Vegetation Dynamics In Drylands Research Articles

The complex relationship between precipitation and productivity in drylands

Abstract Drylands provide multiple essential services to human society, and dryland vegetation is one of the foundations of these services. There is a paradox, however, in the vegetation productivity–precipitation relationship in drylands. Although water is the most limiting resource in these systems, a strong relationship between precipitation and productivity does not always occur. Such a paradox affects our understanding of dryland vegetation dynamics and hinders our capacity to predict dryland vegetation responses under future climates. In this perspective, we examine the possible causes of the dryland precipitation–productivity paradox. We argue that the underlying reasons depend on the location and scale of the study. Sometimes multiple factors may interact, resulting in a less significant relationship between vegetation growth and water availability. This means that when we observe a poor correlation between vegetation growth and water availability, there are potentially missing sources of water input or a lack of consideration of other important processes. The paradox could also be related to the inaccurate measurement of vegetation productivity and water availability indicators. Incorporating these complexities into predictive models will help us better understand the complex relationship between water availability and dryland ecosystem processes and improve our ability to predict how these ecosystems will respond to the multiple facets of climate change.

Changes in vegetation in China's drylands are closely related to afforestation compared with climate change

The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0–7 cm], shallow [7–28 cm], and middle [28–100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0–28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %–71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under global warming.

Dynamics of global dryland vegetation were more sensitive to soil moisture: Evidence from multiple vegetation indices

The prominent role of drylands in the global ecosystem calls for a deeper understanding of the responses of dryland vegetation to ongoing environmental drivers in the context of global climate change. Here, we first investigated the spatial and temporal trends of global dryland vegetation based on multiple satellite- and model-based indices, including the normalized difference vegetation index (NDVI), leaf area index (LAI), vegetation optical depth (VOD), and gross primary productivity (GPP) during 1988–2018. Then, the impacts of a set of environmental drivers (i.e. mean annual precipitation (MAP), mean annual temperature (MAT), soil moisture (SM), and vapor pressure deficit (VPD)) on vegetation dynamics were quantified using partial correlation analysis and structural equation model. All four indices increased strongly before 2000 but slowed afterward. The variation in dryland vegetation was more related to SM anomaly in comparison with other environmental drivers. The variation induced by SM was amplified by high VOD in some continents. Furthermore, MAT contributed similarly as SM to vegetation dynamics in North America. The four vegetation indices exhibited divergent responses to environmental drivers due to their characteristics. At the continental scale, NDVI was only relevant to variation in VPD in North America. In contrast to NDVI, LAI, and VOD, GPP was more closely associated with the variation in SM and VPD. Roughly half of the GPP variation was attributable to the combination of SM and MAT in North America and Australia, whereas they have low predictive power (∼30%) in Eurasia, Africa, and South America. SM was closely linked to the vegetation changes in grasslands and shrublands; however, this impact varied among the continents. Our results advance the current understanding of dryland vegetation dynamics and shed new light on improving dryland carbon flux simulation by fully considering the role of soil moisture.

Effect of nonlocal grazing on dry-land vegetation dynamics.

Dry-land ecosystems have become a matter of grave concern, due to the growing threat of land degradation and bioproductivity loss. Self-organized vegetation patterns are a remarkable characteristic of these ecosystems; apart from being visually captivating, patterns modulate the system response to increasing environmental stress. Empirical studies hinted that herbivory is one the key regulatory mechanisms behind pattern formation and overall ecosystem functioning. However, most of the mathematical models have taken a mean-field strategy to grazing; foraging has been considered to be independent of spatial distribution of vegetation. To this end, an extended version of the celebrated plant-water model due to Klausmeier has been taken as the base here. To encompass the effect of heterogeneous vegetation distribution on foraging intensity and subsequent impact on entire ecosystem, grazing is considered here to depend on spatially weighted average vegetation density instead of density at a particular point. Moreover, varying influence of vegetation at any location over gazing elsewhere is incorporated by choosing a suitable averaging function. A comprehensive analysis demonstrates that inclusion of spatial nonlocality alters the understanding of system dynamics significantly. The grazing ecosystem is found to be more resilient to increasing aridity than it was anticipated to be in earlier studies on nonlocal grazing. The system response to rising environmental pressure is also observed to vary depending on the grazer. Obtained results also suggest the possibility of multistability due to the history dependence of the system response. Overall, this work indicates that the spatial heterogeneity in grazing intensity has a decisive role to play in the functioning of water-limited ecosystems.

