As the effects of anthropogenic stressors (fragmentation, habitat degradation, climate change, etc.) on natural populations increase, it is essential that we understand the factors closely related to population persistence and resilience. The overarching research goal of my lab group is to link genetic factors with other aspects of an organism’s biology, life history, and demography to help predict population persistence. More specifically, we conduct research that aims to understand: 1) spatial patterns of an organism’s genetic diversity, 2) effective population size as a predictor of persistence probability, 3) whether translocation is an effective practice to enhance persistence probabilities (‘genetic rescue’), and 4) adaptive dynamics and mechanisms. We also develop and test general tools that will help advance the field and be used to help conserve a wide variety of taxa.

 Spatial patterns of genetic diversity

Describing an organism’s genetic population structure is often a first critical step for conservation. This type of analysis reveals how environmental and anthropogenic factors have influenced amounts of genetic variation within, and genetic divergence among, natural populations. Isolated populations that may have reduced probabilities of persistence can be detected. Hybridization, defined as the mixing of genetically divergent genomes, can also be diagnosed (Kelly et al. 2010). Analyses of genetic structure might be the most prevalent type of research in my field for good reason – this research provides a starting point for data-driven conservation and management.

My collaborators and I have published ten papers relating environmental heterogeneity to spatial patterns of genetic variation of six different fish species using either population genetic or genomic techniques. My lab group has also begun to explore the relationship between environmental factors and spatial patterns of genetic variation beyond fishes, including vernal pool salamanders (Ambystoma spp.) in Massachusetts (Whiteley et al. 2014a), a Rocky Mountain plant (Ipomopsis aggregata), and bumble bees (Bombus impatiens).

Effective population size

One way to link environmental and anthropogenic stressors to population persistence is through a population’s effective size. Effective population size (N_e) and the effective number of breeders (N_b)can be used to predict population persistence—which makes them central to conservation genetics—but these parameters are difficult to estimate. Ongoing work in my lab is devoted to understanding N_e and N_b and the relationship between these two parameters in trout populations. In two papers in Conservation Genetics, we have examined how N_e is influenced by long-term isolation (Whiteley et al. 2010) and we have determined the most appropriate sampling strategy to obtain precise and unbiased estimates of N_b in headwater trout populations (Whiteley et al. 2012). An additional paper examines the effect of habitat patch size on N_b in Appalachian brook trout populations following relatively recent isolation by dams (Whiteley et al. 2013). Finally, we are currently conducting a US Forest Service-funded pilot study examining N_b and habitat patch size from approximately 30 patches in Virginia (Whiteley et al. 2014c). My goal is to build this work into a genetic monitoring program, based on N_b, for the brook trout across its native eastern range. This program will allow us to precisely estimate N_b repeatedly over time for many sites and compare trends in N_b to trends in population abundance. This program will be critical for the conservation of eastern brook trout and the headwater habitat for which they serve as a sentinel species.

Genetic rescue

One possible solution to alleviate small population “extinction vortex” dynamics is to introduce a small number of individuals into an isolated population (so-called “genetic rescue”). Successful reproduction by these translocated individuals can restore genetic diversity and mask the genes responsible for inbreeding depression. Genetic rescue is becoming an important conservation approach that has successfully been used for single populations of Florida panthers, prairie chickens, and Swedish adders, among other species. However, empirical examples have not been replicated. Extensive fragmentation in stream networks makes genetic rescue an appealing conservation effort that would be feasible for situations where barrier removal is not possible. I co-authored a a recent review on genetic rescue (Whiteley et al. in press). We have also established a US Forest Service-funded replicated genetic rescue experiment with brook trout in Appalachian streams in Virginia. We started the experiment in Fall 2011 and already have extremely promising initial results. This work will be a groundbreaking replicated test of genetic rescue, an approach that we may come to rely on as an increasing number of populations become isolated and small due to anthropogenic factors. If I were to move my research program to UM, I would seek to continue this work in Virginia and look to set up or collaborate on additional experimental tests of genetic rescue in western fishes.

Adaptive dynamics and mechanisms

The ability for individuals to adapt to local environmental conditions plays an important role in population persistence. In the face of environmental and anthropogenic stressors, we must understand if local adaptation can keep pace to allow populations to persist. Collaborators and I have published papers in Evolution, Ecology of Freshwater Fish, and the Journal of Evolutionary Biology that explore the role of adaptation to rapid deglaciation in a freshwater sculpin (Whiteley et al. 2009; Whiteley et al. 2011a; Bergstrom et al. 2012; photos show fish from an older stream, left, and much more recently deglaciated stream, right). I have also published two papers in Genetics that explore the mechanistic genomic association between adaptive divergence and gene expression (Whiteley et al. 2008; Derome et al. 2008). I am currently collaborating with researchers in Europe to examine adaptive genomic change that occurs due to experimental size-selective harvest in wild-derived zebrafish (Danio rerio)(Uusi-Heikkilä in review).

I am a principal collaborator on a research project at UMass that will allow us to understand the link between adaptive dynamics and population persistence in greater depth. We are continuing work on an individual-based study of brook trout in a natural headwater stream population near UMass, initiated by Ben Letcher (US Geological Survey) and Keith Nislow (US Forest Service) in 2000. We have developed models to understand the influence of environmental factors (stream flow and temperature) on demographic vital rates (Letcher et al. in press, Bassar et al. in review). We have reconstructed pedigrees to examine movement and dispersal (Kanno et al. 2014) and are now working to examine fitness consequences in this natural population. We are currently applying modeling approaches that relate demography, evolution, and environmental variation in innovative ways.

Developing tools for improved conservation genetic monitoring

My research group is working to develop and apply genetic and genomic tools to important management issues. For example, collaborators and I have developed a method to genetically test for movement on an ecological time scale through road-stream crossings based on sibling relationships. Full-siblings sampled on either side of a culvert indicate that movement occurred some time between hatching and the time of sample. This method works very well based on simulations and with empirical test cases (Whiteley et al. 2014b). Another recent advance in the field is the ability to obtain DNA from aquatic organisms from sloughed off tissues freely available in the water. This new approach, termed “eDNA” (environmental DNA), will greatly improve our ability to detect rare aquatic organisms, or organisms as they initially invade a new habitat. A MS student and I collaborated with researchers the University of Montana and USFS Rocky Mountain Research Station to develop eDNA approaches for stream fishes (Wilcox et al. 2013; Jane et al. 2014). Finally, A PhD student whom I co-advise, is developing packages in R that will automate current techniques to quantify landscape resistance to animal movement and gene flow. This is a follow up to this student’s initial review on the topic (Zeller et al. 2012) and will be highly useful to managers and academics interested in landscape genetics and applied questions such as corridor development.