Mechanisms of grass response in grasslands and shrublands during dry or wet periods

Asynchronous xylogenesis among and within tree species in the central Congo Basin

BACKGROUND

Xylogenesis is synchronous among trees in regions with a distinct growing season, leading to a forest-wide time lag between growth and carbon uptake. In contrast, little is known about interspecific or even intraspecific variability of xylogenesis in tropical forests. Yet an understanding of xylogenesis patterns is key to successfully combine bottom-up (e.g., from permanent forest inventory plots) and top-down (e.g., from eddy covariance flux towers) carbon flux estimates.

METHODS

Here, we monitor xylogenesis development of 18 trees belonging to 6 abundant species during 8 weeks at the onset of the rainy season from March to April 2022 in a semideciduous rainforest in the Yangambi reserve (central Democratic Republic of the Congo). For each tree, the weekly cambial state (dormant or active) was determined by epifluorescence microscopy.

RESULTS

We find interspecific variability in the cambial phenology, with two species showing predominant cambial dormancy and two species showing predominant cambial activity during the monitoring period. We also find intraspecific variability in two species where individuals either display cambial dormancy or cambial activity. All trees kept > 60% of their leaves throughout the dry season and the monitoring period, suggesting a weak relationship between the phenology of the cambial and foliar. Our results suggest that individual trees in Yangambi asynchronously activate their cambial growth throughout the year, regardless of leaf phenology or seasonal rainfall.

CONCLUSION

These results are consistent with global analysis of gross primary productivity estimates from eddy covariance flux towers, showing that tropical biomes lack a synchronous dormant period. However, a longer-term monitoring experiment, including more species, is necessary to confirm this for the Congo Basin. As Yangambi is equipped with facilities for microscopic wood analysis, a network of inventory plots and a flux tower, further research in this site will reveal how xylogenesis patterns drive annual variability in carbon fluxes and how ground-based and top-down measurements can be combined for robust upscaling analysis of Congo basin carbon budgets.

Legacy effects of precipitation change: Theories, dynamics, and applications

The intensification of climate-induced precipitation change poses a dual challenge to terrestrial ecosystems: immediate effects on their structure and function, coupled with legacy effects that persist beyond the cessation of precipitation change. Quantifying these legacy effects accurately can greatly assist in assessing the long-term impact of precipitation change. However, their broader understanding is just beginning. Therefore, this review endeavors to synthesize the existing knowledge concerning the legacy effects of precipitation change, elucidating their nature, characteristics, driving factors, and implications, thereby fostering further advancements in this research domain. To begin, we define that precipitation legacies are carried by the information and/or material remnants arising from previous precipitation change, with the enduring impacts of these remnants (precipitation legacy carriers) on the current ecosystem being termed the precipitation legacy effects. To comprehensively investigate the performances of precipitation legacy effects, we introduce a multi-faceted characterization framework, encompassing magnitude, direction, duration, and spatial-temporal variability. This framework is complemented by a proposed sequential analysis approach, spanning the pre-, during, and post-precipitation change phases. Next, we emphasize that the nature of precipitation legacy carriers and the pattern of precipitation change jointly determine the characteristics of precipitation legacy effect. Subsequently, we elucidate the possible carriers of precipitation legacies across species, community, and ecosystem levels, as well as the linkages among these carriers and levels, thereby introducing the underlying formation mechanism of precipitation legacy effects. Lastly, from the perspective of ecosystem stability debt, we propose potential applications of precipitation legacy effects in future climate change research. The viewpoints and methodologies outlined in this review can deepen our comprehension of precipitation legacy effects, contributing to the comprehensive assessment of precipitation impact on soil-vegetation systems and providing guidance for formulating effective strategies to address future climate change.