Dynamic traceability effects of soil moisture on the precipitation–vegetation association in drylands

Vegetation growth is critical in characterizing ecosystem carbon sequestration. Water availability profoundly affects the interaction between climate change and vegetation dynamics in drylands. However, the associations of the precipitation–vegetation index (PRE-VI) and temperature–vegetation index (TEM-VI) as well as whether and how the soil moisture modulates PRE-VI and TEM-VI are still unclear. Precipitation contributed substantially much more to vegetation dynamics than temperature, and PRE-VI associations were greater in the Southern Hemisphere than those in the Northern Hemisphere in global drylands. The traceability effects of soil moisture on PRE-VI and TEM-VI were investigated, and a convex shape was observed for PRE-VI as soil moisture increased, but not significant trend for TEM-VI. It showed that moderate soil moisture enhanced PRE-VI associations through the maintenance of reasonable surface–atmosphere feedback to counteract the balance of plant growth and energy collocation. In the past three decades, PRE-VI associations decreased with the increase in soil moisture, suggesting the consistency of the spatial and temporal pattern of the effect of soil moisture on PRE-VI associations in water-limited ecosystems. Our results implied that changes in soil moisture reflect changes in climate–vegetation associations and can guide nature-based solutions to improve ecosystem carbon sink.

Remotely‐sensed slowing down in spatially patterned dryland ecosystems

Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer‐term in situ data. Here, we evaluate the theoretical prediction that regular vegetation patterns are associated with empirically derived temporal indicators (autocorrelation, variance, responsiveness) of critical slowing down in a dryland ecosystem in Sudan using different remote sensing products.We use recently developed methods using remote‐sensing EVI time‐series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test the predicted slowing down. We tested our empirical findings against theoretical predictions from a stochastic version of a spatial explicit model that has been used to describe vegetation dynamics in drylands under aridity stress.Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non‐linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non‐linear way.Our findings suggest that spatial self‐organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non‐linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

Quantitative Analysis of Natural and Anthropogenic Factors Influencing Vegetation NDVI Changes in Temperate Drylands from a Spatial Stratified Heterogeneity Perspective: A Case Study of Inner Mongolia Grasslands, China

The detection and attribution of vegetation dynamics in drylands is an important step for the development of effective adaptation and mitigation strategies to combat the challenges posed by human activities and climate change. However, due to the spatial heterogeneity and interactive influences of various factors, quantifying the contributions of driving forces on vegetation change remains challenging. In this study, using the normalized difference vegetation index (NDVI) as a proxy of vegetation growth status and coverage, we analyzed the temporal and spatial characteristics of the NDVI in China’s Inner Mongolian grasslands using Theil–Sen slope statistics and Mann–Kendall trend test methods. In addition, using the GeoDetector method, a spatially-based statistical technique, we assessed the individual and interactive influences of natural factors and human activities on vegetation-NDVI change. The results show that the growing season average NDVI exhibited a fluctuating upward trend of 0.003 per year from 2000 to 2018. The areas with significant increases in NDVI (p &lt; 0.05) accounted for 45.63% of the entire region, and they were mainly distributed in the eastern part of the Mu Us sandy land and the eastern areas of the Greater Khingan Range. The regions with a decline in the NDVI were mainly distributed in the central and western regions of the study area. The GeoDetector results revealed that both natural and human factors had significant impacts on changes in the NDVI (p &lt; 0.001). Precipitation, livestock density, wind speed, and population density were the dominant factors affecting NDVI changes in the Inner Mongolian grasslands, explaining more than 15% of the variability, while the contributions of the two topography factors (terrain slope and slope aspect) were relatively low (less than 2%). Furthermore, NDVI changes responded to the changes in the level of specific influencing factors in a nonlinear way, and the interaction of two factors enhanced the effect of each singular factor. The interaction between precipitation and temperature was the highest among all factors, accounting for 39.3% of NDVI variations. Findings from our study may aid policymakers in better understanding the relative importance of various factors and the impacts of the interactions between factors on vegetation change, which has important implications for preventing and mitigating land degradation and achieving sustainable pasture use in dryland ecosystems.

