Global Change, Vulnerability and Resilience: Management Options for an Uncertain Future
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 abovementioned 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).
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).
GoalsOur objectives for this new 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 survey 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 currently exploring the usefulness of using Fisher Information in identifying changes in ecosystem order, detecting regime shifts in time, and identifying spatial boundaries of systems. We use observational count data form the North American Breeding Bird Survey (BBS) to achieve these aims. This metric can handle the BBS and similarly large, noisy, and expansive data in a way that transcends the objectives of the original study in such a way that unobservable properties emerge; e.g., ecosystem order, whole-system trajectory, system resilience. Current methods for calculating Fisher Information to detect regime shifts in ecological data are complicated and require multiple, subjective decisions that the user must make that will consequently affect the qualitative results of the analysis. We aim to create a framework that allows the user to use data of varying observational quality, quantity, and of different taxon (or processes) to identify regime shifts. Identifying abrupt changes in the structure and functioning of systems, or system regime shifts, in ecological and social-ecological systems leads to a greater understanding of whole system.
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.