylands or dry sclerophyll ecosystems.
... In alpine tundra, forbs responded to warming by flowering earlier and responded to increase snowpack and nitrogen addition by flowering later, but interactions of warming, snowpack and nitrogen addition advanced flowering (Smith et al., 2012). Commonly, in sub-arid grasslands, interannual variation in precipitation controls the direction of warming effects (delay or advance) on plant phenology (Zelikova et al., 2015). ...
... Hence, preseason water availability is an important factor regulating the warming effects on plant phenology. In the USA, field experiment has showed that seasonal variation in the timing and amount of precipitation governs grassland green up of great plain ecosystems (Zelikova et al., 2015). After conducting three years of year-round warming and spring precipitation addition experiment, we found that warming delayed plant green up and flowering in a warm and dry year (2016) while advanced plant green up in a cold and wet year (2015). ...
Temperature and precipitation are primary regulators of plant phenology. However, our knowledge of how these factors might interact to affect plant phenology is incomplete. The Qinghai-Tibetan Plateau, a cold and high region, has experienced no consistent changes in spring phenology, despite a significant warming trend. We conducted a manipulative experiment of warming and precipitation addition in an alpine meadow on the Qinghai-Tibetan Plateau in 2015 (cold and wet), 2016 (warm and dry) and 2017 (mild and very wet). We found that warming increased annual variability of plant spring phenology. Warming delayed green up of all monitored species in 2016, advanced green up of early flowering species in 2015, and did not alter green up in 2017. For example, green up of the shallow rooted Kobresia pygmaea advanced 8 (± 2) days in 2015 and was delayed by 23 (± 3) days in a dry year (2016) under warming compared with control. Early spring precipitation addition can offset the delaying effects of warming in a dry year on the Qinghai-Tibetan Plateau. Under warming plus precipitation addition, community average green up advanced compared to control plots in 2015 and 2016, and community average flowering advanced for all three years. In 2016, flowering of K. pygmaea (an early flowering species) advanced under warming plus precipitation addition compared to control while flowering of other species did not change. Our results highlight that annual variation of soil moisture condition plays a critical role in determining the magnitude and direction of spring phenology response to warming. We provide insights in how plant spring phenology might change in a warmer future in the presence or absence of precipitation increase .
... Compared with precipitation, soil moisture was a more straightforward index affecting grassland phenology, because it directly reflects the available water for plant seeds and roots (Yuan et al. 2007;Liu et al. 2013). The soil moisture also mediated the phenological response of grass to warming in a semi-arid grassland (Zelikova et al. 2015). ...
... The onset of spring and subsequent seasonal patterns of plant growth depended on both soil temperature and soil moisture in a semi-arid steppe in the western Great Plains of the USA (Moore et al. 2015). Similarly, soil moisture influenced the phenology of grasslands both directly (greenness was two to three times greater in wet years than in dry years) and indirectly by mediating the magnitude and direction of warming effects (Zelikova et al. 2015). In the Canadian Prairies, fewer water deficits favored an earlier start date of the growing season . ...
Investigating grassland phenology and its relationship with climatic factors is crucial for understanding ecosystem responses to climate change. However, there have been few studies on the impact of soil moisture on grassland phenology. In this study, we extracted the green-up date in the Inner Mongolia grasslands, China, using the normalized difference vegetation index (NDVI) data from the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g dataset (1982–2015) and the Moderate Resolution Imaging Spectroradiometer (2001–2015). We investigated the spatiotemporal pattern of the green-up date and its relationship with four climatic factors, including growing degree days, chilling days, soil moisture, and solar radiation. Most areas (67.1%) exhibited a trend towards earlier green-up date, but the significant trends (p < 0.05) were only found in 13.4% of the areas. For both datasets, the pixels with a negative regression coefficient of soil moisture accounted for more than 87% of the total area (more than 21% significantly, p < 0.05). Regarding the other factors, the sign of regression coefficients was not consistent among pixels. Thus, soil moisture correlated more significantly with the green-up date in temperate grasslands compared with the other climatic factors. This study provides the scientific basis for better understanding the mechanism of phenological response to climate change in temperate grasslands.
... Además, los eventos de heladas registrados durante el mismo periodo en el estado no fueron típicos. Estos eventos destruyeron los pastos y causaron la muerte de más de 300,000 bovinos (19,20) . Los objetivos de esta investigación fueron analizar las métricas fenológicas del inicio (SOS) y del final (EOS) de la temporada de crecimiento durante 2000-2010 y 2011-2019, que son períodos anteriores y posteriores a 2011. ...
Los datos fenológicos observados en tierra, junto con datos satelitales, son herramientas cruciales para identificar la estación de crecimiento de la vegetación. Utilizando un enfoque geoestadístico, este estudio tuvo como objetivo determinar la dinámica estacional del pasto banderita [Bouteloua curtipendula (Michx.) Torr.] en Chihuahua y su relación con la variabilidad climática. Se calcularon las métricas del inicio (SOS) y del final (EOS) de la temporada de crecimiento de esta especie en el estado de Chihuahua. Además, se evaluó el efecto de la temperatura del aire y la precipitación en la dinámica del SOS y el EOS durante los periodos 2000-2010 y 2011-2019. Los tratamientos consideraron las tres regiones ecológicas (desierto, valles centrales y sierra) y los años de registro. El estado se estudió a través de tres zonas ecológicas: desierto (D), valles centrales (CV) y sierra (S) para su comparación. El SOS y el EOS del pasto banderita en cada zona se definieron anualmente a partir de datos Landsat durante el periodo 2000-2019, basándose en la dinámica del Índice de Vegetación de Diferencia Normalizada (NDVI). El SOS osciló entre mayo y junio (promedio de día juliano [doy]=174), mientras que el EOS osciló entre octubre y noviembre (promedio de día juliano [doy]=283). Se observó un retraso en el SOS en la zona D; el retraso en el crecimiento del pasto banderita en la estación primaveral puede deberse a una relativa escasez de agua, aunque la mayor temperatura en primavera facilita el cumplimiento de los requisitos térmicos para el crecimiento de la especie. Estos hallazgos sugieren que la variabilidad climática tiene un impacto significativo en la dinámica estacional del pasto banderita, lo que puede influir en las estrategias de manejo de estos ecosistemas.
... While NSC concentrations could be shifting purely in response to temperature, given that bud and stem vasculature may not yet be fully developed (Savage & Chuine, 2021), enzymes could also be shifting activity to degrade starch in response to limited water. This is not wholly unexpected as soil moisture and water availability have been demonstrated to impact spring bud phenological timing (Zelikova et al., 2015;Yun et al., 2018). Moreover, in droughtdeciduous trees it is the cycling of low and high soil water potentialsrather than temperaturethat triggers phenological transitions (Jolly & Running, 2004;Bart et al., 2017). ...
Leaf‐out in temperate forests is a critical transition point each spring and advancing with global change. The mechanism linking phenological variation to external cues is poorly understood. Nonstructural carbohydrate (NSC) availability may be key.
Here, we use branch cuttings from northern red oak (Quercus rubra) and measure NSCs throughout bud development in branch tissue. Given genes and environment influence phenology, we placed branches in an arrayed factorial experiment (three temperatures × two photoperiods, eight genotypes) to examine their impact on variation in leaf‐out timing and corresponding NSCs.
Despite significant differences in leaf‐out timing between treatments, NSC patterns were much more consistent, with all treatments and genotypes displaying similar NSC concentrations across phenophases. Notably, the moderate and hot temperature treatments reached the same NSC concentrations and phenophases at the same growing degree days (GDD), but 20 calendar days apart, while the cold treatment achieved only half the GDD of the other two.
Our results suggest that NSCs are coordinated with leaf‐out and could act as a molecular clock, signaling to cells the passage of time and triggering leaf development to begin. This link between NSCs and budburst is critical for improving predictions of phenological timing.
... Precipitation is also an important factor in sustaining plant growth and has a large impact on the variation of SOS and EOS. Research indicated that the delay or advance of vegetation phenology is suggested to be controlled by variations in precipitation in semi-arid grasslands (Zelikova et al., 2015). Hence, studying the response of vegetation phenology to climate change is critical for improving our understanding of ecosystem functioning and its underlying mechanisms (Piao et al., 2019a). ...
Quantifying how climate factors affect vegetation phenology is crucial for understanding climate-vegetation interactions and carbon and water cycles under a changing climate. However, the effects of different intensities of extreme climatic events on vegetation phenology remain poorly understood. Using a long-term solar-induced chlorophyll fluorescence dataset, we investigated the response of vegetation phenology to extreme temperatures and precipitation events of different intensities across the Tibetan Plateau (TP) from 2000 to 2018. We found that the effect of maximum temperature exposure days (TxED) and minimum temperature exposure days (TnED) on the start of the growing season (SOS) was initially delayed and shifted to advance along the increasing temperature gradients. However, the response of the end of the growing season (EOS) to TxED and TnED shifted from an advance to a delay with increasing temperature gradients until the temperature thresholds were reached, above which thresholds produced an unfavorable response to vegetation growth and brought the EOS to an early end. The corresponding maximum and minimum temperature thresholds were 10.12 and 2.54°C, respectively. In contrast, cumulative precipitation (CP) was more likely to advance SOS and delay EOS as the precipitation gradient increased, but the advance of SOS is gradually weakening. Four vegetation types (i.e., forest, shrubland, meadow, and steppe) showed similar trends in response to different climates, but the optimal climatic conditions varied between the vegetation types. Generally, meadow and steppe had lower optimal temperatures and precipitation than forest and shrubland. These findings revealed the divergent responses of vegetation phenology to extreme climate events of different intensities, implying that the SOS will continue to advance with warming, whereas the EOS may undergo a partial transformation from delayed areas to advanced areas with continued warming.