Response of dryland vegetation under extreme wet events with satellite measures of greenness and fluorescence

Extreme wet events in central Australia triggered large vegetation responses that contributed greatly to large global land carbon sink anomalies. There remain significant uncertainties on the extent to which these events over dryland vegetation can be monitored and assessed with satellite data. In this study, we investigated the vegetation responses of the major Australian semiarid biomes to two extreme wet events utilizing multi-satellite observations of (1) solar-induced chlorophyll fluorescence (SIF), as a proxy for photosynthetic activity and (2) the enhanced vegetation index (EVI), as a measure of canopy chlorophyll or greenness. We related these satellite observations with gross primary productivity (GPP) estimated from eddy covariance tower sites, as a performance benchmark.The C3-dominated Mulga woodland was the most responsive biome to both wet pulses and exhibited the highest sensitivity to soil moisture. The C4-dominated Hummock grassland was more responsive to the 2011 “big wet” event, relative to the later 2016–2017 wet pulse. EVI swiftly responded to the extreme wet events and showed markedly amplified seasonal amplitude, however, there was a time lag as compared with SIF during the post-wet period, presumably due to the relatively slower chlorophyll degradation in contrast with declines in photosynthetic activity. Despite a robust linear SIF-GPP relationship (r2 ranging from 0.59 to 0.85), the spatially coarse SIF derived from the Global Ozone Monitoring Experiment-2 (GOME-2) yielded high retrieval noise over the xeric biomes, hindering its capacity to capture thoroughly the dryland vegetation dynamics in central Australia. Our study highlights that synchronous satellite observations of greenness and fluorescence can potentially offer an improved understanding of dryland vegetation dynamics and can advance our ability to detect ecosystem alterations under future changing climates.

Disentangling the independent effects of vegetation cover and pattern on runoff and sediment yield in dryland systems – Uncovering processes through mimicked plant patches

There is strong empirical evidence on the importance of the spatial pattern of vegetation in dryland hydrologic and geomorphologic dynamics. However, changes in vegetation cover and spatial pattern are often linked, making it difficult to disentangle and assess their independent hydro-geomorphologic roles. We used synthetic sponges placed on the soil surface to mimic the aboveground structure of vegetation patches, and manipulated patch cover and pattern as well as the sink capacity of the patches on a set of 24 (2 × 1 m) runoff plots. Combining natural-rainfall and simulated-rainfall experiments, we aimed to test that (1) both vegetation cover and pattern independently control runoff and sediment yield; (2) for any given cover, coarsening the vegetation pattern entails increasing runoff and sediment yield; and (3) pattern effect is mostly exerted by modulating the source-sink dynamics of the system. We found that increasing either patch cover or patch density decreased runoff and sediment yields from natural rainfalls, yet the effect of patch density largely disappeared when the effect of the co-varying patch cover was removed. Simulated-rainfall experiments on plots with equal medium-low patch cover showed however that coarser patterns (lower patch density; higher patch size) increased runoff coefficients and reduced time to runoff as compared with finer patterns. The effect of patch density was particularly clear when the sink function of vegetation patches was also mimicked. Rainfall interception and direct soil protection proved to be critical mechanisms underlying the effects of patch cover, yet they barely contributed to the effects of patch pattern. The control of overland flow by patch pattern was exerted through changes in the level of runoff disruption. However, physical obstructions to runoff hardly reduced runoff unless coupled to mimicked soil sinks. Overall this work demonstrates the independent effects of patch cover and pattern on the hydro-geomorphologic functioning of patchy landscapes, with patch cover being the primary hydrologic control factor and patch pattern exhibiting its full potential for low and medium low patch cover values. Our findings provide useful information for modelling and understanding dryland vegetation dynamics, and for designing management and restoration measures that take into account the critical role played by source-sink dynamics and hydrological connectivity in dryland landscapes.

