An asymmetry in wave scaling drives outsized quantities of coastal wetland erosion.

Wetland shorelines around the world are susceptible to wave erosion. Previous work has suggested that the lateral erosion rate of their cliff-like edges can be predicted as a function of intercepting waves, and yet numerous field studies have shown that other factors, for example, tidal currents or mass wasting of differing soil types, induce a wide range of variability. Our objective was to isolate the unique effects of wave heights, wavelengths, and water depths on lateral erosion rates and then synthesize a mechanistic understanding that can be applied globally. We found a potentially universal relationship, where the lateral erosion rates increase exponentially as waves increase in height but decrease exponentially as waves become longer in length. These findings suggest that wetlands and other sheltered coastlines likely experience outsized quantities of erosion, as compared to oceanic-facing coastlines.

Ecohydrology 2.0.

This paper aims at a definition of the domain of ecohydrology, a relatively new discipline borne out of an intrusion-as advertised by this Topical Collection of the Rendiconti Lincei-of hydrology and geomorphology into ecology (or vice-versa, depending on the reader's background). The study of hydrologic controls on the biota proves, in our view, significantly broader than envisioned by its original focus that was centered on the critical zone where much of the action of soil, climate and vegetation interactions takes place. In this review of related topics and contributions, we propose a reasoned broadening of perspective, in particular by firmly centering ecohydrology on the fluvial catchment as its fundamental control volume. A substantial unity of materials and methods suggests that our advocacy may be considered legitimate.

Variability of ecosystem carbon source from microbial respiration is controlled by rainfall dynamics.

Soil heterotrophic respiration (Rh) represents an important component of the terrestrial carbon cycle that affects whether ecosystems function as carbon sources or sinks. Due to the complex interactions between biological and physical factors controlling microbial growth, Rh is uncertain and difficult to predict, limiting our ability to anticipate future climate trajectories. Here we analyze the global FLUXNET 2015 database aided by a probabilistic model of microbial growth to examine the ecosystem-scale dynamics of Rh and identify primary predictors of its variability. We find that the temporal variability in Rh is consistently distributed according to a Gamma distribution, with shape and scale parameters controlled only by rainfall characteristics and vegetation productivity. This distribution originates from the propagation of fast hydrologic fluctuations on the slower biological dynamics of microbial growth and is independent of biome, soil type, and microbial physiology. This finding allows us to readily provide accurate estimates of the mean Rh and its variance, as confirmed by a comparison with an independent global dataset. Our results suggest that future changes in rainfall regime and net primary productivity will significantly alter the dynamics of Rh and the global carbon budget. In regions that are becoming wetter, Rh may increase faster than net primary productivity, thereby reducing the carbon storage capacity of terrestrial ecosystems.

Microclimate feedbacks sustain power law clustering of encroaching coastal woody vegetation.

The spatial pattern of vegetation patchiness may follow universal characteristic rules when the system is close to critical transitions between alternative states, which improves the anticipation of ecosystem-level state changes which are currently difficult to detect in real systems. However, the spatial patterning of vegetation patches in temperature-driven ecosystems have not been investigated yet. Here, using high-resolution imagery from 1972 to 2013 and a stochastic cellular automata model, we show that in a North American coastal ecosystem where woody plant encroachment has been happening, the size distribution of woody patches follows a power law when the system approaches a critical transition, which is sustained by the local positive feedbacks between vegetation and the surrounding microclimate. Therefore, the observed power law distribution of woody vegetation patchiness may be suggestive of critical transitions associated with temperature-driven woody plant encroachment in coastal and potentially other ecosystems.

Probabilistic structure of events controlling the after-storm recovery of coastal dunes.

Coastal dunes protect beach communities and ecosystems from rising seas and storm flooding and influence the stability of barrier islands by preventing overwashes and limiting barrier migration. Therefore, the degree of dune recovery after a large storm provides a simple measure of the short-term resiliency (and potential long-term vulnerability) of barrier islands to external stresses. Dune recovery is modulated by low-intensity/high-frequency high-water events (HWEs), which remain poorly understood compared to the low-frequency extreme events eroding mature dunes and dominating the short-term socio-economic impacts on coastal communities. Here, we define HWEs and analyze their probabilistic structure using time series of still-water level and deep-water wave data from multiple locations around the world. We find that HWEs overtopping the beach can be modeled as a marked Poisson process with exponentially distributed sizes or marks and have a mean size that varies surprisingly little with location. This homogeneity of global HWEs is related to the distribution of the extreme values of a wave-runup parameter, [Formula: see text], defined in terms of deep-water significant wave height [Formula: see text] and peak wavelength [Formula: see text] Furthermore, the characteristic beach elevation at any given location seems to be tied to a constant HWE frequency of about one event per month, which suggests a stochastic dynamics behind beach stabilization. Our results open the door to the development of stochastic models of beach, dune, and barrier dynamics, as well as a better understanding of wave-driven nuisance flooding.