Local surface warming assessment in response to vegetation shifts over arid lands of Central Asia (2001-2020)

The Northern Eurasia Earth Science Partnership Initiative (NEESPI) was established to address the large-scale environmental change across this region. Regardless of the increasingly insightful literature addressing vegetation change across Central Asia, the biogeophysical warming effects of vegetation shifts still need to be clarified. To contribute, the utility of robust satellite observation is explored to evaluate the surface warming effects of vegetation shifts across Central Asia, which is among NEEPSI's hotspots. We estimated an average increase of +1.9 °C in daytime local surface temperature and + 1.5 °C in the nighttime due to vegetation shift (2001-2020). Meanwhile, the mean local latent heat increased by 4.65Wm-2, following the mild reduction of emitted longwave radiation (-0.8Wm-2). We found that vegetation shifts led to local surface warming with a bright surface, noting that the average air surface temperature was revealed to have increased significantly (2001-2020). This signal was driven mainly by agricultural expansion in western Kazakhstan stretching to Tajikistan and Xinjiang, then deforestation confined in Tajikistan, southeast Kazakhstan, and the northwestern edge of Xinjiang, and finally, grassland encroachment occurred massively in the west to central Kazakhstan. These findings address the latest information on Central Asia's vegetation shifts that may be substantial in landscape change mitigation plans.

Will trees or grasses profit from changing rainfall regimes in savannas?

Increasing rainfall variability is widely expected under future climate change scenarios. How will savanna trees and grasses be affected by growing season dry spells and altered seasonality and how tightly coupled are tree-grass phenologies with rainfall? We measured tree and grass responses to growing season dry spells and dry season rainfall. We also tested whether the phenologies of 17 deciduous woody species and the Soil Adjusted Vegetation Index of grasses were related to rainfall between 2019 and 2023. Tree and grass growth was significantly reduced during growing season dry spells. Tree growth was strongly related to growing season soil water potentials and limited to the wet season. Grasses can rapidly recover after growing season dry spells and grass evapotranspiration was significantly related to soil water potentials in both the wet and dry seasons. Tree leaf flushing commenced before the rainfall onset date with little subsequent leaf flushing. Grasses grew when moisture became available regardless of season. Our findings suggest that increased dry spell length and frequency in the growing season may slow down tree growth in some savannas, which together with longer growing seasons may allow grasses an advantage over C3 plants that are advantaged by rising CO2 levels.

Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland

Understanding the resilience of ecosystems globally is hampered by the complex and interacting drivers of change characteristic of the Anthropocene. This is true for drylands of the western US, where widespread alteration of disturbance regimes and spread of invasive non-native species occurred with westward expansion during the 1800s, including the introduction of domestic livestock and spread of Bromus tectorum, an invasive non-native annual grass. In addition, this region has experienced a multi-decadal drought not seen for at least 1200 years with potentially large and interacting impacts on native plant communities. Here, we present 24 years of twice-annual plant cover monitoring (1997-2021) from a semiarid grassland never grazed by domestic livestock but subject to a patchy invasion of B. tectorum beginning in ~1994, compare our findings to surveys done in 1967, and examine potential climate drivers of plant community changes. We found a significant warming trend in the study area, with more than 75% of study year temperatures being warmer than average (1966-2021). We observed a native perennial grass community with high resilience to climate forcings with cover values like those in 1967. In invaded patches, B. tectorum cover was greatest in the early years of this study (1997-2001; ~20%-40%) but was subsequently constrained by climate and subtle variation in soils, with limited evidence of long-term impacts to native vegetation, contradicting earlier studies. Our ability to predict year-to-year variation in functional group and species cover with climate metrics varied, with a 12-month integrated index and fall and winter patterns appearing most important. However, declines to near zero live cover in recent years in response to regional drought intensification leave questions regarding the resiliency of intact grasslands to ongoing aridification and whether the vegetation observations reported here may be a leading indicator of impending change in this protected ecosystem.