Species interactions across trophic levels mediate rainfall effects on dryland vegetation dynamics

AbstractArid ecosystems are strongly limited by water availability, and precipitation plays a major role in the dynamics of all species in arid regions, as well as the ecosystem processes that occur there. However, understanding how biotic interactions mediate long‐term responses of dryland ecosystems to rainfall remains very fragmented. We report on a unique large‐scale field experiment spanning 25 yr and three trophic levels (plants, small mammal herbivores, predators) in a dryland ecosystem in the northern Chilean Mediterranean Region where we assessed how biotic interactions influence the long‐term plant community responses to precipitation. As the most persistent ecological changes in dryland systems may result from changes in the structure, cover, and composition of the perennial vegetation, we emphasized the interplay between bottom‐up and top‐down controls of perennial plants in our analyses. Rainfall was the primary factor affecting the dynamics of, and interactions among, plants and small mammals. Ephemeral plant cover dynamics closely tracked short‐term annual rainfall, but seemed unaffected by top‐down controls (herbivory). In contrast, the response of the perennial plant cover to precipitation was mediated by (1) a complex interplay between subtle top‐down (herbivory) controls that become more apparent in the long‐term, (2) competition with ephemeral plants during wet years, and (3) an indirect effect of predators on subdominant shrubs and perennial herbs. This long‐term field experiment highlights how climate‐induced responses of arid perennial vegetation are influenced by interactions across trophic levels and temporal scales. In the face of global change, understanding how multi‐trophic controls mediate dryland vegetation responses to climate is essential to properly managing the conservation of biodiversity in arid systems.

Indirect facilitation drives species composition and stability in drylands

Dryland ecosystems are likely to respond discontinuously to gradual changes in environmental conditions. Direct facilitation between plants, whereby plants improve the local environmental conditions for others, has been shown to be a mechanism contributing to these discontinuous ecosystem transitions. Theoretical models describing dryland vegetation dynamics often consider a single plant species and one type of facilitation, namely direct facilitation. However, another type of facilitation–indirect facilitation–is widespread in dryland ecosystems as well; it is performed by plants protected against grazing, the nurses, when this protection extends to other plants growing in their neighbourhood that are deprived of such protection, the protegees. Little is known about the long-term effects of indirect facilitation on dryland dynamics. Here, we developed and analysed a theoretical model including two species–a nurse and a protegee–and indirect facilitation through grazing. We investigated the effects of indirect facilitation on species composition, species spatial clustering and the stability of dryland ecosystems. We showed that indirect facilitation through grazing enables the stable coexistence of the nurse and the protegee and allows the reversibility of the protegee extinction. Surprisingly, the strength of indirect facilitation affected neither the total nor the interspecific vegetation clustering. Our study highlights that spatially explicit grazing protection may affect species composition and the stability of dryland ecosystems and gives hints about how species interactions translate into spatial clustering.

Formation of localized states in dryland vegetation: Bifurcation structure and stability.

We study theoretically the emergence of localized states of vegetation close to the onset of desertification. These states are formed through the locking of vegetation fronts, connecting a uniform vegetation state with a bare soil state, which occurs nearby the Maxwell point of the system. To study these structures we consider a universal model of vegetation dynamics in drylands, which has been obtained as the normal form for different vegetation models. Close to the Maxwell point localized gaps and spots of vegetation exist and undergo collapsed snaking. The presence of gaps strongly suggest that the ecosystem may undergo a recovering process. In contrast, the presence of spots may indicate that the ecosystem is close to desertification.