Stochastic dynamics of barrier island elevation.

Barrier islands are ubiquitous coastal features that create low-energy environments where salt marshes, oyster reefs, and mangroves can develop and survive external stresses. Barrier systems also protect interior coastal communities from storm surges and wave-driven erosion. These functions depend on the existence of a slowly migrating, vertically stable barrier, a condition tied to the frequency of storm-driven overwashes and thus barrier elevation during the storm impact. The balance between erosional and accretional processes behind barrier dynamics is stochastic in nature and cannot be properly understood with traditional continuous models. Here we develop a master equation describing the stochastic dynamics of the probability density function (PDF) of barrier elevation at a point. The dynamics are controlled by two dimensionless numbers relating the average intensity and frequency of high-water events (HWEs) to the maximum dune height and dune formation time, which are in turn a function of the rate of sea level rise, sand availability, and stress of the plant ecosystem anchoring dune formation. Depending on the control parameters, the transient solution converges toward a high-elevation barrier, a low-elevation barrier, or a mixed, bimodal, state. We find the average after-storm recovery time-a relaxation time characterizing barrier's resiliency to storm impacts-changes rapidly with the control parameters, suggesting a tipping point in barrier response to external drivers. We finally derive explicit expressions for the overwash probability and average overwash frequency and transport rate characterizing the landward migration of barriers.

Spatial patterning among savanna trees in high-resolution, spatially extensive data.

In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.

Tree clusters in savannas result from islands of soil moisture.

Tree clusters in savannas are commonly found in sizes that follow power laws with well-established exponents. We show that their size distributions could result from the space-time probabilistic structure of soil moisture, estimated over the range of rainfall observed in semiarid savannas; patterns of soil moisture display islands whose size, for moisture thresholds above the mean, follows power laws. These islands are the regions where trees are expected to exist and they have a fractal structure whose perimeter-area relationship is the same as observed in field data for the clustering of trees. When the impact of fire and herbivores is accounted for, as acting through the perimeter of the tree clusters, the power law of the soil moisture islands is transformed into a power law with the same exponents observed in the tree cluster data.

Evolving biodiversity patterns in changing river networks.

Biodiversity patterns are governed by landscape structure and dispersal strategies of residing organisms. Landscape, however, changes, and dispersal strategies evolve with it. It is unclear how these biological and geomorphological changes interplay to affect biodiversity patterns. Here we develop metacommunity models that allow for dispersal evolution and implement them in river networks with different structures, mimicking the geomorphological dynamics of fluvial landscape. For a given dispersal kernel, a more compact network structure, where local communities are closer to one another, results in biodiversity patterns characteristic of a more well-mixed environment. When dispersal evolution is present, however, organisms adopt more local dispersal strategies in a more compact network, counteracting the effects of the more well-mixed environment. The combined effects lead to biodiversity patterns different from when dispersal evolution is absent. These findings underscore the importance of taking the interplay between the evolution of dispersal, landscape, and biodiversity patterns into account when studying and managing biodiversity in changing landscape.

Water-limited vegetated ecosystems driven by stochastic rainfall: feedbacks and bimodality.

In arid or semi-arid ecosystems, water availability is one of the primary controls on vegetation growth. When subsurface water resources are unavailable, the vegetation growth is dictated by the rainfall, and the random nature of the rainfall arrivals and quantities induces a probability distribution of soil moisture and vegetation biomass via the coupled dynamic equations of biomass balance and water balance. We have previously obtained an exact solution for these distributions under certain conditions, and shown that the mapping of rainfall variability to observed biomass variability can be successfully applied to a field site. Here, we expand upon our earlier theoretical work to show how the dynamics can give rise to more complicated, bimodal (and multimodal) structures in the biomass distribution when positive feedbacks between growth and water availability are included. We also derive some new analytical results for the crossing properties of this system, which enable us to determine on what time scale the effects of these feedbacks will be felt, and, relatedly, how long the system will take to cross between different modes.

River networks as ecological corridors: A coherent ecohydrological perspective.

This paper draws together several lines of argument to suggest that an ecohydrological framework, i.e. laboratory, field and theoretical approaches focused on hydrologic controls on biota, has contributed substantially to our understanding of the function of river networks as ecological corridors. Such function proves relevant to: the spatial ecology of species; population dynamics and biological invasions; the spread of waterborne disease. As examples, we describe metacommunity predictions of fish diversity patterns in the Mississippi-Missouri basin, geomorphic controls imposed by the fluvial landscape on elevational gradients of species' richness, the zebra mussel invasion of the same Mississippi-Missouri river system, and the spread of proliferative kidney disease in salmonid fish. We conclude that spatial descriptions of ecological processes in the fluvial landscape, constrained by their specific hydrologic and ecological dynamics and by the ecosystem matrix for interactions, i.e. the directional dispersal embedded in fluvial and host/pathogen mobility networks, have already produced a remarkably broad range of significant results. Notable scientific and practical perspectives are thus open, in the authors' view, to future developments in ecohydrologic research.

