|
My overarching research interests are broad, drawing from an eclectic educational background and an overarching interest in exploring new things. I've tried to summarize some themes below. Probably the tl;dr version of this is that I view myself as part quantitative/statistical ecologist interested in developing tools and products to support management or conservation applications, and part behavioral/community ecologist interested in more fundamental questions. I am open to using many datastreams to tackle these objectives: the standard toolkit includes in-situ observations derived from camera traps, tagged animals, non-invasive genetic sampling devices, or from professional or participatory scientists, along with data or products derived from airborne or satellite remote sensing. (This may not be a strong selling point, but what this implies is that, by virtue or necessity, jack of many/master of few).
|
Sampling And Observational Processes
Essentially every observational ecological study must contend with sampling and observation error. Ecological studies are increasingly characterized by large datasets collected without a structured design and where observations or measurements are both known to exhibit errors but impossible to completely vouch (e.g., citizen science, varied forms of remote sensing). Sampling bias and observation errors also pervade smaller studies motivated by specific questions. I am interested in exploring sensitivity to data quirks like species misclassification or preferential sampling, both to better understand which types of insights these quirks hinder (and which are relatively insensitive) and to better develop and implement effective and pragmatic solutions rooted in models or other means.
Regardless of the solution employed, I believe thinking about *how* field or remote methods sample or observe/measure ecological phenomena is probably the strongest way to approach these issues. As such, this broad interest subsumes many more targeted interests related to how humans and instruments obtain samples of the world, and the degree to which covarying patterns in the state of the world and where it is sampled or what is observed create epistemological challenges for conservation and management action. It also includes wonkier interests in statistical epistemology related to trade-offs between inference and prediction and the practice of specifying and selecting models.
Regardless of the solution employed, I believe thinking about *how* field or remote methods sample or observe/measure ecological phenomena is probably the strongest way to approach these issues. As such, this broad interest subsumes many more targeted interests related to how humans and instruments obtain samples of the world, and the degree to which covarying patterns in the state of the world and where it is sampled or what is observed create epistemological challenges for conservation and management action. It also includes wonkier interests in statistical epistemology related to trade-offs between inference and prediction and the practice of specifying and selecting models.
Inferring, Predicting, and Forecasting Species Distributions
Like many other ecologists, I spend a lot of time working on trying to figure out where organisms are located at or across specific times and why. I use and advance a variety of different data streams and models (occupancy, N-mixture, RSF, SCR, etc.) to predict, monitor, or forecast distributions and infer key drivers of their patterns or dynamics. This work encompasses a range of different spatiotemporal extents/grains with different environmental foci ranging from longer-term climate or land use/land cover change to short-term variation associated with seasonality or other ephemeral impacts.
Much of this work is motivated by questions germane to management or conservation decision-making. As I've worked more with practitioners and decision-makers, I've become more interested in the science of how to get better at making decisions and undertaking actions, including eliciting goals and objectives, optimizing decisions to meet objectives, and implementing monitoring that improves the decision-making process.
Much of this work is motivated by questions germane to management or conservation decision-making. As I've worked more with practitioners and decision-makers, I've become more interested in the science of how to get better at making decisions and undertaking actions, including eliciting goals and objectives, optimizing decisions to meet objectives, and implementing monitoring that improves the decision-making process.
Behavioral And Community Ecology
How communities vary and how they form, maintain, or dissolve remain fundamental ecological questions. I am interested in exploring key drivers of species richness, nestedness, and turnover across space and time, and characterizing how different mechanisms of community assembly contribute to variation in species assemblages. I have a particular interest in understanding whether certain patterns exhibit temporal scaling (i.e., do the effects of seasonal environmental variation provide insights into how longer-term global change might impact communities?).
I am also interested in exploring species interactions within a community. Species interactions often exhibit complex mixtures of cost and benefit to different players in different contexts, particularly when the interacting species occupy different trophic levels. I commonly explore these interactions using tools and concepts rooted in behavioral ecology (foraging games, behavioral response races, and so forth).
I am also interested in exploring species interactions within a community. Species interactions often exhibit complex mixtures of cost and benefit to different players in different contexts, particularly when the interacting species occupy different trophic levels. I commonly explore these interactions using tools and concepts rooted in behavioral ecology (foraging games, behavioral response races, and so forth).