Abrupt transitions in a southwest U.S. desert grassland related to the Pacific Decadal Oscillation

Prediction of abrupt ecosystem transitions resulting from climatic change will be an essential element of adaptation strategies in the coming decades. In the arid southwest United States, the collapse and recovery of long-lived perennial grasses have important effects on ecosystem services, but the causes of these variations have been poorly understood. Here we use a quality-controlled vegetation monitoring dataset initiated in 1915 to show that grass cover dynamics during the 20th century were closely correlated to the Pacific Decadal Oscillation (PDO) index. The relationship out-performed models correlating grasses to yearly precipitation and drought indices, suggesting that ecosystem transitions attributed only to local disturbances were instead influenced by climate teleconnections. Shifts in PDO phase over time were associated with the persistent loss of core grass species and recovery of transient species, so recovery of grasses in aggregate concealed significant changes in species composition. However, the relationship between PDO and grass cover broke down after 1995; grass cover is consistently lower than PDO would predict. The decoupling of grass cover from the PDO suggests that a threshold had been crossed in which warming or land degradation overwhelmed the ability of any grass species to recover during favorable periods. This article is protected by copyright. All rights reserved.

Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere

Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPP_max), and the ratio of mean daily GPP to GPP_max (α_GPP)), and then decomposed AGPP into mean leaf area index (LAI_m) and annual photosynthetic capacity per leaf area (AGPP_lm). Furthermore, GPP_max was decomposed into leaf area index of DOY_max (the day when GPP_max appeared) (LAI_max) and photosynthesis per leaf area of DOY_max (GPP_lmax). Relative contributions of parameters to AGPP and GPP_max were then calculated. Finally, environmental variables of DOY_max were extracted to analyze factors influencing interannual variation of GPP_lmax. Trends of AGPP in 39 ecosystems varied from -65.23 to 53.05 g C m^-2 yr^-2, with the mean value of 6.32 g C m^-2 yr^-2. Photosynthetic capacity (GPP_max and AGPP_lm), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPP_lmax determined the interannual variation of GPP_max, and temperature, water, and radiation conditions of DOY_max affected the interannual variation of GPP_lmax. This study used the cascade relationship of "environmental variables-GPP_lmax-GPP_max-AGPP" to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.

Cross-Site Comparisons of Dryland Ecosystem Response to Climate Change in the US Long-Term Ecological Research Network

Long-term observations and experiments in diverse drylands reveal how ecosystems and services are responding to climate change. To develop generalities about climate change impacts at dryland sites, we compared broadscale patterns in climate and synthesized primary production responses among the eight terrestrial, nonforested sites of the United States Long-Term Ecological Research (US LTER) Network located in temperate (Southwest and Midwest) and polar (Arctic and Antarctic) regions. All sites experienced warming in recent decades, whereas drought varied regionally with multidecadal phases. Multiple years of wet or dry conditions had larger effects than single years on primary production. Droughts, floods, and wildfires altered resource availability and restructured plant communities, with greater impacts on primary production than warming alone. During severe regional droughts, air pollution from wildfire and dust events peaked. Studies at US LTER drylands over more than 40 years demonstrate reciprocal links and feedbacks among dryland ecosystems, climate-driven disturbance events, and climate change.

