A Framework to Assess Biogeochemical Response to Ecosystem Disturbance Using Nutrient Partitioning Ratios

The Ecology of Disturbance Interactions

Global change has been accompanied by recent increases in the frequency and intensity of various ecological disturbances (e.g., fires, floods, cyclones), both natural and anthropogenic in origin. Because these disturbances often interact, their cumulative and synergistic effects can result in unforeseen consequences, such as insect outbreaks, crop failure, and progressive ecosystem degradation. We consider the roles of biological legacies, thresholds, and lag effects responsible for the distinctive impacts of interacting disturbances. We propose a hierarchical classification that distinguishes the patterns and implications associated with random co-occurrences, individual links, and multiple links among disturbances that cascade in chains or networks. Disturbance-promoting interactions apparently prevail over disturbance-inhibiting ones. Complex and exogenous disturbance cascades are less predictable than simple and endogenous links because of their dependency on adjacent or synchronous events. These distinctions help define regional disturbance regimes and can have implications for natural selection, risk assessment, and options for management intervention.

Stochastic disturbance regimes alter patterns of ecosystem variability and recovery

Altered ecosystem variability is an important ecological response to disturbance yet understanding of how various attributes of disturbance regimes affect ecosystem variability is limited. To improve the framework for understanding the disturbance regime attributes that affect ecosystem variability, we examine how the introduction of stochasticity to disturbance parameters (frequency, severity and extent) alters simulated recovery when compared to deterministic outcomes from a spatially explicit simulation model. We also examine the agreement between results from empirical studies and deterministic and stochastic configurations of the model. We find that stochasticity in disturbance frequency and spatial extent leads to the greatest increase in the variance of simulated dynamics, although stochastic severity also contributes to departures from the deterministic case. The incorporation of stochasticity in disturbance attributes improves agreement between empirical and simulated responses, with 71% of empirical responses correctly classified by stochastic configurations of the model as compared to 47% using the purely deterministic model. By comparison, only 2% of empirical responses were correctly classified by the deterministic model and misclassified by stochastic configurations of the model. These results indicate that stochasticity in the attributes of a disturbance regime alters the patterns and classification of ecosystem variability, suggesting altered recovery dynamics. Incorporating stochastic disturbance processes into models may thus be critical for anticipating the ecological resilience of ecosystems.

Long-Term Ecological Research and Evolving Frameworks of Disturbance Ecology

Detecting and understanding disturbance is a challenge in ecology that has grown more critical with global environmental change and the emergence of research on social–ecological systems. We identify three areas of research need: developing a flexible framework that incorporates feedback loops between social and ecological systems, anticipating whether a disturbance will change vulnerability to other environmental drivers, and incorporating changes in system sensitivity to disturbance in the face of global changes in environmental drivers. In the present article, we review how discoveries from the US Long Term Ecological Research (LTER) Network have influenced theoretical paradigms in disturbance ecology, and we refine a framework for describing social–ecological disturbance that addresses these three challenges. By operationalizing this framework for seven LTER sites spanning distinct biomes, we show how disturbance can maintain or alter ecosystem state, drive spatial patterns at landscape scales, influence social–ecological interactions, and cause divergent outcomes depending on other environmental changes.

A theory of pulse dynamics and disturbance in ecology

We propose four postulates as the minimum set of logical propositions necessary for a theory of pulse dynamics and disturbance in ecosystems: (1) resource dynamics characterizes the magnitude, rate, and duration of resource change caused by pulse events, including the continuing changes in resources that are the result of abiotic and biotic processes; (2) energy flux characterizes the energy flow that controls the variation in the rates of resource assimilation across ecosystems; (3) patch dynamics characterizes the distribution of resource patches over space and time, and the resulting patterns of biotic diversity, ecosystem structure, and cross-scale feedbacks of pulses processes; and (4) biotic trait diversity characterizes the evolutionary responses to pulse dynamics and, in turn, the way trait diversity affects ecosystem dynamics during and after pulse events. We apply the four postulates to an important class of pulse events, biomass-altering disturbances, and derive seven generalizations that predict disturbance magnitude, resource trajectory, rate of resource change, disturbance probability, biotic trait diversification at evolutionary scales, biotic diversity at ecological scales, and functional resilience. Ultimately, theory must define the variable combinations that result in dynamic stability, comprising resistance, recovery, and adaptation.