... Therefore, precipitation is a critical variable in the water budget Xu et al., 2018) and can be effective in alleviating water stress, as the limitation on water transport capacity and leaf photosynthetic rate is avoided Ding et al., 2016;Forkel et al., 2015;Gao et al., 2020). In arid and subarid grasslands, interannual variability in precipitation controls the direction (delayed or advanced) and magnitude of the effects of climate warming on plant phenology (Zelikova et al., 2015). This explains why the increase in preseason cumulative precipitation in autumn facilitates delaying effect of warming on EOS. ...
Many studies have reported that daytime warming advances the end of the vegetation growing season (EOS) in arid and semi-arid ecosystems in the northern middle latitudes. This finding, however, seems to contradict the fact that low temperature constrains alpine vegetation activity. Using EOS from 1982 to 2015 retrieved from satellite observations, we show that daytime warming could facilitate a delay in EOS on the Tibetan Plateau, the world's largest and highest alpine region, with a dry and cold climate. Our analysis revealed a positive partial correlation (REOS-Tmax) between EOS and preseason mean daily maximum temperature (Tmax) on 57 % of the Plateau in wetter years, but on only 41 % of it in drier years. At a regional level, REOS-Tmax was 0.69 (P < 0.05, t-test) during wetter years and -0.56 (P = 0.11) during drier years, indicating that daytime warming could directly delay EOS on the Plateau. On the other hand, we found a positive partial correlation (REOS-Prec) between EOS and preseason cumulative precipitation on 62 % of the Plateau during warmer years, but on only 47 % during colder years. At a regional level, REOS-Prec was 0.68 (P < 0.05) during warmer years and - 0.28 (P = 0.46) during colder years. Moreover, REOS-Prec increased on 60 % of the Plateau under increasing Tmax during 1982-2015, suggesting that daytime warming facilitates a delay in EOS on the Tibetan Plateau by regulating the effect of precipitation on EOS. Thus, to improve autumn phenology models in this region, researchers should consider the interactive effects of temperature and precipitation on EOS.
... Craine et al. [5] and Seddon et al. [6] found that precipitation is the dominant factor for vegetation growth in arid and semi-arid areas, while temperature is more important in high altitude and high latitude areas. Many studies have shown that the enhancement of vegetation activity in the middle latitudes is related to regional climate warming [9][10][11][12]. However, despite the significant increase in temperature, the positive impact of warming on vegetation dynamics is not significant in Europe [13]. ...
The mid-to-high latitudes of Asia (MHA) region is one of the regions with the strongest warming trend. It is also one of the regions where ecosystems are most sensitive to climate variability. However, it is still uncertain how the vegetation in the region will change in the future. Using an observation-based leaf area index (LAI) and meteorological data and the multiple regression method, this study analyzes the response of vegetation in the MHA to climate elements between 1982 and 2020. Machine learning prediction models based on the Random Forest (RF) and Extreme Random Tree (ERT) algorithms are then built and validated. Based on the calibrated meteorological fields from 17 Coupled Model Intercomparison Project Phase 6 (CMIP6) models under intermediate (SSP2-4.5) and high (SSP5-8.5) emission scenarios and the machine learning models, the LAI over the MHA between 2021 and 2100 is projected. It is found that the historical long-term increase in LAI in the MHA since 1982 is mainly caused by the increasing near-surface air temperature, while the interannual variations in LAI are also greatly affected by precipitation and surface downward solar radiation, especially in summer. The LAI over most of the MHA shows a significant upward trend in the future, except over some dry areas, and this upward trend is stronger under the SSP5-8.5 scenario than under the SSP2-4.5 scenario.
... Some grasslands are dominated by a few species that can be mapped using satellite-mounted sensors [15,16]; however, natural or semi-natural grasslands are often characterized by a high community complexity within small areas [17]. In addition, grasslands are particularly dynamic over time due to variations in water availability [18] and other environmental factors. Despite these challenges, recent technological developments have made applications involving grasslands more feasible. ...
Over the last 20 years, there has been a surge of interest in the use of reflectance data collected using satellites and aerial vehicles to monitor vegetation diversity. One methodological option to monitor these systems involves developing empirical relationships between spectral heterogeneity in space (spectral variation) and plant or habitat diversity. This approach is commonly termed the ‘Spectral Variation Hypothesis’. Although increasingly used, it is controversial and can be unreliable in some contexts. Here, we review the literature and apply three-level meta-analytical models to assess the test results of the hypothesis across studies using several moderating variables relating to the botanical and spectral sampling strategies and the types of sites evaluated. We focus on the literature relating to grasslands, which are less well studied compared to forests and are likely to require separate treatments due to their dynamic phenology and the taxonomic complexity of their canopies on a small scale. Across studies, the results suggest an overall positive relationship between spectral variation and species diversity (mean correlation coefficient = 0.36). However, high levels of both within-study and between-study heterogeneity were found. Whether data was collected at the leaf or canopy level had the most impact on the mean effect size, with leaf-level studies displaying a stronger relationship compared to canopy-level studies. We highlight the challenges facing the synthesis of these kinds of experiments, the lack of studies carried out in arid or tropical systems and the need for scalable, multitemporal assessments to resolve the controversy in this field.
... In some temperate regions, precipitation addition had little effect on flowering phenology (Cleland et al., 2006;Sherry et al., 2007), however, others have reported that spring phenology is affected by the interaction of warming and precipitation (Cleland et al., 2007;Shen et al., 2011). For example, in semiarid regions, variability in interannual precipitation controls the magnitude and direction (delay or advance) of flowering phenology in response to warming (Ganjurjav et al., 2020;Zelikova et al., 2015). Higher precipitation may compensate for the warming-induced reduction in soil moisture and thus advance phenology, while lower precipitation will further reduce soil moisture offsetting the positive effect of warming on phenology. ...
The timing of phenological events is highly sensitive to climate change, and may influence ecosystem structure and function. Although changes in flowering phenology among species under climate change have been reported widely, how species‐specific shifts will affect phenological synchrony and community‐level phenology patterns remains unclear. We conducted a manipulative experiment of warming and precipitation addition and reduction to explore how climate change affected flowering phenology at the species and community levels in an alpine meadow on the eastern Tibetan Plateau. We found that warming advanced the first and last flowering times differently and with no consistent shifts in flowering duration among species, resulting in the entire flowering period of species emerging earlier in the growing season. Early‐flowering species were more sensitive to warming than mid‐ and late‐flowering species, thereby reducing flowering synchrony among species and extending the community‐level flowering season. However, precipitation and its interactions with warming had no significant effects on flowering phenology. Our results suggest that temperature regulates flowering phenology from the species to community levels in this alpine meadow community, yet how species shifted their flowering timing and duration in response to warming varied. This species‐level divergence may reshape flowering phenology in this alpine plant community. Decreasing flowering synchrony among species and the extension of community‐level flowering seasons under warming may alter future trophic interactions, with cascading consequences to community and ecosystem function.
... Other studies in the alpine region indicated that higher soil warming (+1.6ºC) delayed flowering of K. pygmaea which is a dominant species in the alpine grassland (Dorji et al. 2013;Zhu et al. 2016) due to decreased soil water content induced by higher warming relative to our study. The warming effect on flowering phenology depended on soil water content in the alpine grassland (Ganjurjav et al. 2020), and interannual variation in precipitation controls the direction of warming effects (delay or advance) on plant phenology (Zelikova et al. 2015). However, we found that neither warming rate affected annual mean soil water content (Fig. S2b), and warming rates did not affect community flowering phenology regardless of the drought year in 2015 or wet years in 2016-2018. ...
There is a debate about unmatched results between manipulative warming using constant warming rates every year (CW) and long-term observations warming affect temperature sensitive of flowering phenology, and it is probable because that long-term observations could represent the actual yearly increase in temperature (i.e., a yearly stepwise warming rate per year, SW) which would differ from CW and their effects would be regulated by precipitation alteration. Here we conducted a warming experiment with CW (temperature increase by +1 ºC and sustained this elevated temperature for the duration of the study) and SW (temperature increase by + 0.25 ºC progressively each year) with precipitation addition in an alpine grassland for four years. Our results showed that neither warming rates affected community flowering phenology. However, precipitation addition advanced onsets of flowering for early-spring flowering (ESF) and mid-summer flowering (MSF) groups, and advanced the end date of flowering for ESF but delayed it for the MSF group. Thus, flowering duration remained stable for the ESF group and was prolonged for the MSF group, and further prolonged the flowering duration of the community. There were no interactions between warming rates and precipitation addition on the community flowering phenology. A severe drought in a year significantly decreased the maximum number of community flowers the following year. Therefore, change in precipitation has a greater effect than warming on the community flowering phenology in the semi-arid alpine grassland.
... community composition, maximum photosynthetic production, precipitation repackaging, semi-arid grasslands, vegetation greenness repackaging have been difficult to discern through long-term observations due to large interannual precipitation variability, legacy and lag effects, and complex impacts of simultaneous variations in natural precipitation amount and temporal packaging (Sala et al., 2012;Wu et al., 2015). However, high degrees of interannual and intra-annual variability in peak vegetation greenness timing suggest that precipitation variability at various time-scales may drive the magnitude and timing of GPP max (Zelikova et al., 2015). ...
Against a backdrop of rising temperature, large portions of the western United States are experiencing fewer, larger and less frequent precipitation events. How such temporal ‘repackaging’ of precipitation alters the magnitude and timing of seasonal maximum gross primary productivity (GPPmax) remains unknown. Addressing this knowledge gap is critical, since changes to GPPmax magnitude and timing can impact a range of ecosystem services and management decisions.