Plant Species Richness in Multiyear Wet and Dry Periods in the Chihuahuan Desert

In drylands, most studies of extreme precipitation events examine effects of individual years or short-term events, yet multiyear periods (>3 y) are expected to have larger impacts on ecosystem dynamics. Our goal was to take advantage of a sequence of multiple long-term (4-y) periods (dry, wet, average) that occurred naturally within a 26-y time frame to examine responses of plant species richness to extreme rainfall in grasslands and shrublands of the Chihuahuan Desert. Our hypothesis was that richness would be related to rainfall amount, and similar in periods with similar amounts of rainfall. Breakpoint analyses of water-year precipitation showed five sequential periods (1993–2018): AVG1 (mean = 22 cm/y), DRY1 (mean = 18 cm/y), WET (mean = 30 cm/y), DRY2 (mean = 18 cm/y), and AVG2 (mean = 24 cm/y). Detailed analyses revealed changes in daily and seasonal metrics of precipitation over the course of the study: the amount of nongrowing season precipitation decreased since 1993, and summer growing season precipitation increased through time with a corresponding increase in frequency of extreme rainfall events. This increase in summer rainfall could explain the general loss in C3 species after the wet period at most locations through time. Total species richness in the wet period was among the highest in the five periods, with the deepest average storm depth in the summer and the fewest long duration (>45 day) dry intervals across all seasons. For other species-ecosystem combinations, two richness patterns were observed. Compared to AVG2, AVG1 had lower water-year precipitation yet more C3 species in upland grasslands, creosotebush, and mesquite shrublands, and more C4 perennial grasses in tarbush shrublands. AVG1 also had larger amounts of rainfall and more large storms in fall and spring with higher mean depths of storm and lower mean dry-day interval compared with AVG2. While DRY1 and DRY2 had the same amount of precipitation, DRY2 had more C4 species than DRY1 in creosote bush shrublands, and DRY1 had more C3 species than DRY2 in upland grasslands. Most differences in rainfall between these periods occurred in the summer. Legacy effects were observed for C3 species in upland grasslands where no significant change in richness occurred from DRY1 to WET compared with a 41% loss of species from the WET to DRY2 period. The opposite asymmetry pattern was found for C4 subdominant species in creosote bush and mesquite shrublands, where an increase in richness occurred from DRY1 to WET followed by no change in richness from WET to DRY2. Our results show that understanding plant biodiversity of Chihuahuan Desert landscapes as precipitation continues to change will require daily and seasonal metrics of rainfall within a wet-dry period paradigm, as well as a consideration of species traits (photosynthetic pathways, lifespan, morphologies). Understanding these relationships can provide insights into predicting species-level dynamics in drylands under a changing climate.

Precipitation-productivity relationships and the duration of precipitation anomalies: An underappreciated dimension of climate change

In terrestrial ecosystems, climate change forecasts of increased frequencies and magnitudes of wet and dry precipitation anomalies are expected to shift precipitation-net primary productivity (PPT-NPP) relationships from linear to nonlinear. Less understood, however, is how future changes in the duration of PPT anomalies will alter PPT-NPP relationships. A review of the literature shows strong potential for the duration of wet and dry PPT anomalies to impact NPP and to interact with the magnitude of anomalies. Within semi-arid and mesic grassland ecosystems, PPT gradient experiments indicate that short-duration (1 year) PPT anomalies are often insufficient to drive nonlinear aboveground NPP responses. But long-term studies, within desert to forest ecosystems, demonstrate how multi-year PPT anomalies may result in increasing impacts on NPP through time, and thus alter PPT-NPP relationships. We present a conceptual model detailing how NPP responses to PPT anomalies may amplify with the duration of an event, how responses may vary in xeric vs. mesic ecosystems, and how these differences are most likely due to demographic mechanisms. Experiments that can unravel the independent and interactive impacts of the magnitude and duration of wet and dry PPT anomalies are needed, with multi-site long-term PPT gradient experiments particularly well-suited for this task.

Increasing Summer Rainfall and Asymmetrical Diurnal and Seasonal Warming Enhanced Vegetation Greenness in Temperate Deciduous Forests and Grasslands of Northern China

Temperate forests and grasslands carry key ecosystem functions and provide essential services. Remote-sensing derived greenness has been widely used to assess the response of ecosystem function to climate and land-cover changes. Although reforestation and grassland restoration have been proposed to enhance the regional greenness in Northern China, the independent contribution of climate without the interference of land-cover change at meso and large scales has rarely been explored. To separate the impacts of climate change on vegetation greenness from those of land-cover/use change, we identified large patches of forests and grasslands in Northern China without land-cover/use changes in 2001–2015 and derived their greenness using MODIS enhanced vegetation index (EVI). We found that most deciduous-broadleaved forest patches showed greening, and the significant slope of the annual mean and maximum EVI are 3.97 ± 0.062 × 10−3 and 4.8 ± 0.116 × 10−3 yr−1, respectively. On the contrary, grassland patches showed great spatial heterogeneity and only those in the east showed greening. The partial correlation analysis between EVI and climate showed that the greening of grassland patches is primarily supported by the increased growing-season precipitation with mean significant coefficient of 0.72 ± 0.01. While wet-year (0.57 ± 0.01) and nongrowing-season precipitation (0.68 ± 0.01) significantly benefit greening of deciduous-broadleaved forests, the altered temperature seasonality modulates their greening spatial-heterogeneously. The increased growing-season minimum temperature might lengthen the growing season and contribute to the greening for the temperature-limited north as shown by positive partial correlation coefficient of 0.66 ± 0.01, but might elevate respiration and reduce greening of the forests in the south as shown by negative coefficient of −0.70 ± 0.01. Daytime warming in growing season is found to favor the drought-tolerant oak dominated forest in the south due to enhanced photosynthesis, but may not favor the forests dominated by less-drought-tolerant birch in the north due to potential water stress. Therefore, grassland greening was essentially promoted by the growing-season precipitation, however, in addition to being driven by precipitation, greening of deciduous forests was regulated spatial-heterogeneously by asymmetrical diurnal and seasonal warming which could be attributed to species composition.

