Research

 

As a group, we have diverse interests and we tend to have a fairly eclectic set of projects underway at any given time.  Lab members each have their own research focus within one or more of the following broad themes:

Image credit: Ben Nolting


This surface is a quasi-potential: a graphical representation of a model’s dynamics. The system’s state (e.g. set of current population densities) is given by x-y coordinates. The steepness on the z-axis determines the most likely trajectories, like a ball rolling downhill. Stochasticity jostles the ball as it rolls, preventing it from settling in the troughs.

Image credit: Sam Catella


This is a hypothetical 2D landscape where different shades of gray represent different abiotic conditions. Sam created it by independently specifying its fractal dimension (pattern of spatial autocorrelation) and degree of variability.

Image credit: Chris Moore


The benefit of engaging in a mutualism (z-axis) can depend in varied and complex ways on the population densities of both mutualistic partners (x- and y-axes). These surfaces show contrasting linear and nonlinear dependence of mutualistic benefit on self and partner density.

Photo credit: Karen Abbott


The goldenrod beetle, Trirhabda spp., is an outbreaking herbivore that inspired some of our early work on insect outbreak dynamics.

Spatial ecology


Space matters in ecology. This profound fact has been studied intensely for decades yet continues to toss us fascinating puzzles. We use spatial models to understand both causes and consequences of spatial patterns, and to understand the role of dispersal in ecological dynamics.  Some topics we investigate in our recent and ongoing work are:


  1. Dispersal is known to be both synchronizing and stabilizing, but its stabilizing effect relies on some degree of asynchrony. We have found that environmental stochasticity (even when it’s spatially correlated and can enhance synchrony itself!) is sufficient to limit dispersal-induced synchrony, thus allowing dispersal-induced stability.

  2. Spatial patterns in plant communities are driven in part by spatial patterns in abiotic conditions, but different abiotic drivers vary at different scales with different characteristics. We are developing new computational approaches to understand how these different abiotic scales and patterns intersect to jointly shape plant spatial structure.

  3. Multi-host disease dynamics on islands are influenced by the fact that terrestrial and aquatic hosts only interact at shorelines. This may limit the effectiveness of interventions that target only one host species.

Environmental stochasticity and global change


We study how changes in the environment – due either to random (stochastic) variation or directional global change – affect ecological populations.  We begin with baseline, deterministic models for our study systems, then assess the consequences of either adding stochasticity to the models, or of making structural or parameter changes that reflect changing environmental conditions.  We are also working more broadly to develop new tools and approaches for studying and conceptualizing stochastic ecological models. Click here for some ramblings about how we think about stochasticity. Some key ideas from our research on this topic are:


  1. Alternative stable states may be extremely difficult to identify in stochastic systems, since sudden state shifts can occur even when only a single state is stable

  2. “Stability” is, indeed, a tricky concept in stochastic systems, and tools like the quasi-potential may help us clarify and synthesize it

  3. Climate-driven phenological shifts may: interact with range shifts for unexpected effects on population size; disrupt plant-pollinator mutualisms, with eco-evolutionary consequences; and be insufficient to buffer populations with temperature-dependent sex determination

  4. Elevated temperatures have counter-intuitive effects on insect dynamics, due to temperature effects on predators and constraints of photoperiod.

Positive feedbacks and population dynamics


Positive feedbacks occur when ecological interactions cause small populations to get smaller or large populations to get larger.  Since most healthy populations don’t dwindle to extinction or explode to infinite densities, ecological theory has generally highlighted the role of negative feedbacks that cause perturbations above or below an intermediate population size to decay.  Thus, although positive feedbacks are well-known to exist, their role in governing population dynamics is still an active area of research.  We are exploring positive feedbacks in the following contexts:


  1. It has long been thought that benefits among mutualistic partners must taper off to avoid runaway positive feedbacks wherein each species increases ad infinitum in response to the other’s increase. We are studying how the form of intraspecific density dependence that species experience can also play an important role in halting runaway benefits.

  2. A network of positive and negative feedbacks exist among plants and soil microbes, and these likely contribute to plant community patterns. In collaboration with Jim Bever and James Umbanhowar, we are working to characterize these feedbacks during plant succession.

  3. Group structure in social animals may prevent Allee effects (positive feedbacks at low density) from transferring up to the population level.

Insect outbreaks


When herbivores feed, they reduce both the quantity of plant matter available for future herbivores and also, often, its quality.  Plants have a variety of induced responses to herbivory, including chemical defenses and changes in growth patterns, and each should have a different impact on herbivore population dynamics.  We are interested in how plant responses to herbivory promote or prevent insect outbreaks.


  1. Outbreaks in herbivorous insect populations may occur in response to either food limitation (reductions in the quantity of plant matter available) or in response to induced plant defense (reductions in plant quality), but only under some circumstances.  When both food limitation and induced defense act simultaneously, outbreaks become possible even under conditions where neither factor alone would drive them.

  2. Some plants respond to herbivory with compensatory regrowth, which can either prevent outbreaks, or can drive them but under fundamentally different conditions than they would occur without compensation.

  3. Compensatory regrowth typically requires the mobilization of stored energy reserves from inedible structures such as roots. Characteristics of this energy exchange between edible and inedible biomass are important for plant persistence and co-existence under herbivory.