Here we used a field‐based precipitation manipulation experiment in a semi‐arid mixed annual/perennial bunchgrass ecosystem with mean annual precipitation ~384 mm to investigate how temporal repackaging of a fixed total seasonal precipitation amount impacts seasonal GPPmax and its timing.
We found that temporal repackaging of precipitation profoundly influenced the seasonal timing of GPPmax. Many/small precipitation events advanced the seasonal timing of GPPmax by ~13 days in comparison with climatic normal precipitation. Conversely, few/large events led to deeper soil water infiltration, which delayed the timing of GPPmax by up to 16 days in comparison with climatic normal precipitation, and altered end‐of‐season community composition by increasing the diversity of shallow‐rooted annual plants. While GPPmax magnitude did not differ across precipitation treatments, it was positively correlated with the abundance and biomass of deeper‐rooted perennial bunchgrasses. The sensitivity of plant growth, biomass accumulation and plant life histories to the timing and magnitude of precipitation events and the resulting temporal patterns of soil moisture regulated ecosystem responses to altered precipitation patterns.
Our results highlight the sensitivity of semi‐arid grassland ecosystem to the temporal repackaging of precipitation. We find that already‐observed and model‐forecasted shifts toward few/large precipitation events could drive significant delays in the timing of peak productivity for this ecosystem. Adaptive land management frameworks should consider these findings since shifts in peak ecosystem productivity would have major implications for multiple land user communities. Additional research is needed to better understand the role of climate, community composition and soil properties in mediating variability in the seasonal timing of maximum ecosystem productivity.
A free Plain Language Summary can be found within the Supporting Information of this article.
... Some studies have shown that precipitation in temperate grasslands of North America has no significant effect on the flowering date of vegetation [66]; however, other experiments have shown that reduced water supply advances SOS and flowering date to some extent. Moreover, in semiarid grasslands, precipitation largely controls the direction of phenological changes [67]; however, in meadow grasslands, precipitation is dominated by temperature, which indicates the variability among different geographical regions. To better represent the relationship between climate change and SOS, researchers have also used modeling and other means to estimate phenology [68]. ...
Vegetation phenology is an important indicator of global climate change, and the response of grassland phenology to climate change is particularly sensitive in ecologically fragile areas. To enhance the ecological security of the Tibetan Plateau, it is crucial to determine the relationship between fluctuations in the start of the growing season (SOS) and the response to environmental factors. We investigated the trends of the intra-annual (ten-day) and interannual spatiotemporal dynamics of the SOS on the Northeast Qinghai-Tibet Plateau (NQTP) from 2000–2020 with MOD09GA data. We identified the response relationships with environmental factors (climate, terrain) using the maximum value composite method and the Savitzky–Golay filtering and dynamic threshold method. The SOS was concentrated from the 110th to 150th days; the average annual SOS was on the 128th day, with a spatial pattern of “early in the east and late in the west”. The overall trend of the SOS was advanced (45.48%); the regions with the advanced trend were mainly distributed in the eastern part of the NQTP. The regions with a delayed SOS were mainly concentrated in the higher-altitude regions in the southwest (38.31%). The temperature, precipitation and SOS exhibited a reverse fluctuation trend around the midpoint of 2010. Precipitation affected the SOS earlier than temperature. When temperature became a limitation of the SOS, precipitation had a more significant regulatory effect on the SOS. The SOS and aspect, slope and altitude were distributed in axisymmetric, pyramidal and inverted pyramidal shapes, respectively. The SOS on shaded slopes was earlier and more intensive than that on sunny slopes. With increasing slope, the area of the SOS decreased, and it occurred later. The SOS area was largest at 4500–5000 m and decreased at lower and higher altitude intervals. The SOS occurred later as altitude increased.
... In order to evaluate changes in cover and community composition over time, images were analysed from seven time-points covering the beginning, middle and end of the experiment. Images were analysed using the software SamplePoint as described inZelikova et al. (2015). Each photograph was cropped to the rim of the pot and then a grid of one-points was superimposed onto the image. ...
Aims
Given the key functional role of understorey plant communities and the substantial extent of forest cover at the global scale, investigating understorey community responses to elevated CO2 (eCO2) concentrations, and the role of soil resources in these responses, is important for understanding the ecosystem-level consequences of rising CO2 concentrations for forest ecosystems. Here, we evaluated how experimentally manipulated the availabilities of the two most limiting resources in an extremely phosphorus-limited eucalypt woodland in eastern Australia woodland (i.e. water and phosphorus) can modulate the response of the understorey community to eCO2 in terms of germination, phenology, cover, community composition, and leaf traits.
Methods
We collected soil containing native soil seed bank to grow experimental understorey plant communities under glasshouse conditions.
Important findings
Phosphorus addition increased total plant cover, particularly during the first four weeks of growth and under high-water conditions, a response driven by the graminoid component of the plant community. However, the treatment differences diminished as the experiment progressed, with all treatments converging at ~80% plant cover after ~11 weeks. In contrast, plant cover was not affected by eCO2. Multivariate analyses reflected temporal changes in the composition of plant communities, from pots where bare soil was dominant to high-cover pots dominated by a diverse community. However, both phosphorus addition and the interaction between water availability and CO2 affected the temporal trajectory of the plant community during the experiment. Elevated CO2 also increased community-level specific leaf area, suggesting that functional adaptation of plant communities to eCO2 may precede the onset of compositional responses. Given that the response of our seedbank-derived understorey community to eCO2 developed over time and was mediated by interactions with phosphorus and water availability. Our results suggest that a limited role of eCO2 in shaping plant communities in water-limited systems, particularly where low soil nutrient availability constrains productivity responses.
... Ghazanfar, 1997;Olivares and Squeo, 1999;Seghieri and Simier, 2002). In addition to the effect of precipitation, some authors found that in water-limited ecosystems plant growth (Bisigato et al., 2013b;Thoma et al., 2016;Campanella et al., 2018) and also plant phenology (Friedel et al., 1993;Zelikova et al., 2015) are better correlated to soil water availability than to direct precipitation. That was attributed to the fact that, instead of bulk precipitation the most important element is effective precipitation (Fernández, 2007). ...
The identification of the main abiotic variables influencing the seasonal development of plant phenology contributes to our knowledge of how arid and semi-arid ecosystems function. In this study, we addressed the following questions: 1. Is soil water content the most important variable determining plant phenophases? 2. Are phenophases across different life forms associated with the soil water content of different layers? We evaluated the relationships between environmental variables (i.e. precipitation, air temperature, soil moisture, and day length) and plant phenophases, using variable-length time periods preceding each measurement. We selected five representative evergreen shrubs, four deciduous shrubs, and three dominant perennial grasses. All phenophases related to vegetative and reproductive growth, and senescence were registered monthly during three years. The relationships between plant phenophases and environmental variables were evaluated using Spearman's correlation. We found that plant phenophases showed stronger association with soil water content and air temperature than precipitation. In most species, vegetative and reproductive phenophases were positively related to soil water content while leaf senescence was negatively associated. Soil water contents of layers 2 (10–20 cm) and 3 (20–40 cm) were more frequently related to plant phenophases than those of the first (0–10 cm) and fourth (40–100 cm) layers. Significantly correlated environmental variables encompassed previous periods of variable length depending on the species. Our results highlighted that soil water and air temperature were tightly correlated to plant phenophases and that all species seem to use the water contained in the same soil layers.
... Changes in green up can then subsequently alter phenological events, like flowering, fruiting and withering . However, in some arid regions, precipitation, rather than temperature, determines the onset of green up (Zelikova et al., 2015;Cleverly et al., 2016). Moreover, some studies show plant phenology is controlled by the interaction of temperature and precipitation Chen et al., 2015). ...
Phenology is an important indicator of plant responses to environmental changes and is closely correlated with biomass production. However, how changes in phenological events affect plant biomass production when exposed to changing temperature and precipitation remain unclear.
We conducted a 4‐year manipulative experiment of warming and precipitation addition to explore phenology–biomass interactions under climate change in a dry alpine meadow on the central Qinghai–Tibetan Plateau from 2015 to 2018.
In dry and warm years, warming delayed phenology and precipitation addition advanced them. Warming decreased the biomass of Kobresia pygmaea in 2018 and the biomass of Poa pratensis in 2015, 2017 and 2018. However, precipitation addition significantly increased the biomass of Poa pratensis and Potentilla multifida in most of the experimental years. Phenological changes regulated the responses of biomass to treatments. Specifically, delay of green up of P. pratensis and delay of withering of K. pygmaea induced by warming can increase biomass production, but it can be offset by the direct negative effects of warming on biomass.
Synthesis. Here we show how warming‐induced drought tend to decrease the biomass production of graminoids and the negative effects of warming on the biomass of P. pratensis and K. pygmaea were partially offset by green up postponement and withering postponement respectively. Our results highlights phenology is a crucial regulator for biomass production under climate change. Hence, both direct and indirect effects of warming and precipitation addition on phenology and biomass cannot be ignored when predicting biomass responses to climate change.
... The management such as removal of biomass for hay required rainfall for the recovery. The harvesting of biomass or grazing followed by rainfall events stimulated the growth of vegetation causing higher productivity (Zelikova et al., 2015;Zhou et al., 2017b). However, drought following harvesting of biomass impedes the productivity. ...