Role of co-occurring competition and facilitation in plant spacing hydrodynamics in water-limited environments.

Plant performance (i.e., fecundity, growth, survival) depends on an individual's access to space and resources. At the community level, plant performance is reflected in observable vegetation patterning (i.e., spacing distance, density) often controlled by limiting resources. Resource availability is, in turn, strongly dependent on plant patterning mediated by competitive and facilitative plant-plant interactions. Co-occurring competition and facilitation has never been specifically investigated from a hydrodynamic perspective. To address this knowledge gap, and to overcome limitations of field studies, three intermediate-scale laboratory experiments were conducted using a climate-controlled wind tunnel-porous media test facility to simulate the soil-plant-atmosphere continuum. The spacing between two synthetic plants, a design consideration introduced by the authors in a recent publication, was varied between experiments; edaphic and mean atmospheric conditions were held constant. The strength of the above- and belowground plant-plant interactions changed with spacing distance, allowing the creation of a hydrodynamic conceptual model based on established ecological theories. Greatest soil water loss was observed for the experiment with the smallest spacing where competition dominated. Facilitation dominated at the intermediate spacing; little to no interactions were observed for the largest plant spacing. Results suggest that there exists an optimal spacing distance range that lowers plant environmental stress, thus improving plant performance through reduced atmospheric demand and conservation of available soil water. These findings may provide a foundation for improving our understanding of many climatological, ecohydrological, and hydrological problems pertaining to the hydrodynamics of water-limited environments where plant-plant interactions and community self-organization are important.

Probabilistic model predicts dynamics of vegetation biomass in a desert ecosystem in NW China.

The temporal dynamics of vegetation biomass are of key importance for evaluating the sustainability of arid and semiarid ecosystems. In these ecosystems, biomass and soil moisture are coupled stochastic variables externally driven, mainly, by the rainfall dynamics. Based on long-term field observations in northwestern (NW) China, we test a recently developed analytical scheme for the description of the leaf biomass dynamics undergoing seasonal cycles with different rainfall characteristics. The probabilistic characterization of such dynamics agrees remarkably well with the field measurements, providing a tool to forecast the changes to be expected in biomass for arid and semiarid ecosystems under climate change conditions. These changes will depend-for each season-on the forecasted rate of rainy days, mean depth of rain in a rainy day, and duration of the season. For the site in NW China, the current scenario of an increase of 10% in rate of rainy days, 10% in mean rain depth in a rainy day, and no change in the season duration leads to forecasted increases in mean leaf biomass near 25% in both seasons.

Geomorphic controls on elevational gradients of species richness.

Elevational gradients of biodiversity have been widely investigated, and yet a clear interpretation of the biotic and abiotic factors that determine how species richness varies with elevation is still elusive. In mountainous landscapes, habitats at different elevations are characterized by different areal extent and connectivity properties, key drivers of biodiversity, as predicted by metacommunity theory. However, most previous studies directly correlated species richness to elevational gradients of potential drivers, thus neglecting the interplay between such gradients and the environmental matrix. Here, we investigate the role of geomorphology in shaping patterns of species richness. We develop a spatially explicit zero-sum metacommunity model where species have an elevation-dependent fitness and otherwise neutral traits. Results show that ecological dynamics over complex terrains lead to the null expectation of a hump-shaped elevational gradient of species richness, a pattern widely observed empirically. Local species richness is found to be related to the landscape elevational connectivity, as quantified by a newly proposed metric that applies tools of complex network theory to measure the closeness of a site to others with similar habitat. Our theoretical results suggest clear geomorphic controls on elevational gradients of species richness and support the use of the landscape elevational connectivity as a null model for the analysis of the distribution of biodiversity.

Relation between rainfall intensity and savanna tree abundance explained by water use strategies.

Tree abundance in tropical savannas exhibits large and unexplained spatial variability. Here, we propose that differentiated tree and grass water use strategies can explain the observed negative relation between maximum tree abundance and rainfall intensity (defined as the characteristic rainfall depth on rainy days), and we present a biophysical tree-grass competition model to test this idea. The model is founded on a premise that has been well established in empirical studies, namely, that the relative growth rate of grasses is much higher compared with trees in wet conditions but that grasses are more susceptible to water stress and lose biomass more quickly in dry conditions. The model is coupled with a stochastic rainfall generator and then calibrated and tested using field observations from several African savanna sites. We show that the observed negative relation between maximum tree abundance and rainfall intensity can be explained only when differentiated water use strategies are accounted for. Numerical experiments reveal that this effect is more significant than the effect of root niche separation. Our results emphasize the importance of vegetation physiology in determining the responses of tree abundance to climate variations in tropical savannas and suggest that projected increases in rainfall intensity may lead to an increase in grass in this biome.