Ecohydrological effects of biocrust type on restoration dynamics in drylands

Global climate change influences not only vascular plants, but also biological soil crusts (biocrusts), which play important roles in dryland vegetation dynamics by redistributing rainfall in soils. Different types of biocrusts, spanning a spectrum from cyanobacteria-dominated and moss-dominated, have distinct roles in rainfall redistribution patterns, but the ecohydrological effects of different biocrust types on dryland ecosystem dynamics remain largely unclear. This study developed an ecohydrological model with biocrust as a system state variable to explicitly explore the effects of different biocrust types on dryland vegetation dynamics in Shapotou region in northern China, particularly after restoration. The results indicated that both cyanobacteria- and moss-dominated biocrusts could support high grass cover (approximately 40%) after restoration. Cyanobacterial, but not moss biocrusts, could also maintain a high level of shrub cover (13 and 3%, respectively). Shifting from cyanobacteria to mosses gradually increased the biocrust cover from approximately 40% to 80%. The biocrust's water-holding capacity (the volume of water it can intercept per unit area) is likely be able to explain the dynamics of biocrust and shrub cover (with correlation efficiency of R2 = 0.972 and 0.987, respectively), but not grass cover (R2 = 0.224). The findings suggest that biocrust type may significantly affect coverage of biocrusts and shrubs, but not grass coverage, and global climate change may influence dryland restoration by altering biocrust types.

A new approach for biocrust and vegetation monitoring in drylands using multi-temporal Sentinel-2 images

Drylands, one of the planet’s largest terrestrial biomes, are suggested to be greatly threatened by climate change. Drylands are usually sparsely vegetated, and biological soil crusts (biocrusts) – that is, soil surface communities of cyanobacteria, mosses and/or lichens – can cover up to 70% of dryland cover. As they control key ecosystem processes, monitoring their spatial and temporal distribution can provide highly valuable information. In this study, we examine the potential of European Space Agency’s (ESA) Sentinel-2 (S2) data to characterize the spatial and temporal development of biocrust and vascular plant greening along a rainfall gradient of the Negev Desert (Israel). First, the chlorophyll a absorption feature in the red region (CRred) was identified as the index mostly sensitive to changes in biocrust greening but minimally affected by changes in soil moisture. This index was then computed on the S2 images and enabled monitoring the phenological dynamics of different dryland vegetation components from August 2015 to August 2017. The analysis of multi-temporal S2 images allowed us to successfully track the biocrust greening within 15 days from the first seasonal rain events in the north of Negev, and to identify the maximum development of annual vascular plants and greening of perennial ones. These results show potential for monitoring arid and semi-arid environments using the newly available S2 images, allowing new insights into dryland vegetation dynamics.

The impact of fog on soil moisture dynamics in the Namib Desert

Abstract Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014–Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015–Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel

Abstract Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992–2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas.

Localized states qualitatively change the response of ecosystems to varying conditions and local disturbances

The response of dynamical systems to varying conditions and disturbances is a fundamental aspect of their analysis. In spatially extended systems, particularly in pattern-forming systems, there are many possible responses, including critical transitions, gradual transitions and locally confined responses. Here, we use the context of vegetation dynamics in drylands in order to study the response of pattern-forming ecosystems to oscillating precipitation and local disturbances. We focus on two precipitation ranges, a bistability range of bare soil with a patterned vegetation state, and a bistability range of uniform vegetation with a patterned vegetation state. In these ranges, there are many different stable states, which allow for both abrupt and gradual transitions between the system states to occur. We find that large amplitude oscillations of the precipitation rate can lead to a collapse of the vegetation in one range, while in the other range, they result in the convergence to a patterned state with a preferred wavelength. In addition, we show that a series of local disturbances results in the collapse of the vegetation in one range, while it drives the system toward fluctuations around a finite average biomass in the other range. Moreover, it is shown that under certain conditions, local disturbances can actually increase the overall vegetation density. These significant differences in the system response are attributed to the existence of localized states in one of the bistability ranges.

Global changes in dryland vegetation dynamics (1988–2008) assessed by satellite remote sensing: comparing a new passive microwave vegetation density record with reflective greenness data

