Research
In general, we are interested in plant community and restoration ecology. We have experience working in desert plant communities in southern Arizona, semi-arid woodlands in Western Australia, semi-arid shortgrass steppe in Colorado, and sagebrush steppe plant communities in the western United States.
Collecting spatial data using a pantograph in annual plan communties in Western Australia
Spatial and environmental effects on plant interaction outcomes
Strong evidence of non-random spatial arrangements are often interpreted as evidence of the importance of local interactions on plant survival and population growth. The spatial arrangement of individuals within plant communities have also been shown to affect the outcome of interactions between species (particularly in tree plant communities). In addition, environmental conditions vary heterogeneously across a landscape changing the context of these interactions. If spatial patterns within plant communities are non-random, then exploring the potential environmental drivers of those patterns gives us understanding about plant community structure and function.
Understanding the drivers and effects of spatial arrangement of individuals and species can also help inform restoration practices. Currently, we are in working group (including researchers at the University of Arizona and USDA, ARS) to explore how spatial arrangement in restoration seeding may impact germination, survival and fitness. In a greenhouse study, we designed a project to explore the effect of neighbor density (high or low), neighbor diversity (1 to 3 species), and distance (near or far) on the fitness of a focal individual planted in the middle of the pot. Overall we collected trait data and leaves for 1326 individual plants and total biomass per species from 233 pots.
Using functional traits to understand environmental change impacts and improve restoration practices
Functional traits are known to affect how species interact , how plants respond to the environment , and how plants can impact the ecosystems services of the community. Thus, we can understand plant community dynamics using functional traits that are linked to performance, demographic rates, and ecosystem services to improve understanding of ecosystem responses to environmental change across time and space. I am currently working on a large, collaborative project with Dr. Leslie Roche from UC Davis, Dr. Elise Gornish from The University of Arizona, and rancher and community groups from AZ and CA. The project looks at functional traits, population dynamics, and ecosystems in the context of restoration on California and Arizona rangelands.
Currently I am also collaborating with researchers at the University of Arizona to use individual-based models (IBM) to explore understand plant community resilience to disturbance. A plant communities' resilience to disturbance can be influenced by its functional diversity. To explore this resilience, I will use an IBM (STEPWAT2) to build plant communities of different functional trait diversities and simulate disturbances of various intensities and frequencies under current and future climates. A plant community that is currently resilient to disturbance may not be so in the future.
Check out more research from the Gornish Lab at The University of Arizona.
Community DYNAMICS Over Time and Space
Figure 1. Modified from Schlaepfer et al. (2015) Ecosphere.
To explore community dynamics over time, we like to look both behind and forward.
We are currently working on a project to explore the impact of climate on sagebrush growth. This work includes correlating climate data with annual sagebrush ring widths. This is a way to determine impacts of climate on past growth of plants.
To look ahead we often have to rely on models. Individual-based models (IBMs) are an ideal tool for exploring how best to develop from predicting fitness of an individual to predicting vegetation dynamics at a community level. Current collaborations with Drs. William Lauenroth (Yale), John Bradford (USGS), Daniel Schlaepfer (USGS), and Kyle Palmquist (Mashall Uni), work on using an IBM (STEPWAT2) to understand plant community composition and biomass responses under predicted climate change.