Debra P. C. Peters

Legacies of precipitation fluctuations on primary production: theory and data synthesis

Variability of above-ground net primary production (ANPP) of arid to sub-humid ecosystems displays a closer association with precipitation when considered across space (based on multiyear averages for different locations) than through time (based on year-to-year change at single locations). Here, we propose a theory of controls of ANPP based on four hypotheses about legacies of wet and dry years that explains space versus time differences in ANPP–precipitation relationships. We tested the hypotheses using 16 long-term series of ANPP. We found that legacies revealed by the association of current- versus previous-year conditions through the temporal series occur across all ecosystem types from deserts to mesic grasslands. Therefore, previous-year precipitation and ANPP control a significant fraction of current-year production. We developed unified models for the controls of ANPP through space and time. The relative importance of current-versus previous-year precipitation changes along a gradient of mean annual precipitation with the importance of current-year PPT decreasing, whereas the importance of previous-year PPT remains constant as mean annual precipitation increases. Finally, our results suggest that ANPP will respond to climate-change-driven alterations in water availability and, more importantly, that the magnitude of the response will increase with time.

Ecosystem resilience despite large-scale altered hydroclimatic conditions

Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975–1998), and drier, warmer conditions in the early twenty-first century (2000–2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUEe: above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUEe in drier years that increased significantly with drought to a maximum WUEe across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought—that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUEe may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.

Disentangling Complex Landscapes: New Insights into Arid and Semiarid System Dynamics

Abstract Although desertification is a global phenomenon and numerous studies have provided information on dynamics at specific sites, spatial and temporal variations in response to desertification have led to alternative, and often controversial, hypotheses about the key factors that determine these dynamics. We present a new research framework that includes five interacting elements to explain these variable dynamics: (1) historical legacies, (2) environmental driving variables, (3) a soil-geomorphic template of patterns in local properties and their spatial context, (4) multiple horizontal and vertical transport vectors (water, wind, animals), and (5) redistribution of resources within and among spatial units by the transport vectors, in interaction with other drivers. Interactions and feedbacks among these elements within and across spatial scales generate threshold changes in pattern and dynamics that can result in alternative future states, from grasslands to shrublands, and a reorganization of the landscape. We offer a six-step operational approach that is applicable to many complex landscapes, and illustrate its utility for understanding present-day landscape organization, forecasting future dynamics, and making more effective management decisions.

Cross–Scale Interactions and Changing Pattern–Process Relationships: Consequences for System Dynamics

Cross–scale interactions refer to processes at one spatial or temporal scale interacting with processes at another scale to result in nonlinear dynamics with thresholds. These interactions change the pattern–process relationships across scales such that fine-scale processes can influence a broad spatial extent or a long time period, or broad-scale drivers can interact with fine-scale processes to determine system dynamics. Cross–scale interactions are increasing recognized as having important influences on ecosystem processes, yet they pose formidable challenges for understanding and forecasting ecosystem dynamics. In this introduction to the special feature, “Cross–scale interactions and pattern–process relationships”, we provide a synthetic framework for understanding the causes and consequences of cross–scale interactions. Our framework focuses on the importance of transfer processes and spatial heterogeneity at intermediate scales in linking fine- and broad-scale patterns and processes. Transfer processes and spatial heterogeneity can either amplify or attenuate system response to broad-scale drivers. Providing a framework to explain cross–scale interactions is an important step in improving our understanding and ability to predict the impacts of propagating events and to ameliorate these impacts through proactive measures.

Long-term and large-scale perspectives on the relationship between biodiversity and ecosystem functioning

Abstract In a growing body of literature from a variety of ecosystems is strong evidence that various components of biodiversity have significant impacts on ecosystem functioning. However, much of this evidence comes from short-term, small-scale experiments in which communities are synthesized from relatively small species pools and conditions are highly controlled. Extrapolation of the results of such experiments to longer time scales and larger spatial scales—those of whole ecosystems—is difficult because the experiments do not incorporate natural processes such as recruitment limitation and colonization of new species. We show how long-term study of planned and accidental changes in species richness and composition suggests that the effects of biodiversity on ecosystem functioning will vary over time and space. More important, we also highlight areas of uncertainty that need to be addressed through coordinated cross-scale and cross-site research.