Abstract. Drylands, covering nearly 30% of the global land surface, are characterized by high climate variability and sensitivity to land management. Here, two satellite-observed vegetation products were used to study the long-term (1988–2008) vegetation changes of global drylands: the widely used reflective-based Normalized Difference Vegetation Index (NDVI) and the recently developed passive-microwave-based Vegetation Optical Depth (VOD). The NDVI is sensitive to the chlorophyll concentrations in the canopy and the canopy cover fraction, while the VOD is sensitive to vegetation water content of both leafy and woody components. Therefore it can be expected that using both products helps to better characterize vegetation dynamics, particularly over regions with mixed herbaceous and woody vegetation. Linear regression analysis was performed between antecedent precipitation and observed NDVI and VOD independently to distinguish the contribution of climatic and non-climatic drivers in vegetation variations. Where possible, the contributions of fire, grazing, agriculture and CO2 level to vegetation trends were assessed. The results suggest that NDVI is more sensitive to fluctuations in herbaceous vegetation, which primarily uses shallow soil water, whereas VOD is more sensitive to woody vegetation, which additionally can exploit deeper water stores. Globally, evidence is found for woody encroachment over drylands. In the arid drylands, woody encroachment appears to be at the expense of herbaceous vegetation and a global driver is interpreted. Trends in semi-arid drylands vary widely between regions, suggesting that local rather than global drivers caused most of the vegetation response. In savannas, besides precipitation, fire regime plays an important role in shaping trends. Our results demonstrate that NDVI and VOD provide complementary information and allow new insights into dryland vegetation dynamics.

Feedbacks between vegetation pattern and resource loss dramatically decrease ecosystem resilience and restoration potential in a simple dryland model

Conceptual frameworks of dryland degradation commonly include ecohydrological feedbacks between landscape spatial organization and resource loss, so that decreasing cover and size of vegetation patches result in higher water and soil losses, which lead to further vegetation loss. However, the impacts of these feedbacks on dryland dynamics in response to external stress have barely been tested. Using a spatially-explicit model, we represented feedbacks between vegetation pattern and landscape resource loss by establishing a negative dependence of plant establishment on the connectivity of runoff-source areas (e.g., bare soils). We assessed the impact of various feedback strengths on the response of dryland ecosystems to changing external conditions. In general, for a given external pressure, these connectivity-mediated feedbacks decrease vegetation cover at equilibrium, which indicates a decrease in ecosystem resistance. Along a gradient of gradual increase of environmental pressure (e.g., aridity), the connectivity-mediated feedbacks decrease the amount of pressure required to cause a critical shift to a degraded state (ecosystem resilience). If environmental conditions improve, these feedbacks increase the pressure release needed to achieve the ecosystem recovery (restoration potential). The impact of these feedbacks on dryland response to external stress is markedly non-linear, which relies on the non-linear negative relationship between bare-soil connectivity and vegetation cover. Modelling studies on dryland vegetation dynamics not accounting for the connectivity-mediated feedbacks studied here may overestimate the resistance, resilience and restoration potential of drylands in response to environmental and human pressures. Our results also suggest that changes in vegetation pattern and associated hydrological connectivity may be more informative early-warning indicators of dryland degradation than changes in vegetation cover.

Dynamical effects of the statistical structure of annual rainfall on dryland vegetation

AbstractIn this study, we extend a model of daily dryland dynamics by parameterizing a modified version of a minimalistic annual model to examine how the statistical structure of annual rainfall and grazing intensity interact to influence dryland vegetation. With a Monte Carlo approach, an ensemble outcome provides a statistical description of likely dryland vegetation dynamics responding to variations in rainfall structure and grazing intensity. Results suggest that increased rainfall variability decreases the average and increases the variability of grass cover leading to more frequent degradation of the grass resource. Vegetation of drier regions is found to be more sensitive to interannual variability in rainfall. Concentrating this variability into an organized periodic mode further decreases the mean and increases the variability of grass cover. Hence, a shift toward lower, more variable, or more inter‐annually correlated annual rainfall will likely lead to a general decrease in the grass resource and increased dryland vulnerability to degradation.Higher grazing intensity or lower annual rainfall both lead to more frequent and longer duration degradation of the grass condition. We note an interesting interaction in the response of grass biomass to grazing intensity and rainfall variability, where increased rainfall variability leads to longer duration degradation for low grazing, but shorter periods of degradation for high grazing. Once grass reaches a degraded condition, we find that woody vegetation strongly suppresses recovery even if successive rainfall is high. Overall, these findings suggest that the projected increase in interannual rainfall variability will likely decrease grass cover and potentially lead to more frequent, longer lasting degradation of dryland vegetation, particularly if enhanced rainfall variability is concentrated in long period (e.g. decadal) modes.