Modifying connectivity to promote state change reversal: the importance of geomorphic context and plant-soil feedbacks

Alternative states maintained by feedbacks are notoriously difficult, if not impossible, to reverse. Although positive interactions that modify soil conditions may have the greatest potential to alter self-reinforcing feedbacks, the conditions leading to these state change reversals have not been resolved. In a 9-yr study, we modified horizontal connectivity of resources by wind or water on different geomorphic surfaces in an attempt to alter plant-soil feedbacks and shift woody-plant-dominated states back toward perennial grass dominance. Modifying connectivity resulted in an increase in litter cover regardless of the vector of transport (wind, water) followed by an increase in perennial grass cover 2 yr later. Modifying connectivity was most effective on sandy soils where wind is the dominant vector, and least effective on gravelly soils on stable surfaces with low sediment movement by water. We found that grass cover was related to precipitation in the first 5 yr of our study, and plant-soil feedbacks developed following 6 yr of modified connectivity to overwhelm effects of precipitation on sandy, wind-blown soils. These feedbacks persisted through time under variable annual rainfall. On alluvial soils, either plant-soil feedbacks developed after 7 yr that were not persistent (active soils) or did not develop (stable soils). This novel approach has application to drylands globally where desertified lands have suffered losses in ecosystem services, and to other ecosystems where connectivity-mediated feedbacks modified at fine scales can be expected to impact plant recovery and state change reversals at larger scales, in particular for wind-impacted sites.

Indirect effects of water availability in driving and predicting productivity in the Gobi desert

Climate is the fundamental determinant of plant metabolism and net primary productivity (NPP). However, whether climate drives NPP directly or indirectly is not well understand. The Gobi desert across a precipitation gradient in the arid zone provides an ideal naturally-controlled platform for studying the precipitation-productivity relationships. We conducted 3-year experiments in four Gobi desert shrublands across an aridity gradient in Gansu Province of China to test the relationship between water availability and shrub productivity as well as the relative importance of the possible factors driving productivity (using piecewise structural equation modeling) and to explore the appropriate variables for predicting productivity (using three spatial models). The results showed that water availability indirectly affected the NPP via stand biomass, while stand biomass had a significant direct effect on NPP regardless of whether the leaf water content and stand height were considered. The model based on stand size (71.6%) and the model that contained both stand size and water availability (72.3%) explained more of the variation in the water-NPP relationships than the model based on water availability (37.3%). Our findings suggest that even in extremely water-limited areas, the effects of water availability on plant growth and the kinetics of plant metabolism could be indirect via plant size, demonstrating the importance of plant size as an indicator of shrub productivity. This study explains the mechanisms underlying the NPP driving pattern and proposes a practical NPP model for arid ecosystems.

Crop Vulnerability to Weather and Climate Risk: Analysis of Interacting Systems and Adaptation Efficacy for Sustainable Crop Production

Climate change is increasing mean and extreme temperatures in the Southwestern United States, leading to a suite of changes affecting agricultural production. These include changes in water, soils, pathogens, weeds, and pests comprising the production environment. The aim of this synthesis is to describe the anticipated leading agricultural pressures and adaptive responses, many of which are near-term actions with longer-term consequences. In the semiarid Southwestern United States, climate change is expected to increase water scarcity. Surface water shortage is the leading reason for recent diminished crop yields in the Southwest. Drought and lack of water represent the leading regional weather-related cause of crop loss from 1989 to 2017. Thus, water scarcity has been and will continue to be a critical factor leading to regional crop vulnerability. Soils, pathogens, weeds, and insects are components of the agricultural production environment and are directly influenced by near-term weather and long-term climate conditions. Field crops, vegetable crops, and perennial crops have unique production requirements and diverse management options, many already used in farm management, to cope with production environment changes to build climate resilience. Farmers and ranchers continuously respond to changing conditions on a near-term basis. Long-term planning and novel adaptation measures implemented may now build nimble and responsive systems and communities able to cope with future conditions. While decision-support tools and resources are providing increasingly sophisticated approaches to cope with production in the 21st century, we strive to keep pace with the cascading barrage of inter-connected agricultural challenges.

Differing climate and landscape effects on regional dryland vegetation responses during wet periods allude to future patterns

Dryland vegetation is influenced by biotic and abiotic land surface template (LST) conditions and precipitation (PPT), such that enhanced vegetation responses to periods of high PPT may be shaped by multiple factors. High PPT stochasticity in the Chihuahuan Desert suggests that enhanced responses across broad geographic areas are improbable. Yet, multiyear wet periods may homogenize PPT patterns, interact with favorable LST conditions, and in this way produce enhanced responses. In contrast, periods containing multiple extreme high PPT pulse events could overwhelm LST influences, suggesting a divergence in how climate change could influence vegetation by altering PPT periods. Using a suite of stacked remote sensing and LST datasets from the 1980s to the present, we evaluated PPT-LST-Vegetation relationships across this region and tested the hypothesis that enhanced vegetation responses would be initiated by high PPT, but that LST favorability would underlie response magnitude, producing geographic differences between wet periods. We focused on two multiyear wet periods; one of above average, regionally distributed PPT (1990-1993) and a second with locally distributed PPT that contained two extreme wet pulses (2006-2008). 1990-1993 had regional vegetation responses that were correlated with soil properties. 2006-2008 had higher vegetation responses over a smaller area that were correlated primarily with PPT and secondarily to soil properties. Within the overlapping PPT area of both periods, enhanced vegetation responses occurred in similar locations. Thus, LST favorability underlied the geographic pattern of vegetation responses, whereas PPT initiated the response and controlled response area and maximum response magnitude. Multiyear periods provide foresight on the differing impacts that directional changes in mean climate and changes in extreme PPT pulses could have in drylands. Our study shows that future vegetation responses during wet periods will be tied to LST favorability, yet will be shaped by the pattern and magnitude of multiyear PPT events.

Impacts of grazing exclusion on productivity partitioning along regional plant diversity and climatic gradients in Tibetan alpine grasslands

The biodiversity-productivity relationship is critical for better predicting ecosystem responses to climate change and human disturbance. However, it remains unclear about the effects of climate change, land use shifts, plant diversity, and their interactions on productivity partitioning above- and below-ground components in alpine grasslands on the Tibetan Plateau. To answer this question, we conducted field surveys at 33 grazed vs. fenced paired sites that are distributed across the alpine meadow, steppe, and desert-steppe zones on the northern Tibetan Plateau in early August of 2010-2013. Generalized additive models (GAMs) showed that aboveground net primary productivity (ANPP) linearly increased with growing season precipitation (GSP) while belowground net primary productivity (BNPP) decreased with growing season temperature (GST). Compared to grazed sites, short-term fencing did not alter the patterns of ANPP along climatic gradients but tended to decrease BNPP at moderate precipitation levels of 200 mm < GSP <450 mm. We also found that ANPP and BNPP linearly increased with species richness, ANPP decreased with Shannon diversity index, and BNPP did not correlate with the Shannon diversity index. Fencing did not alter the relationships between productivity components and plant diversity indices. Generalized additive mixed models furtherly confirmed that the interaction of localized plant diversity and climatic condition nonlinearly regulated productivity partitioning of alpine grasslands in this area. Finally, structural equation models (SEMs) revealed the direction and strength of causal links between biotic and abiotic variables within alpine grassland ecosystems. ANPP was controlled directly by GSP (0.53) and indirectly via species richness (0.41) and Shannon index (-0.12). In contrast, BNPP was influenced directly by GST (-0.43) and indirectly by GSP via species richness (0.05) and Shannon index (-0.02). Therefore, we recommend using a joint approach of GAMs and SEMs for better understanding mechanisms behind the relationship between biodiversity and ecosystem function under climate change and human disturbance.

Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison

Given the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.

Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods

There is considerable uncertainty in the magnitude and direction of changes in precipitation associated with climate change, and ecosystem responses are also uncertain. Multiyear periods of above- and below-average rainfall may foretell consequences of changes in rainfall regime. We compiled long-term aboveground net primary productivity (ANPP) and precipitation (PPT) data for eight North American grasslands, and quantified relationships between ANPP and PPT at each site, and in 1-3 year periods of above- and below-average rainfall for mesic, semiarid cool, and semiarid warm grassland types. Our objective was to improve understanding of ANPP dynamics associated with changing climatic conditions by contrasting PPT-ANPP relationships in above- and below-average PPT years to those that occurred during sequences of multiple above- and below-average years. We found differences in PPT-ANPP relationships in above- and below-average years compared to long-term site averages, and variation in ANPP not explained by PPT totals that likely are attributed to legacy effects. The correlation between ANPP and current- and prior-year conditions changed from year to year throughout multiyear periods, with some legacy effects declining, and new responses emerging. Thus, ANPP in a given year was influenced by sequences of conditions that varied across grassland types and climates. Most importantly, the influence of prior-year ANPP often increased with the length of multiyear periods, whereas the influence of the amount of current-year PPT declined. Although the mechanisms by which a directional change in the frequency of above- and below-average years imposes a persistent change in grassland ANPP require further investigation, our results emphasize the importance of legacy effects on productivity for sequences of above- vs. below-average years, and illustrate the utility of long-term data to examine these patterns.

Breaks in MODIS time series portend vegetation change: verification using long-term data in an arid grassland ecosystem

Frequency and severity of extreme climatic events are forecast to increase in the 21st century. Predicting how managed ecosystems may respond to climatic extremes is intensified by uncertainty associated with knowing when, where, and how long effects of extreme events will be manifest in an ecosystem. In water-limited ecosystems with high inter-annual variability in rainfall, it is important to be able to distinguish responses that result from seasonal fluctuations in rainfall from long-term directional increases or decreases in precipitation. A tool that successfully distinguishes seasonal from directional biomass responses would allow land managers to make informed decisions about prioritizing mitigation strategies, allocating human resource monitoring efforts, and mobilizing resources to withstand extreme climatic events. We leveraged long-term observations (2000-2013) of quadrat-level plant biomass at multiple locations across a semiarid landscape in southern New Mexico to verify the use of Normalized Difference Vegetation Index (NDVI) time series derived from 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) data as a proxy for changes in aboveground productivity. This period encompassed years of sustained drought (2000-2003) and record-breaking high rainfall (2006 and 2008) followed by subsequent drought years (2011 through 2013) that resulted in a restructuring of plant community composition in some locations. Our objective was to decompose vegetation patterns derived from MODIS NDVI over this period into contributions from (1) the long-term trend, (2) seasonal cycle, and (3) unexplained variance using the Breaks for Additive Season and Trend (BFAST) model. BFAST breakpoints in NDVI trend and seasonal components were verified with field-estimated biomass at 15 sites that differed in species richness, vegetation cover, and soil properties. We found that 34 of 45 breaks in NDVI trend reflected large changes in mean biomass and 16 of 19 seasonal breaks accompanied changes in the contribution to biomass by perennial and/or annual grasses. The BFAST method using satellite imagery proved useful for detecting previously reported ground-based changes in vegetation in this arid ecosystem. We demonstrate that time series analysis of NDVI data holds potential for monitoring landscape condition in arid ecosystems at the large spatial scales needed to differentiate responses to a changing climate from responses to seasonal variability in rainfall.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.