Tree Mortality in Gap Models: Application to Climate Change

Gap models are perhaps the most widely used class of individual-based tree models used in ecology and climate change research. However, most gap model emphasize, in terms of process detail, computer code, and validation effort, tree growth with little attention to the simulation of plant death or mortality. Mortality algorithms have been mostly limited to general relationships because of sparse data on the causal mechanisms of mortality. If gap models are to be used to explore community dynamics under changing climates, the limitations and shortcomings of these mortality algorithms must be identified and the simulation of mortality must be improved. In this paper, we review the treatment of mortality in gap models, evaluate the relationships used to represent mortality in the current generation of gap models, and then assess the prospects for making improvements, especially for applications involving global climate change. Three needs are identified to improve mortality simulations in gap models: (1) process-based empirical analyses are needed to create more climate-sensitive stochastic mortality functions, (2) fundamental research is required to quantify the biophysical relationships between mortality and plant dynamics, and (3) extensive field data are needed to quantify, parameterize, and validate existing and future gap model mortality functions.

Analysis of abrupt transitions in ecological systems

The occurrence and causes of abrupt transitions, thresholds, or regime shifts between ecosystem states are of great concern and the likelihood of such transitions is increasing for many ecological systems. General understanding of abrupt transitions has been advanced by theory, but hindered by the lack of a common, accessible, and data-driven approach to characterizing them. We apply such an approach to 30–60 years of data on environmental drivers, biological responses, and associated evidence from pelagic ocean, coastal benthic, polar marine, and semi-arid grassland ecosystems. Our analyses revealed one case in which the response (krill abundance) linearly tracked abrupt changes in the driver (Pacific Decadal Oscillation), but abrupt transitions detected in the three other cases (sea cucumber abundance, penguin abundance, and black grama grass production) exhibited hysteretic relationships with drivers (wave intensity, sea-ice duration, and amounts of monsoonal rainfall, respectively) through a variety of response mechanisms. The use of a common approach across these case studies illustrates that: the utility of leading indicators is often limited and can depend on the abruptness of a transition relative to the lifespan of responsive organisms and observation intervals; information on spatiotemporal context is useful for comparing transitions; and ancillary information from associated experiments and observations aids interpretation of response-driver relationships. The understanding of abrupt transitions offered by this approach provides information that can be used to manage state changes and underscores the utility of long-term observations in multiple sentinel sites across a variety of ecosystems.

Plant species dominance at a grassland–shrubland ecotone: an individual-based gap dynamics model of herbaceous and woody species

Abstract Transition zones or ecotones between biomes are predicted to be particularly sensitive areas to directional changes in climate. However, for many ecotones, there is little understanding of the key processes that allow dominant species from adjacent biomes to coexist at transition zones and how differences in these processes affect species responses to changes in environmental conditions. The objective of this study was to examine the relationship between plant life history traits and patterns in dominance and composition at a grassland–shrubland transition zone in order to predict shifts in dominance with directional changes in climate. It was hypothesized that differences in life history traits allow species from adjacent biomes to coexist at this transition zone, and that these dominance patterns are dynamic through time as a result of species-specific responses to changes in climate. A mixed lifeform individual plant-based gap dynamics model (ECOTONE) was developed to examine consequences of differences in recruitment, resource acquisition, and mortality to patterns in species dominance and composition under a variety of soils and climatic conditions. This model is unique because it represents interactions among multiple potential dominant species that include congeneric species of one lifeform as well as herbaceous and woody lifeforms across multiple spatial scales. Similar to other gap models, ECOTONE simulates the recruitment, growth, and mortality of individual plants on a small plot through time at an annual timestep. ECOTONE differs from other gap models in the degree of detail involved in determining successful recruitment by each species and in the simulation of belowground resources. Individual plant root distributions and resource availability by depth are dynamic. Soil water content is simulated on a daily timestep and nitrogen is simulated monthly. Multiple spatial scales can be simulated using a grid of plots connected by seed dispersal. ECOTONE was parameterized for two soil types at the Sevilleta National Wildlife Refuge (SEV), a site located within the transition zone between two major biomes in North America. Shortgrass steppe communities are dominated by the perennial grass Bouteloua gracilis (blue grama) and Chihuahuan desert communities are dominated by the perennial grass Bouteloua eriopoda (black grama) or the shrub Larrea tridentata (creosotebush). Experiments were conducted to provide key parameters related to recruitment and growth that were supplemented with information from the literature for remaining parameters. Model output was verified using field estimates of cover and biomass for the three dominant species as well as other groups of species. Simulation analyses were conducted under current climate and for a directional change in climate. Nitrogen was assumed constant for all runs to allow a focus on water availability constraints as affected by climate. Under current climatic conditions, simulated biomass on sandy loam soils was dominated by B. eriopoda with smaller biomass of B. gracilis and other species groups. By contrast, simulated biomass on a loamy sand soil was codominated by B. eriopoda and L. tridentata with very small biomass attributed to other species groups. Under a GFDL climate change scenario of increased year-round temperatures and increased summer precipitation, vegetation patterns shifted to a clear dominance of biomass by B. eriopoda on both soil types. These results show that temporal partitioning of soil water is important to codominance by the two Bouteloua species, and that spatial and temporal partitioning of soil water is important for grass–shrub interactions. The results also suggest that global climate change may provide a mechanism for the recovery of B. eriopoda following shrub invasion in the Southwestern U.S. Thus, an individual-based modeling approach is capable of representing complex interactions among herbaceous and woody species as well as between congeneric species with different life history traits at a biome transition zone. This modeling approach is useful in improving our understanding of key processes driving these vegetation dynamics as well in predicting shifts in dominance as environmental conditions change in the future.