Future weather and climates, especially rainfall, are expected to have larger variability in the Southern Plains of the United States. However, the degree and timing of environmental variability that affect productivity of pastures managed differently have not been well studied. We examined the impacts of environmental variability on grassland productivity using 17 years of gross primary productivity (GPP) data for co-located native and managed prairie pastures in Oklahoma. We also considered the interactive effects of management factors and environmental variability into the regression models and identified the critical temporal windows of environmental variables (CWE) that influence annual variability in GPP. Managed pasture (MP) showed greater variability of GPP than did native pasture (NP), particularly with reduced GPP in drought years. The resilience of native prairies under unfavorable climate extremes was evident by lower GPP anomalies in NP than MP during the 2011–2012 drought. Although both pastures experienced the same degree of environmental variability, the CWE affecting GPP was significantly different between NP and MP due to the modulating impact of management practices on the responses of GPP. Not only the range but also the timings of the CWE were different between NP and MP as MP was more responsive to the spring temperature and fall rainfall. Our findings warrant the incorporation of MP as a different commodity from NP when accounting for the ecosystem responses to environmental variability in global climate models.
... The dominating factors for vegetation activities are complicated in cold and semi-arid mid-latitude regions such as northeastern Asia, where plant life cycle is likely limited by temperature and also water shortage. Previous studies of vegetation dynamics in the mid-latitude regions had concluded that enhanced vegetation activity were related to regional climate warming (Fensholt et al 2012, Cong et al 2013, Zelikova et al 2015. However, the positive effect of climate warming on vegetation dynamics was insignificant despite the pronounced increase in temperature (Garonna et al 2014). ...
Long-term (1982–2013) datasets of climate variables and Normalized Difference Vegetation Index (NDVI) were collected from Climate Research Union (CRU) and GIMMS NDVI3g. By setting the NDVI values below the threshold of 0.2 as 0, NDVI_0.2 was created to eliminate the noise caused by changes of surface albedo during non-growing period. TimeSat was employed to estimate the growing season length (GSL) from the seasonal variation of NDVI. Statistical analyses were conducted to reveal the mechanisms of climate-vegetation interactions in the cold and semi-arid Upper Amur River Basin of Northeast Asia. The results showed that the regional climate change can be summarized as warming and drying. Annual mean air temperature (T) increased at a rate of 0.13 °C per decade. Annual precipitation (P) declined at a rate of 18.22 mm per decade. NDVI had an insignificantly negative trend, whereas, NDVI_0.2 displayed a significantly positive trend (MK test, p < 0.05) over the past three decades. GSL had a significantly positive rate of approximately 2.9 days per decade. Correlation analysis revealed that, NDVI was significantly correlated with amount of P, whereas, GSL was highly correlated with warmth index (WMI), accumulation of monthly T above the threshold of 5°C. Principal regression analysis revealed that the inter-annual variations of NDVI, NDVI_0.2 and GSL were mostly contributed by WMI. Spatially, NDVI in grassland was more sensitive to P, whereas, T was more important in areas of high elevation. GSL in most of the areas displayed high sensitivity to T. This study examined the different roles of climate variables in controlling the vegetation activities. Further studies are needed to reveal the impact of extended GSL on the regional water balance and the water level of regional lakes, providing the habitats for the migratory birds and endangered species.
... Resource managers need effective options to address increasing conservation challenges as key rangelands are subjected to changing fire regimes (Balch et al. 2013;Kelly et al. 2013), the spread of non-native invasive plant species (Watkins et al. 2007;Dufresne et al. 2009;McCary et al. 2016), urban expansion (Soulsbury and White 2015), energy development (Sawyer et al. 2006) and changing climates (Dufresne et al. 2009;Zelikova et al. 2015). Particularly in western sagebrush rangelands such as the Kaibab, conservation and restoration efforts have the potential to promote not only mule deer populations, but other seasonal or year-round sagebrush obligates in Arizona, such as sage thrashers (Oreoscoptes montanus), Brewer's sparrows (Spizella breweri), and American pronghorn (Antilocapra americana), as well as pygmy rabbits (Brachylagus idahoensis) and greater sage-grouse (Centrocerus urophasianus) in other western states (Copeland et al. 2014). ...
Context Wildfire and vegetation treatments affect mule deer (Odocoileus hemionus) populations across the western United States. However, the relative influence of fire and treatments on habitat use by mule deer in Arizona is not well defined. Aims We examined locations of mule deer on the Kaibab Plateau in northern Arizona, so as to determine the influence of vegetation treatments and wildfire severity on deer habitat-use patterns across their winter range where fires and treatments had occurred previously. Methods We used locations (n = 11297) from 21 adult female mule deer fitted with global positioning system collars to model probability of use as a function of habitat covariates. Key results The best model describing winter-range habitat use by mule deer on the Kaibab Plateau included covariates describing the age of vegetation treatments and fire severity. Increased deer use in winter was associated with areas of lower terrain ruggedness and reduced snow depths. Deer use also increased in areas that experienced a higher average fire severity, resulting in decreased vegetation heights. Among treatment age classes, deer use was greatest in areas containing vegetation treatments that were ≤6 years old, but negatively associated with treatments that were >6 years old. Conclusions Vegetation treatments designed to remove or reduce less palatable tree and shrub species to improve forage conditions may increase the use of winter habitats by deer on the Kaibab Plateau. Similarly, prescribed fire and rangeland treatments designed to return areas to a more natural fire regime and, thereby, generate new plant growth, may improve winter-range habitat conditions for mule deer. Implications Similar treatment strategies may also benefit mule deer populations throughout the western USA, by improving forage conditions on critical habitats and reducing the potential for catastrophic wildfire.
... An earlier onset of spring and significant extension of the growing season, particularly, have been documented due to climate warming in the Northern Hemisphere [16][17][18] . Apart from changes in temperature, ecosystem processes are influenced by other factors like elevated CO 2 and N in soil in different seasons 19,20 . ...
... In the present study, warming facilitated significantly community NEP and WUE in May and August, but inhibited them significantly between June and July ( Figure 5), which partly supports hypothesis 2 that warming would inhibit these factors. The result found in this study is similar to that found by Zelikova et al. (2015). They showed that differential daytime/night-time warming (1.5/3°C) for 8 years increased vegetation cover and greenness early in the growing season, but often had a negative effect during the middle of the summer in a semiarid grassland. ...
Abstract Temperature increasing and precipitation alteration are predicted to occur in arid and semiarid lands; however, the response mechanism of carbon and water exchange at community level is still unclear in semiarid sandy land. We investigated the responses of carbon and water exchanges to warming and precipitation enhancement along a sand dune restoration gradient: mobile sand dunes (MD), semifixed sand dunes (SFD), and fixed sand dunes (FD). The average net ecosystem productivity (NEP) and evapotranspiration (ET) between May and August increased by 98% and 59%, respectively, from MD to SFD, while they had no significant differences between FD and the other two habitats. Warming inhibited ecosystem NEP, ET, and water use efficiency (WUE) by 69%, 49% (p
... In some species, phenological changes caused by warming were detected within the first year of warming, whereas phenological changes in most other species occurred after 2-4 years of warming treatment. Warming effects on the phenology of plants in grasslands interact with other climate change factors (e.g., elevated CO 2 , Reyes-Fox et al., 2014) or are mediated by variation in both intraannual and interannual precipitation (Zelikova et al., 2015). ...
... The ecological consequences of drought, loosely defined as a decline in the expected quantity of precipitation, is explored in some fashion by each of the papers featured in this special issue. Less explored and understood are the ecological consequences of shifts in rainfall seasonality (Zelikova et al. 2015), rainfall frequency (Liu et al. 2017), and rainfall intensity (Kulmatiski and Beard 2013). The fact that all four of these elements of precipitation variability may shift in response to anthropogenic climate change underpins the urgency to understand their ecological consequences despite the logistical limitations of experimental design (Owens 2003;Beier et al. 2012). ...
... However, we also found positive effects of warming at the central site during the winter and spring of the wet year (2017) and at the northern site during the winter, spring, and fall of both wet and average years. Thus, for the central and northern sites, there appear to be interactions between the effect of warming and annual rainfall on live biomass across parts of theyear, a phenomenon that has been previously documented(Mueller et al., 2016;Zelikova et al., 2015). At the southern site, however, this interaction is absent; warming is consistently negative. ...
Plant phenology will likely shift with climate change, but how temperature and/or moisture regimes will control phenological responses is not well understood. This is particularly true in Mediterranean climate ecosystems where the warmest temperatures and greatest moisture availability are seasonally asynchronous. We examined plant phenological responses at both the population and community levels to four climate treatments (control, warming, drought, and warming plus additional precipitation) embedded within three prairies across a 520 km latitudinal Mediterranean climate gradient within the Pacific Northwest, USA. At the population level, we monitored flowering and abundances in spring 2017 of eight range‐restricted focal species planted both within and north of their current ranges. At the community level, we used normalized difference vegetation index (NDVI) measured from fall 2016 to summer 2018 to estimate peak live biomass, senescence, seasonal patterns, and growing season length. We found that warming exerted a stronger control than our moisture manipulations on phenology at both the population and community levels. Warming advanced flowering regardless of whether a species was within or beyond its current range. Importantly, many of our focal species had low abundances, particularly in the south, suggesting that establishment, in addition to phenological shifts, may be a strong constraint on their future viability. At the community level, warming advanced the date of peak biomass regardless of site or year. The date of senescence advanced regardless of year for the southern and central sites but only in 2018 for the northern site. Growing season length contracted due to warming at the southern and central sites (~3 weeks) but was unaffected at the northern site. Our results emphasize that future temperature changes may exert strong influence on the timing of a variety of plant phenological events, especially those events that occur when temperature is most limiting, even in seasonally water‐limited Mediterranean ecosystems.
... Types of land use are different in different climatic conditions. For example, wet areas are dominated by forest [2], arid and semi-arid areas are dominated by grassland [3], while arid areas are dominated by desert [4]. Climate warming and wetting changes will correspondingly result in further land use changes [5]. ...
In this study, we analyzed the temporal-spatial variations of the characteristics of land use change in central Asia over the past two decades. This was conducted using four indicators (change rate, equilibrium extent, dynamic index, and transfer direction) and a multi-scale correlation analysis method, which explained the impact of recent environmental transformations on land use changes. The results indicated that the integrated dynamic degree of land use increased by 2.2% from 1995 to 2015. The areas of cropland, water bodies, and artificial land increased, with rates of 1047 km2/a, 39 km2/a, and 129 km2/a, respectively. On the other hand, the areas of forest, grassland, and unused land decreased, with rates of 54 km2/a, 803 km2/a, and 359 km2/a, respectively. There were significant increases in cropland and water bodies from 1995 to 2005, while the amount of artificial land significantly increased from 2005 to 2015. The increased areas of cropland in Xinjiang were mainly converted from grassland and unused land from 1995 to 2015, while the artificial land increase was mainly a result of the conversion from cropland, grassland, and unused land. The area of cropland rapidly expanded in south Xinjiang, which has led to centroid position to move cropland in Xinjiang in a southwest direction. Economic development and the rapid growth of population size are the main factors responsible for the cropland increases in Xinjiang. Runoff variations have a key impact on cropland changes at the river basin scale, as seen in three typical river basins.
... Our goal was to evaluate these relationships under relatively realistic conditions. Thus, DETECT was parameterized based on the well-studied Prairie Heating and CO 2 Enrichment (PHACE) study in Wyoming, United States, (Bachman et al., 2010;Pendall et al., 2013;Zelikova et al., 2015) and run with driving data representative of the PHACE site. We then applied a CWC analysis to the model output to evaluate variability in the temporal relationship between S Total and R soil and between these CO 2 fluxes and environmental driving variables at subdaily to monthly time scales over the course of a single growing season. ...
Inferences about subsurface CO2 fluxes often rely on surface soil respiration (Rsoil) estimates because directly measuring subsurface microbial and root respiration (collectively, CO2 production, STotal) is difficult. To evaluate how well Rsoil serves as a proxy for STotal, we applied the nonsteady state DEconvolution of Temporally varying Ecosystem Carbon componenTs model (0.01-m vertical resolution), using 6-hourly data from a Wyoming grassland, in six simulations that cross three soil types (clay, sandy loam, and sandy) with two depth distributions of subsurface biota. We used cross-wavelet coherence analysis to examine temporal coherence (localized linear correlation) and offsets (lags) between STotal and Rsoil and fluxes and drivers (e.g., soil temperature and moisture). Cross-wavelet coherence revealed higher coherence between fluxes and drivers than linear regressions between concurrent variables. Soil texture and moisture exerted the strongest controls over coherence between CO2 fluxes. Coherence between CO2 fluxes in all soil types was strong at short (~1 day) and long periods (>8 days), but soil type controlled lags, and rainfall events decoupled the fluxes at periods of 1-8 days for several days in sandy soil, up to 1 week in sandy loam, and for a month or more in clay soil. Concentrating root and microbial biomass nearer the surface decreased lags in all soil types and increased coherence up to 10% in clay soil. The assumption of high temporal coherence between Rsoil and STotal is likely valid in dry, sandy soil, but may lead to underestimates of short-term STotal in semiarid grasslands with fine-grained and/or wet soil.
... Most previous studies suggest that a warmer spring results in an advancement of spring phenological events of grassland vegetation [11,[31][32][33][34]. However, under conditions where concurrent precipitation is limiting, increasing temperature may have no significant effects on spring phenology [35,36]. It has been shown that increasing precipitation had no significant effects on flowering dates in two temperate grasslands of North America [37,38], while reduced precipitation induced an earlier green-up and flowering of herbaceous species in field experiments [39][40][41]. ...
Vegetation phenology in temperate grasslands is highly sensitive to climate change. However, it is still unclear how the timing of vegetation phenology events (especially for autumn phenology) is altered in response to climate change across different grassland types. In this study, we investigated variations of the growing season start (SOS) and end (EOS), derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data (2000–2016), for meadow steppe, typical steppe, and desert steppe in the Inner Mongolian grassland of Northern China. Using gridded climate data (2000–2015), we further analyzed correlations between SOS/EOS and pre-season average air temperature and total precipitation (defined as 90-day period prior to SOS/EOS, i.e., pre-SOS/EOS) in each grid. The results showed that both SOS and EOS occurred later in desert steppe (day of year (doy) 114 and 312) than in meadow steppe (doy 109 and 305) and typical steppe (doy 111 and 307); namely, desert steppe has a relatively late growing season than meadow steppe and typical steppe. For all three grasslands, SOS was mainly controlled by pre-SOS precipitation with the sensitivity being largest in desert steppe. EOS was closely connected with pre-EOS air temperature in meadow steppe and typical steppe, but more closely related to pre-EOS precipitation in desert steppe. During 2000–2015, SOS in typical steppe and desert steppe has significantly advanced by 2.2 days and 10.6 days due to a significant increase of pre-SOS precipitation. In addition, EOS of desert steppe has also significantly advanced by 6.8 days, likely as a result from the combined effects of elevated preseason temperature and precipitation. Our study highlights the diverse responses in the timing of spring and autumn phenology to preceding temperature and precipitation in different grassland types. Results from this study can help to guide grazing systems and to develop policy frameworks for grasslands protection.
Soil moisture is an important precision agricultural variable that can be used to identify optimal growth conditions, infer vegetation stress, and maximize crop yield. However, obtaining soil moisture information with sufficient spatial and temporal resolution for such applications remains a challenge. The optical trapezoid model (OPTRAM), a shortwave infrared transformed reflectance and normalized difference vegetation index (STR-NDVI) method, has previously been used for retrieving soil moisture from optical remote sensing data. However, the capacity of OPTRAM for mapping the high-resolution spatial heterogeneity of soil moisture at individual agricultural field scales has yet to be explored. Here, we advance an approach for retrieving and quantifying the spatial heterogeneity of soil moisture for individual fields using high spatiotemporal resolution Sentinel-2 imagery. We also propose the concept of a dynamic STR-NDVI space for identification of irrigation events and crop growth stages, such as irrigation start and end dates, and dates of initial crop growth, maturity and harvest. Pre-existing OPTRAM parameterization schemes were evaluated for several crops (maize, carrot, alfalfa and Rhodes grass) and a new scheme was proposed. Results show that the original OPTRAM model can derive surface soil moisture (∼ 1 cm in depth) with acceptable coefficients of determination (R² ≥ 0.43) and root mean square errors (RMSE ≤ 0.09 m³/m³) against ground measurements when uniform dry and wet edge parameters are applied for all crop types. The proposed scheme produced improved soil moisture retrievals with an R² ≥ 0.65 and RMSE ≤ 0.05 m³/m³ when the specific dry and wet edge parameters were applied for each specific crop type. By analyzing time series of STR-NDVI, we demonstrate that the dynamic STR-NDVI spaces not only traces the coevolution of surface processes but also quantifies the spatial heterogeneity of soil moisture and vegetation status. Thus, the proposed dynamic STR-NDVI spaces based on the high spatiotemporal resolution Sentinel-2 imagery can both advance and extend the application of OPTRAM and improve the interpretation of soil moisture spatial heterogeneity at agricultural field scales, supporting efforts towards irrigation and crop growth monitoring in precision agriculture.
Regeneration of grassland species is being affected by climate warming and elevated CO2 as interspecific variation in regeneration success drives change in community structure. Although regeneration in many grasslands is driven predominately by vegetative reproduction, climate change has been shown to benefit species that reproduce wholly or in part by seeds, suggesting that understanding how climate change affects regeneration from seed will help predict its impacts on grassland ecosystems. This chapter explores the shifts in community composition induced by climate change. We compared simulated with observational climate change studies and field versus laboratory results. Using this information, we explore the effects of climate change on flowering phenology, seed production, seed physiology, and the relationship of these factors to seed germination and seedling recruitment. Finally, we attempt to relate shifts in seed traits to changes in grassland community composition.
Knowledge of the response of grassland phenology towards climatic factors is essential to improve our understanding of ecological processes under global warming. To date, however, it remains unclear how climate change and associated changes in vegetation dynamics might affect autumn phenology of grasslands at the global scale. In this study, the trends in start of growing season (SOS) and end of growing season (EOS) dates were explored using remote sensing data (1981-2014). The responses of EOS to preseason temperature, rainfall, SOS, and net primary productivity (NPP) were then investigated for the mid-latitude (30°N~55°N) grasslands of the Northern Hemisphere. The remotely-sensed SOS/EOS and PhenoCam-based SOS/EOS were first compared and a good correlation was observed. Trend analysis revealed that the time span of SOS/EOS (from the earliest SOS/EOS to the last SOS/EOS) and the growing season length (from SOS to EOS) have extended for the entire study region. Furthermore, a forward shift in all SOS pixels was observed in Central-West Asian grasslands, whereas no such significant trend was observed for North American grasslands and East Asian grasslands. The duration of EOS completion had shortened within North American grasslands but lengthened in Asian grasslands. Next, correlation analysis uncovered a stronger relationship between EOS and previous rainfall than between EOS and temperature, indicating the key role of water availability in controlling autumn phenology. The sensitivity of EOS to both temperature and rainfall was higher in drier and warmer locations. Moreover, a significant negative correlation between EOS and SOS was observed in part of the study region, but no significant relationship between NPP and EOS was observed. Overall, this study highlights the spatially intensified heterogeneity of spring and autumn phenology in northern grasslands and that climatic changes in precipitation might act as key drivers for modifying autumn phenology of grassland vegetation in the Northern Hemisphere.
Studying grassland phenology and its relationships to climate would deepen our understanding of vegetation-air interactions under global climate change. To date, however, our knowledge of the responses of grassland phenology to climatic factors is still limited at the continental scale. In this study, we retrieved the start (SOS) and end (EOS) of the growing season for mid-latitude (30°N–55°N) grasslands of the Northern Hemisphere during 1981–2014, and investigated their relations with previous temperature, rainfall, and snowfall (only for SOS) through trends analysis and time window analysis. Results illustrated a predominant significant advancing/delaying trend of SOS/EOS in 23.2%/20.5% of the study region. They jointly resulted in a primarily significant prolongation trend of growing season length in 22.7% of the study region. Next, a dominated negative correlation between air temperature/rainfall and SOS was found in 62.4%/57.6% of areas. Snowfall showed converse effects (positive/negative) among different grasslands. The time window opening date for air temperature to start to affect SOS was identified as the day 1–90 before the multi-year average SOS in 76.1% of areas, while the time window opening date for the effect of rainfall/snowfall on SOS was relatively evenly distributed between the 1st and 180th day before the multi-year average SOS. EOS was found to be significantly negatively/positively correlated with air temperature/precipitation in 74.8%/83.7% of areas. The time window opening date for the effect of air temperature on EOS was identified as the 90–180th day before the multi-year average EOS in 66.9% of areas, while the time window opening date for the effect of precipitation on EOS was mainly concentrated on the 60-120th day before the multi-year average EOS in 51.5% of areas. Overall, this study highlights the distinctly different time windows for the thermal-moisture effects on grassland vegetation phenology and this should be considered when establishing process-based phenological models.
Phenology studies mostly focus on variation across time or landscapes. However, phenology can vary at fine spatial scales, and these differences may be as important as long-term change from climate warming. We used high-frequency “PhenoCam” data to examine phenology of Spartina alterniflora, a foundation species native to salt marshes on the US East and Gulf coasts, and a common colonizer elsewhere. We examined phenology across three microhabitats from 2013 to 2017 and used this information to create the first spring green-up model for S. alterniflora. We then compared modern spatial variation to that exhibited over a 60-year climate record. Marsh interior plants initiated spring growth 17 days earlier than channel edge plants and spent 35 days more in the green-up phenophase and 25 days less in the maturity phenophase. The start of green-up varied by 17 days among 3 years. The best spring green-up model was based on winter soil total growing degree days. Across microhabitats, spring green-up differences were caused by small elevation changes (15 cm) that drove soil temperature variation of 0.8°C. Preliminary evidence indicated that high winter belowground biomass depletion triggered early green-up. Long-term change was similar: winter soil temperatures warmed 1.7 ± 0.3°C since 1958, and green-up advanced 11 ± 6 days, whereas contemporary microhabitat differences were 17 ± 4 days. Incorporating local spatial variation into plant phenology models may provide an early warning of climate vulnerability and improve understanding of ecosystem-scale productivity. Microscale phenology variation likely exists in other systems and has been unappreciated.
The rapid pace of global climate change necessitates tools for prioritizing limited climate-adaptation resources in the face of imperfect knowledge regarding plant community responses to changing climate. In addition, global climate change often leads to novel shifts in plant communities which are difficult to anticipate with detailed models based on current system dynamics, which are often greatly altered under novel climates. In order to identify nonforested plant communities that are highly susceptible to state transitions under global climate change, we examined differences between the historical climate envelopes and end-of-century projections. We developed a vulnerability index based on the realized climate envelope for a given plant community relative to future climate exposure under two different climate-forcing models. To provide an approach to prioritizing climate-change adaptation resources at smaller scales, we used scenario analysis to determine the probability of falling outside of the historical climate envelope for each vegetation type present in a given management unit. The large-scale index consistently identified several areas as highly vulnerable to ecosystem state transition under future global climate change. South and north central Texas, the northwestern Great Plains and Rocky Mountain regions, eastern Kansas, and large portions of central and western Texas appear most vulnerable under both climate models. Scenarios identified thresholds of potential state shift for every vegetation type in the small-scale management areas investigated. Our study identifies a simple method for determining the relative vulnerability of nonforested plant communities to state shifts, providing a robust approach for prioritizing limited climate-adaptation resources at multiple scales.
The flux of CO2 from the soil to the atmosphere (soil respiration, Rsoil) is a major component of the global carbon (C) cycle. Methods to measure and model Rsoil, or partition it into different components, often rely on the assumption that soil CO2 concentrations and fluxes are in steady state, implying that Rsoil is equal to the rate at which CO2 is produced by soil microbial and root respiration. Recent research, however, questions the validity of this assumption. Thus, the aim of this work was two-fold: (1) to describe a non-steady state (NSS) soil CO2 transport and production model, DETECT, and (2) to use this model to evaluate the environmental conditions under which Rsoil and CO2 production are likely in NSS. The backbone of DETECT is a non-homogeneous, partial differential equation (PDE) that describes production and transport of soil CO2, which we solve numerically at fine spatial and temporal resolution (e.g., 0.01 m increments down to 1 m, every 6 h). Production of soil CO2 is simulated for every depth and time increment as the sum of root respiration and microbial decomposition of soil organic matter. Both of these factors can be driven by current and antecedent soil water content and temperature, which can also vary by time and depth. We also analytically solved the ordinary differential equation (ODE) corresponding to the steady-state (SS) solution to the PDE model. We applied the DETECT NSS and SS models to the six-month growing season period representative of a native grassland in Wyoming. Simulation experiments were conducted with both model versions to evaluate factors that could affect departure from SS, such as (1) varying soil texture; (2) shifting the timing or frequency of precipitation; and (3) with and without the environmental antecedent drivers. For a coarse-textured soil, Rsoil from the SS model closely matched that of the NSS model. However, in a fine-textured (clay) soil, growing season Rsoil was ∼ 3 % higher under the assumption of NSS (versus SS). These differences were exaggerated in clay soil at daily time scales whereby Rsoil under the SS assumption deviated from NSS by up to 35 % on average in the 10 days following a major precipitation event. Incorporation of antecedent drivers increased the magnitude of Rsoil by 15 to 37 % for coarse- and fine-textured soils, respectively. However, the responses of Rsoil to the timing of precipitation and antecedent drivers did not differ between SS and NSS assumptions. In summary, the assumption of SS conditions can be violated depending on soil type and soil moisture status, as affected by precipitation inputs. The DETECT model provides a framework for accommodating NSS conditions to better predict Rsoil and associated soil carbon cycling processes.
Global changes that alter soil water availability may have profound effects on semiarid ecosystems. Although both elevated CO2 (eCO2) and warming can alter water availability, often in opposite ways, few studies have measured their combined influence on the amount, timing, and temporal variability of soil water. Here, we ask how free air CO2 enrichment (to 600 ppmv) and infrared warming (+ 1.5 °C day, + 3 °C night) effects on soil water vary within years and across wet-dry periods in North American mixed-grass prairie. We found that eCO2 and warming interacted to influence soil water and that those interactions varied by season. In the spring, negative effects of warming on soil water largely offset positive effects of eCO2. As the growing season progressed, however, warming reduced soil water primarily (summer) or only (autumn) in plots treated with eCO2. These interactions constrained the combined effect of eCO2 and warming on soil water, which ranged from neutral in spring to positive in autumn. Within seasons, eCO2 increased soil water under drier conditions, and warming decreased soil water under wetter conditions. By increasing soil water under dry conditions, eCO2 also reduced temporal variability in soil water. These temporal patterns explain previously observed plant responses, including reduced leaf area with warming in summer, and delayed senescence with eCO2 plus warming in autumn. They also suggest that eCO2 and warming may favor plant species that grow in autumn, including winter annuals and C3 graminoids, and species able to remain active under the dry conditions moderated by eCO2.
Impact of climate change on water supply and use is a critical issue for dryland crop production. In this study is assessed the potential impact of atmospheric CO2 enrichment (500 μmol mol⁻¹, CE) and canopy warming (+2 °C, WA) and their combination (CW) on crop water utilization efficiency (WUE) of winter wheat in an open-air field experiment from Southeast China. Micro-meteorological measurement and wheat growth under individual treatments over three executive years of 2012–2015 were used to estimate the crop water requirement (CWR) of wheat using an improved FAO Penman-Monteith equation. Overall, CO2 enrichment slightly decreased the CWR by 8.3%, and increased the WUE of grain production (WUEg) by 23.1%, averaged over the three years. In contrast, warming increased CWR by 19.6% but decreased WUEg by 27.9% over the period. Under CW treatment, however, CWR was increased by 3.1–15.8% but WUEg was decreased by 3.5–18.2% throughout three years. Clearly, the positive impact of CO2 enrichment on WUE was largely negated under canopy warming. Moreover, when assessing with individual year data, inter-annual variability of WUEg was insignificant under WA, smaller under CE but much higher under CW, compared to CK. These results indicated that an interaction by canopy warming overshadowed the potential increase in WUE with CO2 enrichment and enforced yearly fluctuation of the crop production under simulated climate change conditions. Therefore, improving water supply and management in agriculture should thus be endeavored to address the potential constraints with future trends of concurrent atmospheric CO2 enrichment and warming.
