We are employing various analytical and statistical techniques to quantify how core attributes of resilience (within-scale and cross-scale distributions of species and their functional traits) change over time in ecosystems and landscapes. Techniques used include, but are not limited to, stochastic modelling, information theory, and discontinuity analysis. Additionally, we will evaluate the significance of individual species to adaptive capacity, and thus the resilience of ecosystems and landscapes. We are conducting these analyses with data from the central United States with focal areas on Department of Defense managed properties, in particular Eglin Air Force Base, Florida, and Fort Riley, Kansas.
In addition to the goals, which are aimed specifically at informing the Department of Defense of potential threat to military readiness, two dissertations will be produced under this grant.
As the Anthropocene progresses, examples of global ecological uncertainty are on the rise: many systems are undergoing ecological regime shifts into novel, often undesirable, states. Estimating systems’ vulnerability to ecological change and regime shifts can provide policy makers, land managers, and researchers the ability to prioritize land management to possibly avoid regime shifts or at least mitigate negative impacts. Using discontinuity analysis approaches to long-term continental-scale North American Breeding Bird Survey data, northward shifts have been detected in spatial ecological regime boundaries in central North America from 1970 to 2014. The results suggest that the methods used can detect direction and magnitude of ecological regime shifts in space that also implies a potential method for estimating a given ecosystem’s ecological vulnerability to change: proximity to an approaching change in spatial regimes may indicate greater ecological vulnerability for ecosystems in the path of the change.
As a part of additional projects, first-authored manuscripts have been submitted to peer-reviewed journals in which undocumented ecological legacies from a 27-year-old wildfire in an eastern ponderosa pine system are identified along with identified policy and ecology mismatches in the management of a native invader (eastern redcedar).
GoalsOur objectives for this project are to develop models to detect and assess ecological regime shifts in space and time, to identify components of adaptive capacity, and to identify species and techniques that may serve as leading indicators of thresholds of changing ecological regimes. We are utilizing monitoring and surveying data that is currently available in North America (e.g., Breeding Bird Surveys) with novel statistical tools and theory to assess long-term trends in the resilience of landscapes, changes in ecological regimes in both space and time, and species vulnerable to decline and extinction.
We are also exploring the use and sensitivity of multivariate metrics in identifying, and potentially predicting, regime shifts and boundaries in space and time. Specifically, we are testing the use of the Fisher Information metric, a sound, statistical estimation of the amount of information available in observations. Fisher Information metric has been used to estimate the orderliness, or information available, within a complex system. The Fisher Information metric is well-grounded in mathematics and statistics but the sensitivities of using Fisher Information on noisy and non-Gaussian ecological data is not well-understood (non-experimental, observational data gathered about ecological systems are often noisy).
Rapid environmental change may alter the ability of the Department of Defense to maintain readiness, and require costly remediation and mitigation when formerly abundant species become rare. The uncertainties associated with global change support the need for a framework that allows the explicit incorporation of non-linear responses of complex systems. Our project addresses this uncertainty by identifying ecosystems with potential current high vulnerability to global change (risk of an impending regime shift). Here, we identified spatial regimes in avian community data and track their movements over 46 years (1970 – 2015) in the North American Great Plains biome. In 46 years, we found the northernmost spatial regime boundaries moved >590 km northward, the southernmost boundary moved >260 km northward. We demonstrate an eminent biome-level regime shift in the Great Plains and how tracking spatial regimes provides spatially and temporally explicit estimates of vulnerability to ecological change. Spatial regimes provided early warnings of regime shifts >10 years prior to the regime shift, suggesting that spatial regimes can provide decades worth of ecological planning horizons.
Principal Investigator(s)-Craig R. Allen, NE CFWRU
-Dirac Twidwell, University of Nebraska-Lincoln
-David G. Angeler, Swedish University of Agricultural Sciences
Graduate Student(s)-Jessica Burnett, Ph.D.
-Caleb Roberts, Ph.D.