My talk, sitting in the last slot of today's session, draws on several presentations we have heard today. This final talk will put eco-evolutionary research and knowledge in the context of conservation and climate change.
Le me first remind you that climate change is a big deal with a large influence on biological systems. Under a business as usual emission scenario, temperatures on land are predicted to increase 5-6 deg C this century. The last time the world was this much cooler, Death Valley was covered with mesic forest, a habitat that has since been replaced with drought and temperature tolerant plants and animals. The last time the climate was this warm, there was a relative of the alligator living at the pole.
With this backdrop of large potential change, I'm arguing today four four points that form the basis of a commentary that my colleague Mike Pfrender and I wrote for the 25th anniversary issue of Conservation Biology (Hellmann and Pfrender 2011). I will illustrate these points with empirical data, from my lab or my close collaborators. Research that considers evolutionary processes in climate change biology is still rare but increasing everyday. We need to pick up this pace to inform good management and preserve a sizable portion of life as we know it.
In the language of evolutionary biology, climate change--in simplified form--looks something like this: A species "B" is composed of individuals with a particular distribution of phenotypes or traits. "A" depicts a simple fitness landscape and the mean of "B" sits at the optimum of that landscape. Climate change shifts the landscape to, say, "C." Most ecologists' attempts to predict B's response to change considers the distance between the current trait distribution and the new optimum. They also assume that "B" is fixed or that it is composed of a single fitness peak that matches a single fitness landscape per species. As a result, these predictions lack key eco-evolutionary features.
The first claim I will make is that we must consider variation within species in the reaction to climate change, variation due to processes such as drift and local adaptation. Two quick examples:
1. In common garden (translocation) experiments with a butterfly, we showed that populations at the northern edge of a species range react differently to temperature than central populations. When the RNA of experimental animals was hybridized to a microarray, we identified ~300 genes with localized expression in this butterfly species (O'Neil et al. 2014). 55 of those we can guess at their function thanks to annotation in related species. Many of them are oxidative and metabolic genes. Each line in this graph shows the expression level of a gene under central and peripheral temperature conditions; purple are individuals from peripheral populations and yellow are individuals from central populations. Nearly all of the 300 genes show an unbalanced response to temperature in this species: the two source regions/populations respond differently to peripheral, cooler conditions, but they respond similarly to central, warmer conditions. In this case, warming could be homogenizing force; still, localization is a strong signal in these data.
2. In another species of butterfly, we tested if modeling populations separately--as functionally distinct entities--versus together--as one uniform species--in in statistical niche modeling has an effect on predicted occupancy under climate change (Hallfors et al. in revision). In this species, populations in the eastern portion of the range occupy a distinct climate niche relative to western populations, as shown in this PCA of occupancy as a function of 2 principal components involving 19 different climate variables. This next slide shows where MaxEnt, a common statistical niche model, predicts Karner would live 15, 35, and 65 years from now. On the left, I show predictions based on the entire species as a single niche. On the right, I show predictions if we model the two ecotypes separately (black are current points; colors are predicted, future areas). Both the particular predicted occupied area and the total area occupied are different between the left and right panels. Whether we consider climatic differences between populations matters in generating predictions about where they might go in the future, or where we might put them.
My second claim is that we must consideration adaptive capacity when evaluating the effects of climate change. My previous slide involving the Karner blue butterfly assumes that species--or the two forms within the species--is static. The model assesses vulnerability in terms of the amount of change, called exposure, and how much it perturbs the insect, its sensitivity. But a third component of vulnerability, adaptive capacity, is not considered by most ecological assessments, including niche models. Adaptive capacity involves the ability of a species to adjust, physiologically, through dispersal, or through evolutionary change.
In a forthcoming paper, colleagues and I argue that we can think of adaptive capacity like we think of niche theory, that realized adaptive capacity is a constrained subset of fundamental adaptive capacity (Beever et al. in press). In this abstract graph, for example, consider two hypothetical dimensions of adaptive capacity: evolution and dispersal. The fundamental adaptive capacity is in purple, and the realized adaptive capacity is in green. Smart management can reduce constraints on realized adaptive capacity to increase the ability of species to cope with climate change. Here, for example, through habitat connectivity to release dispersal constraints or genetic mixing to release constraints on adaptive evolution.
My third and fourth points consider evolutionary aspects of management itself. If we aspire to create new management techniques or apply them in new ways because of climate change, we will need to consider eco-evolutionary dynamics in crafting these plans. Further, as all interventions have side effects, we must consider not only the ecological consequences of our actions--on population size, abating extinction, etc.--but also non-target *evolutionary* effects.
I'll tackle both of these points with the example of managed relocation. Managed relocation is an intervention technique aimed at moving species from area of historic occupancy to areas of future occupancy (Richardson et al. 2009). You might pursue managed relocation because it could prevent species or population losses, but it could likely also create new pests, put already-endangered populations at greater risk, and/or incur considerable costs.
Some key, unanswered questions for managed relocation include:
i) should introduced populations be sourced from multiple locales?
ii) how well matched is the source material to the current and future environment?
iii) as the environment changes further, how much genetic variation is desirable?
Each of these are eco-evolutionary questions.
Further, we recently asked published scientists their opinions on managed relocation and found considerable context-dependence (Javeline et al. 2015). For example, we asked about three hypothetical cases of managed relocation: one for an endangered butterfly to prevent species extinction, one for forest trees to enable timber production, and one for a symbiont of corals to prevent coral degradation and loss. We found variation among these cases in how necessary scientists felt managed relocation might be and how effective they thought it could be to address the stated goal. Eco-evolutionary dynamics would add another layer of complexity and uncertainty to an issue that experts already tell us will be different in different instances.
I've offered four essential areas where eco-evolutionary dynamics is critical to managing our conservation future under climate change. Fortunately, these issues are also incredibly interesting biologically. For both the future of biodiversity and humanity, and for the opportunity to study the inner-workings of nature, these four topics are worthy of your research attention as evolutionary biologists. I hope that the entirety of today's session inspires new, creative eco-evolutionary work.
Beever et al. In press. Improving conservation outcomes with a new paradigm for understanding species’ fundamental and realized adaptive capacity. Conservation Letters.
Hällfors et al. In revision. Addressing potential local adaptation in species distribution models: implications for conservation under climate change. Ecological Applications.
Hellmann and Pfrender. 2011. Future human intervention in ecosystems and the critical role for evolutionary biology. Conservation Biology 25: 1143.
Javeline et al. 2015. Expert opinion on extinction risk and climate change adaptation for biodiversity. Elementa. DOI 10.12952.
O’Neil et al. 2014. Gene expression in closely-related species mirrors local adaptation: consequences for responses to a warmer world. Molecular Ecology 23: 2686.
Richardson et al. 2009. Multidimensional evaluation of managed relocation. Proceedings of the National Academy of Sciences 106: 9721.