Significance
Evaluating ecological responses to climate change is essential to predict ecosystem function under future climate scenarios. In a mixed-grass prairie, we use a multifactor field experiment to show that the effects of elevated CO 2 and warming on plant community structure and productivity depend on interannual variation in precipitation. We also show that shifts in plant dominance patterns driven by elevated CO 2 in a mixed-grass prairie ecosystem promoted biomass and compositional stability and resistance to interannual variation in precipitation. The economic value of grasslands is largely dependent on the relative abundance of key forage species. Thus, our results have implications for how we manage native grasslands in the face of changing climate.
Precipitation and temperature drive many aspects of terrestrial ecosystem function. Climate change scenar-ios predict increasing precipitation variability and temper-ature, and long term experiments are required to evaluate the ecosystem consequences of interannual climate variation, increased growing season (intra-annual) rainfall variability, and warming. We present results from an experiment ap-plying increased growing season rainfall variability and year round warming in native tallgrass prairie. During ten years of study, total growing season rainfall varied 2-fold, and we found ∼50–200 % interannual variability in plant growth and aboveground net primary productivity (ANPP), leaf carbon assimilation (A CO 2), and soil CO 2 efflux (J CO 2) despite only ∼40 % variation in mean volumetric soil water content (0– 15 cm, 15). Interannual variation in soil moisture was thus amplified in most measures of ecosystem response. Dif-ferences between years in 15 explained the greatest por-tion (14–52 %) of the variation in these processes. Exper-imentally increased intra-annual season rainfall variability doubled the amplitude of intra-annual soil moisture varia-tion and reduced 15 by 15 %, causing most ecosystem pro-cesses to decrease 8–40 % in some or all years with increased rainfall variability compared to ambient rainfall timing, sug-gesting reduced ecosystem rainfall use efficiency. Warming treatments increased soil temperature at 5 cm depth, partic-ularly during spring, fall, and winter. Warming advanced canopy green up in spring, increased winter J CO 2 , and re-duced summer J CO 2 and forb ANPP, suggesting that the ef-fects of warming differed in cooler versus warmer parts of the year. We conclude that (1) major ecosystem processes Correspondence to: in this grassland may be substantially altered by predicted changes in interannual climate variability, intra-annual rain-fall variability, and temperature, (2) interannual climate vari-ation was a larger source of variation in ecosystem function than intra-annual rainfall variability and warming, and (3) effects of increased growing season rainfall variability and warming were small, but ecologically important. The relative effects of these climate drivers are likely to vary for different ecosystem processes and in wetter or drier ecosystems.
The rising atmospheric concentration of carbon dioxide (CO2) should stimulate ecosystem productivity, but to what extent is highly uncertain, particularly when combined with changing temperature and precipitation. Ecosystem response to CO2 is complicated by biogeochemical feedbacks but must be understood if carbon storage and associated dampening of climate warming are to be predicted. Feedbacks through the hydrological cycle are particularly important and the physiology is well known; elevated CO2 reduces stomatal conductance and increases plant water use efficiency (the amount of water required to produce a unit of plant dry matter). The CO2 response should consequently be strongest when water is limiting; although this has been shown in some experiments, it is absent from many. Here we show that large annual variation in the stimulation of above-ground biomass by elevated CO2 in a mixed C3/C4 temperate grassland can be predicted accurately using seasonal rainfall totals; summer rainfall had a positive effect but autumn and spring rainfall had negative effects on the CO2 response. Thus, the elevated CO2 effect mainly depended upon the balance between summer and autumn/spring rainfall. This is partly because high rainfall during cool, moist seasons leads to nitrogen limitation, reducing or even preventing biomass stimulation by elevated CO2. Importantly, the prediction held whether plots were warmed by 2 °C or left unwarmed, and was similar for C3 plants and total biomass, allowing us to make a powerful generalization about ecosystem responses to elevated CO2. This new insight is particularly valuable because climate projections predict large changes in the timing of rainfall, even where annual totals remain static. Our findings will help resolve apparent differences in the outcomes of CO2 experiments and improve the formulation and interpretation of models that are insensitive to differences in the seasonal effects of rainfall on the CO2 response.
Observations of a longer growing season through earlier plant growth in temperate to polar regions have been thought to be a response to climate warming. However, data from experimental warming studies indicate that many species that initiate leaf growth and flowering earlier also reach seed maturation and senesce earlier, shortening their active and reproductive periods. A conceptual model to explain this apparent contradiction, and an analysis of the effect of elevated CO2-which can delay annual life cycle events-on changing season length, have not been tested. Here we show that experimental warming in a temperate grassland led to a longer growing season through earlier leaf emergence by the first species to leaf, often a grass, and constant or delayed senescence by other species that were the last to senesce, supporting the conceptual model. Elevated CO2 further extended growing, but not reproductive, season length in the warmed grassland by conserving water, which enabled most species to remain active longer. Our results suggest that a longer growing season, especially in years or biomes where water is a limiting factor, is not due to warming alone, but also to higher atmospheric CO2 concentrations that extend the active period of plant annual life cycles.
As computing technology and image analysis techniques have advanced, the practice of histology has grown from a purely qualitative method to one that is highly quantified. Current image analysis software is imprecise and prone to wide variation due to common artifacts and histological limitations. In order to minimize the impact of these artifacts, a more robust method for quantitative image analysis is required.
Here we present a novel image analysis software, based on the hue saturation value color space, to be applied to a wide variety of histological stains and tissue types. By using hue, saturation, and value variables instead of the more common red, green, and blue variables, our software offers some distinct advantages over other commercially available programs. We tested the program by analyzing several common histological stains, performed on tissue sections that ranged from 4 µm to 10 µm in thickness, using both a red green blue color space and a hue saturation value color space.
We demonstrated that our new software is a simple method for quantitative analysis of histological sections, which is highly robust to variations in section thickness, sectioning artifacts, and stain quality, eliminating sample-to-sample variation.
As global changes reorganize plant communities, invasive plants may benefit. We hypothesized that elevated CO 2 and warming would strongly influence invasive species success in a semi‐arid grassland, as a result of both direct and water‐mediated indirect effects.
To test this hypothesis, we transplanted the invasive forb L inaria dalmatica into mixed‐grass prairie treated with free‐air CO 2 enrichment and infrared warming, and followed survival, growth, and reproduction over 4 yr. We also measured leaf gas exchange and carbon isotopic composition in L . dalmatica and the dominant native C 3 grass P ascopyrum smithii .
CO 2 enrichment increased L . dalmatica biomass 13‐fold, seed production 32‐fold, and clonal expansion seven‐fold, while warming had little effect on L . dalmatica biomass or reproduction. Elevated CO 2 decreased stomatal conductance in P . smithii , contributing to higher soil water, but not in L . dalmatica . Elevated CO 2 also strongly increased L . dalmatica photosynthesis (87% versus 23% in P . smithii ), as a result of both enhanced carbon supply and increased soil water.
More broadly, rapid growth and less conservative water use may allow invasive species to take advantage of both carbon fertilization and water savings under elevated CO 2 . Water‐limited ecosystems may therefore be particularly vulnerable to invasion as CO 2 increases.
The flux of carbon dioxide (CO2) between terrestrial ecosystems and the atmosphere may ameliorate or exacerbate climate change, depending on the relative responses of ecosystem photosynthesis and respiration to warming temperatures, rising atmospheric CO2, and altered precipitation. The combined effect of these global change factors is especially uncertain because of their potential for interactions and indirectly mediated conditions such as soil moisture. Here, we present observations of CO2 fluxes from a multi-factor experiment in semi-arid grassland that suggests a potentially strong climate - carbon cycle feedback under combined elevated [CO2] and warming. Elevated [CO2] alone, and in combination with warming, enhanced ecosystem respiration to a greater extent than photosynthesis, resulting in net C loss over four years. The effect of warming was to reduce respiration especially during years of below-average precipitation, by partially offsetting the effect of elevated [CO2] on soil moisture and C cycling. Carbon losses were explained partly by stimulated decomposition of soil organic matter with elevated [CO2]. The climate - carbon cycle feedback observed in this semiarid grassland was mediated by soil water content, which was reduced by warming and increased by elevated [CO2]. Ecosystem models should incorporate direct and indirect effects of climate change on soil water content in order to accurately predict terrestrial feedbacks and long-term storage of C in soil.
We used overhead infrared radiators to add a constant increment of â15 W/m², over 2 yr, to the downward heat flux on five 30-m² montane meadow plots in Gunnison County, Colorado, USA. Heating advanced snowmelt by â1 wk, increased summer soil temperatures by up to 3°C, and reduced summer soil moisture levels by up to 25% compared to control plots. Soil microclimate response to heating varied with season, time of day, weather conditions, and location along the microclimate and vegetation gradient within each plot, with the largest temperature increase observed in daytime and in the drier, more sparsely vegetated zone of each plot. Day-to-day variation in the daily-averaged temperature response to heating in the drier zone was negatively correlated with that in the wetter zone. Our experimental manipulation provides a novel and effective method for investigating feedback processes linking climate, soil, and vegetation. 36 refs., 5 figs., 8 tabs.
A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming ( thus, an extension of the vegetation period with intensive transpiration), and an insignificant change in total precipitation could lead to an increase in the frequency of a potentially serious type of extreme events: prolonged periods without precipitation ( even when the mean seasonal rainfall totals increase). This paper investigates whether this development is already occurring during the past several decades over the conterminous United States, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of "dry" days without sizeable (> 1.0 mm) precipitation were assessed only during the warm season ( defined as a period when mean daily temperature is above the 5 C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem's health and agriculture. During the past four decades, the mean duration of prolonged dry episodes ( 1 month or longer in the eastern United States and 2 months or longer in the southwestern United States) has significantly increased. As a consequence the return period of 1-month-long dry episodes over the eastern United States has reduced more than twofold from 15 to 6-7 yr. The longer average duration of dry episodes has occurred during a relatively wet period across the country but is not observed over the northwestern United States.