Using Mechanistic Models to Scale Ecological Processes across Space and Time

Abstract Human activities affect the natural environment at local to global scales. To understand these effects, knowledge derived from short-term studies on small plots needs to be projected to much broader spatial and temporal scales. One way to project short-term, plot-scale knowledge to broader scales is to embed that knowledge in a mechanistic model of the ecosystem. The National Science Foundations Long Term Ecological Research (LTER) Network makes two vital contributions to this type of modeling effort: (1) a commitment to multidisciplinary research at individual sites, which results in a broad range of mutually consistent data, and (2) long-term data sets essential for estimating rate constants for slow ecosystem processes that dominate long-term ecosystem dynamics. In this article, we present four examples of how a mechanistic approach to modeling ecological processes can be used to make projections to broader scales. The models are all applied to sites in the LTER Network.

Taking the pulse of a continent: expanding site‐based research infrastructure for regional‐ to continental‐scale ecology

Many of the most dramatic and surprising effects of global change on ecological systems will occur across large spatial extents, from regions to continents. Multiple ecosystem types will be impacted across a range of interacting spatial and temporal scales. The ability of ecologists to understand and predict these dynamics depends, in large part, on existing site-based research infrastructures developed in response to historic events. Here we review how unevenly prepared ecologists are, and more generally, ecology is as a discipline, to address regional- to continental-scale questions given these pre-existing site-based capacities, and we describe the changes that will be needed to pursue these broad-scale questions in the future. We first review the types of approaches commonly used to address questions at broad scales, and identify the research, cyber-infrastructure, and cultural challenges associated with these approaches. These challenges include developing a mechanistic understanding of the drivers and responses of ecosystem dynamics across a large, diverse geographic extent where measurements of fluxes or flows of materials, energy or information across levels of biological organization or spatial units are needed. The diversity of methods, sampling protocols, and data acquisition technologies make post-hoc comparisons of ecosystems challenging, and data collected using standardized methods across sites require coordination and teamwork. Sharing of data and analytics to create derived data products are needed for multi-site studies, but this level of collaboration is not part of the current ecological culture. We then discuss the strengths and limitations of current site-based research infrastructures in meeting these challenges, and describe a path forward for regional- to continental-scale ecological research that integrates existing infrastructures with emerging and potentially new technologies to more effectively address broad-scale questions. This new research infrastructure will be instrumental in developing an “uber network” to allow users to seamlessly identify and select, analyze, and interpret data from sites regardless of network affiliation, funding agency, or political affinity, to cover the spatial variability and extent of regional-to continental-scale questions. Ultimately, scientists must network across institutional boundaries in order to tap and expand these existing network infrastructures before these investments can address critical broad-scale research questions and needs.