Long-term exposure to more frequent disturbances increases baseline carbon in some ecosystems: Mapping and quantifying the disturbance frequency-ecosystem C relationship

Disturbance regimes have a major influence on the baseline carbon that characterizes any particular ecosystem. Often regimes result in lower average regional baseline C (compared to those same systems if the disturbance processes were lessened/removed). However, in infrequently disturbed systems the role of disturbance as a “background” process that influences broad-scale, baseline C levels is often neglected. Long-term chronosequences suggest disturbances in these systems may serve to increase regional biomass C stocks by maintaining productivity. However, that inference has not been tested spatially. Here, the large forested system of southeast Alaska, USA, is utilized to 1) estimate baseline regional C stocks, 2) test the fundamental disturbance-ecosystem C relationship, 3) estimate the cumulative impact of disturbances on baseline C. Using 1491 ground points with carbon measurements and a novel way of mapping disturbance regimes, the relationship between total biomass C, disturbance exposure, and climate was analyzed statistically. A spatial model was created to determine regional C and compare different disturbance scenarios. In this infrequently disturbed ecosystem, higher disturbance exposure is correlated with higher biomass C, supporting the hypothesis that disturbances maintain productivity at broad scales. The region is estimated to potentially contain a baseline 1.21–1.52 Pg biomass C (when unmanaged). Removal of wind and landslides from the model resulted in lower net C stocks (-2 to -19% reduction), though the effect was heterogeneous on finer scales. There removal of landslides alone had a larger effect then landslide and wind combined removal. The relationship between higher disturbance exposure and higher biomass within the broad ecosystem (which, on average, has a very low disturbance frequency) suggest that disturbances can serve maintain higher levels of productivity in infrequently disturbed but very C dense ecosystems. Carbon research in other systems, especially those where disturbances are infrequent relative to successional processes, should consider the role of disturbances in maintaining baseline ecosystem productivity.

Emerging climate-driven disturbance processes: widespread mortality associated with snow-to-rain transitions across 10° of latitude and half the range of a climate-threatened conifer

Climate change is causing rapid changes to forest disturbance regimes worldwide. While the consequences of climate change for existing disturbance processes, like fires, are relatively well studied, emerging drivers of disturbance such as snow loss and subsequent mortality are much less documented. As the climate warms, a transition from winter snow to rain in high latitudes will cause significant changes in environmental conditions such as soil temperatures, historically buffered by snow cover. The Pacific coast of North America is an excellent test case, as mean winter temperatures are currently at the snow-rain threshold and have been warming for approximately 100 years post-Little Ice Age. Increased mortality in a widespread tree species in the region has been linked to warmer winters and snow loss. Here, we present the first high-resolution range map of this climate-sensitive species, Callitropsis nootkatensis (yellow-cedar), and document the magnitude and location of observed mortality across Canada and the United States. Snow cover loss related mortality spans approximately 10° latitude (half the native range of the species) and 7% of the overall species range and appears linked to this snow-rain transition across its range. Mortality is commonly >70% of basal area in affected areas, and more common where mean winter temperatures is at or above the snow-rain threshold (>0 °C mean winter temperature). Approximately 50% of areas with a currently suitable climate for the species (<-2 °C) are expected to warm beyond that threshold by the late 21st century. Regardless of climate change scenario, little of the range which is expected to remain suitable in the future (e.g., a climatic refugia) is in currently protected landscapes (<1-9%). These results are the first documentation of this type of emerging climate disturbance and highlight the difficulties of anticipating novel disturbance processes when planning for conservation and management.