Ground vegetation influences habitat selection and provides critical resources for survival and reproduction of animals. Researchers often employ visual methods to estimate ground cover, but these approaches may be prone to observer bias. We therefore evaluated a method using digital photographs of vegetation to objectively quantify percent ground cover of grasses, forbs, shrubs, litter, and bare ground within 90 plots of 2m(2). We carried out object-based image analysis, using a software program called eCognition, to divide photographs into different vegetation classes (based on similarities among neighboring pixels) to estimate percent ground cover for each category. We used the Kappa index of agreement (KIA) to quantify correctly classified, randomly selected segments of all images. Our KIA values indicated strong agreement (> 80%) of all vegetation categories, with an average of 90-96% (SE = 5%) of shrub, litter, forb, and grass segments classified correctly. We also created artificial plots with known percentages of each vegetation category to evaluate the accuracy of software predictions. Observed differences between true cover and eCognition estimates for each category ranged from 1 to 4%. This technique provides a repeatable and reliable way to estimate percent ground cover that allows quantification of classification accuracy.
Although the potential for increased temperature is the primary and best-studied aspect of anthropogenic climate change, altered rainfall patterns, increased storm intensity, and more severe droughts are also predicted in most climate-change scenarios. We altered experimentally the rainfall regime in a native tallgrass prairie in northeastern Kansas and assessed leaf-level physiological activity and plant growth responses for C3 and C4 plant species. Our primary objective was to contrast the importance of reductions in rainfall quantity (30% smaller rain events, no change in rainfall pattern) with an altered, more extreme distribution of rainfall (no reduction in total growing-season quantity, 50% increased inter-rainfall dry intervals) for these dominant species from the two main plant functional groups (C4 grasses, C3 forbs) present in many grasslands. Leaf water potential (wl), net photosynthetic carbon gain ( ), specific leaf mass, leaf C : N ratio, growth rate ACO2 for Andropogon gerardii (C4 grass) and Solidago canadensis (C3 forb), vegetative and flowering stem densities, and canopy light penetration for grass and forb assemblages were intensively monitored during the 1999 growing season in a long-term rainfall manipulation study at the Konza Prairie Biological Station. Soil water content at 0-30 cm depth was more variable in response to the altered rainfall distribution compared to the reduced-quantity treatment. In S. canadensis ,, gs (stomatal conductance), A : Ci (leaf stomatal (CO2)), ACO2 and A : E (estimated leaf transpiration rate) were positively correlated with soil water content, but no rela- tionship was seen for A. gerardii, indicating that even though this dominant grass species has most of its roots in the upper 30 cm of the soil, A. gerardii was buffered physiologically from increased resource variability. There were few significant responses in growth parameters in either grasses or forbs, but canopy light pen- etration increased with both rainfall treatments. We concluded (1) that the temporal variability in rainfall inputs can have as much impact on soil moisture as simple reductions in rainfall quantities with no change in temporal distribution, (2) that responses of A. gerardii and S. canadensis to altered rainfall distributions were not consistent with common views of soil resource partitioning between shallow-rooted grasses and deep-rooted forbs, and (3) that altered rainfall patterns may have the potential to offset elevated CO2 impacts on grassland vegetation.
RESTORATION IS AN OPPORTUNITY TO STUDY NATURAL SELECTION: One can measure the distribution of traits in source propagules used to found populations, compare this with the distribution of traits in successful recruits, and determine the strength and direction of selection on potentially adaptive traits. We investigated whether natural selection influenced seedling establishment during postfire restoration in the Great Basin, an area where large-scale restoration occurs with a few widely available cultivars planted over a large range of environmental conditions. We collected seeds from established plants of the perennial grass Elymus elymoides ssp. californicus (squirreltail) at two restoration sites and compared the distribution of phenotypic traits of surviving plants with the original pool of restoration seeds. Seeds were planted in common gardens for two generations. Plants grown from seeds that established in the field were a nonrandom subset of the original seeds, with directional selection consistently favoring a correlated suite of traits in both field sites: small plant and seed size, and earlier flowering phenology. These results demonstrate that natural selection can affect restoration establishment in strong and predictable ways and that adaptive traits in these sites were opposite of the current criteria used for selection of restoration material in this system.
Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought-that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.
Changes in Earth's surface temperatures caused by anthropogenic emissions of greenhouse gases are expected to affect global
and regional precipitation regimes. Interactions between changing precipitation regimes and other aspects of global change
are likely to affect natural and managed terrestrial ecosystems as well as human society. Although much recent research has
focused on assessing the responses of terrestrial ecosystems to rising carbon dioxide or temperature, relatively little research
has focused on understanding how ecosystems respond to changes in precipitation regimes. Here we review predicted changes
in global and regional precipitation regimes, outline the consequences of precipitation change for natural ecosystems and
human activities, and discuss approaches to improving understanding of ecosystem responses to changing precipitation. Further,
we introduce the Precipitation and Ecosystem Change Research Network (PrecipNet), a new interdisciplinary research network
assembled to encourage and foster communication and collaboration across research groups with common interests in the impacts
of global change on precipitation regimes, ecosystem structure and function, and the human enterprise.
The magnitude and direction of the coupled feedbacks between the biotic and abiotic components of the terrestrial carbon cycle is a major source of uncertainty in coupled climate-carbon-cycle models. Materially closed, energetically open biological systems continuously and simultaneously allow the two-way feedback loop between the biotic and abiotic components to take place, but so far have not been used to their full potential in ecological research, owing to the challenge of achieving sustainable model systems. We show that using materially closed soil-vegetation-atmosphere systems with pro rata carbon amounts for the main terrestrial carbon pools enables the establishment of conditions that balance plant carbon assimilation, and autotrophic and heterotrophic respiration fluxes over periods suitable to investigate short-term biotic carbon feedbacks. Using this approach, we tested an alternative way of assessing the impact of increased CO 2 and temperature on biotic carbon feedbacks. The results show that without nutrient and water limitations, the short-term biotic responses could potentially buffer a temperature increase of 2.3 °C without significant positive feedbacks to atmospheric CO 2. We argue that such closed-system research represents an important test-bed platform for model validation and parameterization of plant and soil biotic responses to environmental changes.
Normalized Difference Vegetation Index (NDVI) is generally recog-nized as a good indicator of terrestrial vegetation productivity. Understanding climatic influences, in particular precipitation and temperature, on NDVI enables prediction of productivity changes under different climatic scenarios. We examined temporal responses of remotely sensed NDVI to precipitation and temperature during a nine-year period (1989–97) in Kansas. Biweekly (every two weeks) and monthly precipitation data were derived from 410 weather stations and biweekly temperature data were derived from 17 weather stations inside and around the borders of Kansas. Biweekly and monthly climate maps were derived by interpola-tion. Biweekly growing season (March–October) NDVI values for Kansas were calculated using National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) NDVI images. Average growing season NDVI values were highly correlated with precipitation received during the current growing season and seven preceding months (15-month dura-tion); biweekly NDVI values were correlated with precipitation received during 2–4 preceding biweekly periods; and response time of NDVI to a major precipita-tion event was typical 1–2 biweekly periods (2–4 weeks). Temperature was posit-ively correlated with NDVI early and late in the growing season, and there was a weak negative correlation between temperature and NDVI in the mid growing season. Precipitation has the primary influence on NDVI and, by inference, on productivity. The relationship between precipitation and NDVI is strong and predictable when viewed at the appropriate spatial scale.
1] This paper analyzes the relation between satellite-based measures of vegetation greenness and climate by land cover type at a regional scale (2° Â 2° grid boxes) between 1982 and 1999. We use the normalized difference vegetation index (NDVI) from the Global Inventory Monitoring and Modeling Studies (GIMMS) data set to quantify climate-induced changes in terrestrial vegetation. Climatic conditions are represented with monthly data for land surface air temperature and precipitation. The relation between NDVI and the climate variables is represented using a quadratic specification, which is consistent with the notion of a physiological optimum. The effects of spatial heterogeneity and unobserved variables are estimated with specifications and statistical techniques that allow coefficients to vary among grid boxes. Using this methodology, we are able to estimate statistically meaningful relations between NDVI and climate during spring, summer, and autumn for forests between 40°N and 70°N in North America and Eurasia. Of the variables examined, changes in temperature account for the largest fraction of the change in NDVI between the early 1980s and the late 1990s. Changes in stratospheric aerosol optical depth and precipitation have a smaller effect, while artifacts associated with variations in solar zenith angle are negligible. These results indicate that temperature changes between the early 1980s and the late 1990s are responsible for much of the observed increase in satellite measures of northern forest greenness.
The Normalized Difference Vegetation Index (NDVI) has proven to be a robust indicator of terrestrial vegetation productivity. Among climatic factors, precipitation and temperature strongly in uence both temporal and spatial pat-terns of NDVI. We examined spatial responses of NDVI to precipitation and temperature during a 9-year period (1989–1997) in Kansas. Biweekly climate maps (precipitation and temperature) were constructed by interpolation of weather station measurements. Maps of biweekly growing season (March to October) NDVI were constructed for Kansas using National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radio-meter (AVHRR) NDVI images. Average precipitation is a strong predictor of the major east–west NDVI gradient. Deviation from average precipitation explained most of the year-to-year variation in spatial patterns. NDVI and precipitation covaried in the same direction (both positive or both negative) for 60–95% of the total land area. Minimum and average temperatures were positively correlated with NDVI, but temperature deviation from average was generally not correlated with NDVI deviation from average. Our results demonstrate that precipitation is a strong predictor of regional spatial patterns of NDVI and, by inference, patterns of productivity.
