The Kitzes Lab studies biodiversity loss and extinction in human-altered landscapes. We take a somewhat unusual approach to this topic, in that we do not study any particular threatened species, or any specific ecosystem. Rather, we work to develop and apply theory, models, and measurement techniques that are useful across many taxonomic groups and habitats.
Broadly speaking, our work on biodiversity loss and extinction divides into four distinct but related goals:
- Measure – Where is extinction, or population decline, occurring? For what species? How fast? We answer these questions by developing and deploying autonomous sensor networks, which are combined with machine learning classification models to gather biodiversity data at very large spatiotemporal scales, beyond what can be collected by human observers.
- Understand – What are the specific drivers or causes of extinction, and how do they interact? We answer these questions by combining large data sets, including our own and those collected by others, with statistical analyses designed to identify commonalities across locations where species populations are low or declining.
- Predict – How much extinction is likely to occur in the future, where, for what species? We answer these questions largely with pattern-based theory and models, largely based in spatial macroecology, that relate species diversity to habitat area and range sizes.
- Prevent – What actions can we take to prevent, or mitigate, biodiversity loss? We answer these questions by developing analyses and decision tools that highlight specific management actions that are likely to lead to, or prevent, future extinctions.
Nested within and crossing these questions, the major ongoing projects in our lab at the moment include:
Theoretical research on spatial scaling and turnover
Our major ongoing theory-based project focuses on the relationship between measures of spatial scaling and spatial turnover. If we know, for example, how species richness increases as the size of a plot increases, how can we use this information to predict how two different communities, separated by some distance, might be similar or different? Our major line of work involves using point pattern analysis, coupled with traditional methods from spatial macroecology, to relate these measures of spatial scaling to spatial turnover. This research will ultimately lead to the derivation of multivariate species-area relationships, which can predict steady state species richness in networks of habitat patches with different sizes and shapes.
Large scale field surveys of bird and bat diversity
Our current field research involves surveying birds and bats using autonomous acoustic recorders, which are able to efficiently and rapidly gather diversity and activity data at large spatial and temporal scales. We are currently establishing field sites near western Pennsylvania that use these recorders to study the spatial ecology of bird and bat populations. These take the form of long, linear transects, and smaller grid survey designs. Ultimately we hope to gather long-term data sets on population change across years, within years, and in response to changes in human disturbance pressures.
Methods for large scale acoustic biodiversity surveys
In concert with our own field research, we are also heavily involved in developing new methods and technology to improve the efficiency and applicability of acoustic biodiversity surveys. We are developing a new, scalable, open source audio analysis platform, OpenSoundscape, to support ecologists and conservation biologists in classifying animal vocalizations in audio recordings. We are also investigating hardware and software designs that can be used to identify the location of sounds on a several hectare plot to within a few meters.
In addition to our main interests described above, our lab is active in open science and reproducible research communities. We have developed several open source software packages, and Dr. Kitzes recently co-edited a book titled The Practice of Reproducible Research. Dr. Kitzes has also conducted extensive research on global models of sustainable resource consumption (“footprint” modeling).