Decreased water limitation under elevated CO2 amplifies potential for forest carbon sinks.

Increasing atmospheric CO2 concentrations and changing rainfall regimes are creating novel environments for plant communities around the world. The resulting changes in plant productivity and allocation among tissues will have significant impacts on forest carbon storage and the global carbon cycle, yet these effects may depend on mechanisms not included in global models. Here we focus on the role of individual-level competition for water and light in forest carbon allocation and storage across rainfall regimes. We find that the complexity of plant responses to rainfall regimes in experiments can be explained by individual-based competition for water and light within a continuously varying soil moisture environment. Further, we find that elevated CO2 leads to large amplifications of carbon storage when it alleviates competition for water by incentivizing competitive plants to divert carbon from short-lived fine roots to long-lived woody biomass. Overall, we find that plant dependence on rainfall regimes and plant responses to added CO2 are complex, but understandable. The insights developed here will serve as an important foundation as we work to predict the responses of plants to the full, multidimensional reality of climate change, which involves not only changes in rainfall and CO2 but also changes in temperature, nutrient availability, and disturbance rates, among others.

Balancing water resource conservation and food security in China.

China's economic growth is expected to continue into the next decades, accompanied by sustained urbanization and industrialization. The associated increase in demand for land, water resources, and rich foods will deepen the challenge of sustainably feeding the population and balancing agricultural and environmental policies. We combine a hydrologic model with an economic model to project China's future food trade patterns and embedded water resources by 2030 and to analyze the effects of targeted irrigation reductions on this system, notably on national agricultural water consumption and food self-sufficiency. We simulate interprovincial and international food trade with a general equilibrium welfare model and a linear programming optimization, and we obtain province-level estimates of commodities' virtual water content with a hydrologic model. We find that reducing irrigated land in regions highly dependent on scarce river flow and nonrenewable groundwater resources, such as Inner Mongolia and the greater Beijing area, can improve the efficiency of agriculture and trade regarding water resources. It can also avoid significant consumption of irrigation water across China (up to 14.8 km(3)/y, reduction by 14%), while incurring relatively small decreases in national food self-sufficiency (e.g., by 3% for wheat). Other researchers found that a national, rather than local, water policy would have similar effects on food production but would only reduce irrigation water consumption by 5%.

Stochastic soil water balance under seasonal climates.

The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude and the phase difference between the climatic forcings. The results provide accurate descriptions of probabilistic soil moisture dynamics under seasonal climates without requiring extensive numerical simulations. We also find that the transfer of soil moisture between the wet to the dry season is responsible for hysteresis in the hydrological response, showing asymmetrical trajectories in the mean soil moisture and in the transient Budyko's curves during the 'dry-down' versus the 'rewetting' phases of the year. Furthermore, in some dry climates where rainfall and potential evapotranspiration are in-phase, annual evapotranspiration can be shown to increase because of inter-seasonal soil moisture transfer, highlighting the importance of soil water storage in the seasonal context.

Water resources transfers through Chinese interprovincial and foreign food trade.

China's water resources are under increasing pressure from socioeconomic development, diet shifts, and climate change. Agriculture still concentrates most of the national water withdrawal. Moreover, a spatial mismatch in water and arable land availability--with abundant agricultural land and little water resources in the north--increases water scarcity and results in virtual water transfers from drier to wetter regions through agricultural trade. We use a general equilibrium welfare model and linear programming optimization to model interprovincial food trade in China. We combine these trade flows with province-level estimates of commodities' virtual water content to build China's domestic and foreign virtual water trade network. We observe large variations in agricultural water-use efficiency among provinces. In addition, some provinces particularly rely on irrigation vs. rainwater. We analyze the virtual water flow patterns and the corresponding water savings. We find that this interprovincial network is highly connected and the flow distribution is relatively homogeneous. A significant share of water flows is from international imports (20%), which are dominated by soy (93%). We find that China's domestic food trade is efficient in terms of rainwater but inefficient regarding irrigation, meaning that dry, irrigation-intensive provinces tend to export to wetter, less irrigation-intensive ones. Importantly, when incorporating foreign imports, China's soy trade switches from an inefficient system to a particularly efficient one for saving water resources (20 km(3)/y irrigation water savings, 41 km(3)/y total). Finally, we identify specific provinces (e.g., Inner Mongolia) and products (e.g., corn) that show high potential for irrigation productivity improvements.

Evolution and selection of river networks: statics, dynamics, and complexity.

Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics--every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept.