Some ecological disciplines have made greater use of molecular tools than others, yet common use of molecular approaches is not evident in any ecological field (Fig. 1). Several arguments can be made to explain this pattern. It is possible that some ecological disciplines are slow to make use of molecular tools because important questions in these fields can be answered adequately without molecular approaches. It is also possible that the widespread use of molecular tools as historical tracers – that is, tools to reconstruct historical patterns – gives the impression that they are of limited use for contemporary ecological questions. Alternatively, ecologists may simply be slow or unwilling to adopt new tools that are perceived to be the domain of molecular biologists (what some refer to as a ‘gel jockey’ syndrome). One way to examine these possibilities is to ask how well ecologists are answering their most fundamental questions, with or without molecular approaches. We contend that at least in some ecological fields, traditional approaches are reaching the limits of their explanatory power, and that it explanatory power, and that it would be beneficial to integrate new cross-disciplinary approaches. Molecular tools, coupled with synthetic analytical approaches, should be able to help us make new progress on several key ecological questions, including those at the interface of ecology and other disciplines.
What then are the most pressing problems in ecology, and how can molecular techniques help resolve them? In 1999, Robert May outlined several unanswered questions in ecology, focusing specifically on those that were expected to guide the ecological research agenda of the 21st century (May 1999). Several of these questions remain untapped. Interestingly, many of them could benefit from a molecular perspective. We list a subset of May's questions here and briefly point to ways that molecular methods might be incorporated to help gain additional insights. Our list is by no means exhaustive, but should illustrate how molecular techniques might help address some current questions in ecological research, both from a contemporary and historical perspective.
What determines population density and population persistence?
Ecologists have long focused on variation in organismal life histories and their demographic consequences to explain density and population persistence. The use of molecular methods to reveal the genetic underpinnings of complex life histories offers an important way of identifying the relative contributions of life history adaptations versus environmental factors in driving demographic trends. For example, genetic analyses of aging in Caenorhabditis elegans reveals that although the genotype is largely responsible for the mean life span of a metapopulation, individual longevity is largely influenced by stochastic environmental effects (Chen et al. 2006, Antebi 2007, Caswell-Chen and Caswell 2007). A functional genomic RNAi screen revealed over 80 genes in C. elegans that, when knocked down, result in significant increases in lifespan (Hamilton et al. 2005). It is suspected that many of these genes are pleiotropic (like daf-2 or clk-1, which, by equal factors, simultaneously increase lifespan but decrease fecundity), as revealed by genomic analysis showing genetic correlations between life history traits such as egg size, egg number and body mass (Gutteling et al. 2007). Such studies are honing in on the causal mechanisms responsible for life history tradeoffs that ultimately shape demographic trends (Williams 1957, Caswell 2001, Gutteling et al. 2007). Given that many of the genetic pathways involved in fundamental life history traits (such as lifespan) are highly conserved across all eukaryotes (Curran and Ruvkun 2007), genomic approaches are particularly promising in linking life history evolution to demography. As our ability to economically generate full-genome data sets increases, ecologists should be ready to take advantage of these data. Molecular ecologists must assume the critical role of linking assays of individual genetic variation to demographic trends.
Molecular methods can also be used to approach the question of population density and persistence from a historical perspective. For example, several analytical methods are now available that use gene trees and genetic diversity data to infer historical population sizes through space and time (Kuhner et al. 1998, Hayes et al. 2003, Drummond et al. 2005, Minin et al. 2008, Vasco 2008). Combining these data with historical reconstructions of environmental conditions offers an opportunity to explore population abundance and persistence on a much greater temporal and spatial scale – albeit a courser one – than is typically attempted in contemporary ecological studies. Hence, molecular data can help ecologists gain the benefit of a historical perspective to help shape current hypotheses and experiments.
What role does spatial structure play in regulating population stability?
Since its advent, the evolutionary field of phylogeography has explored spatial relationships among populations. Initial work in this field focused solely on historical patterns of gene flow through space – in ecological terms, this might be viewed simply as the successful movement and reproduction of individuals across a geographic landscape. Hence, phylogeography offers ecologists a way to look back in time and quantify historic patterns of spatial linkages among populations. The issue of population stability can be assessed via historical demography, where researchers are able to infer patterns of population expansion, stability, or bottlenecks through space and time. The current focus in phylogeography is on combining data from several co-distributed species; as multiple data sets become available, molecular ecologists will be able to compare historical demographic trends in highly structured species relative to highly connected ones, and ask if there is any association between spatial structure and population dynamics. Extending this idea, the comparative approach could also be applied to multiple interacting species helping us better understand how communities and ecosystems form and persist over time, an original goal of phylogeography (Avise et al. 1987). Hence, comparative phylogeography could be viewed as one additional tool in community ecology research that seeks to benefit from a historical perspective.
How does biodiversity scale with geographic range and body size?
Most studies of biological diversity are viewed at landscape levels, typically ranging from tens to thousands of kilometers, and most focus on large taxa that are visible to the naked eye. In contrast, we know much less about patterns of diversity for very small organisms, even at very small geographic scales. Do organisms smaller than 1 mm even have community provinces, and if so, are these biogeographies comparable to larger organisms? One difficulty community ecologists have had in working with small organisms is species delimitation and identification at this level. Given that most biological diversity is small (<1 mm), and most small organisms have yet to be described, we currently have a clear understanding of species distributions for only a small fraction of Earth's species. In such cases, molecular methods and sophisticated statistical tools offer our best approach to species identification, an essential prerequisite to describing levels of biodiversity in micro-organisms (Bohannan and Hughes 2003, Cohan and Perry 2007, Green and Plotkin 2007, Lozupone and Knight 2008). The issue of biodiversity and range size is also best approached using DNA sequence data. In some cases where taxa are thought to be geographically widespread, molecular assays have revealed cryptic diversity, in some cases revealing hidden species (Hebert et al. 2004). In other cases, careful examination with molecular methods have revealed methodological problems with DNA barcoding (Song et al. 2008). Still, in most cases molecular techniques currently provide the best, and sometimes only tool whereby ecologists can assay species geographic boundaries and diversity. More importantly, these tools open up studies of micro-organisms that have previously been difficult for community and landscape ecologists to approach.
How do ecological and geophysical factors regulate ecosystem functioning?
Understanding ecosystem functioning remains one of the final frontiers in ecology primarily because of its scope, which includes understanding the ways in which biotic and abiotic components of ecosystems change over time (Noss 1990, Hooper et al. 2000, 2005, Balvanera et al. 2006). Considerable attention has focused on links between ecological factors – such as species diversity, abundance, and distribution – and the flux of energy and nutrients through ecosystems. Still, little is known about the influence of geochemistry and geophysics as drivers of ecosystem functioning. Molecular methods could play an important role in understanding how ecological and geophysical factors govern ecosystem processes.
It is well known that species richness and the abundance of each species can influence ecosystem functioning (Niklaus et al. 2006, Cornwell et al. 2008, Reed et al. 2008). Understanding the former relies on accurate species identification, an enterprise increasingly dependent on molecular approaches, especially for small organisms (as discussed above). Understanding the latter requires knowledge of the functional role that each species plays in ecosystem processes (such as nutrient cycling) and a way to measure the abundance of each species. Here, molecular biogeochemistry is having a major impact in ecosystem research (Zak et al. 2006). A variety of molecular tools can be used to determine patterns of microbe community composition (e.g. T-RFLP, DGGE, LH-PCR, clone library sequences, and next generation sequencing) and molecular approaches like qPCR and microarrays can be used to rapidly recover species abundance (reviewed by Zak et al. 2006). Similarly, by measuring the expression of functional genes involved in biogeochemical pathways (using RT-PCR), we can actually infer the contributions of each species to overall ecosystem functioning (Zak et al. 2006).
Ecosystem functioning is also affected by the geographic distribution of species. Hence, it is important to determine how ecological and geophysical factors influence species ranges. Environmental niche modeling coupled with molecular phylogeography (Lapointe and Rissler 2005, Rissler et al. 2006, Rissler and Apodaca 2007) provides a way to understand how geophysical changes (i.e. climate) might affect the distribution of species, which in turn can be used to predict patterns of nutrient cycling. Such an approach could be further improved if we could determine the adaptive responses of species to both short and long-term environmental changes. For example, research programs such as ecological genomics, focusing on physiological adaptation at molecular genetic and gene expression levels, can identify functional environmental responses of organisms to changes in their immediate and longer-term environment. These responses by individual species could then be used to model predictions of geographic distributions under different climate change scenarios. Elucidating species-level gene expression patterns and linking these to environmental stresses is now possible due to recent advances in transcriptome and DNA sequencing technologies, and genomic resources such as the Gene Ontology Consortium (Harris et al. 2008, Rhee et al. 2008) and Kyoto Encyclopedia of Genes and Genomes (Kanehisa and Goto 2000).
Integrating genomics and ecology can present challenges. Researchers must recognize that gene expression studies require controlling for environmental effects as well as ontogenetic effects. Moreover, genomic resources are still primarily available for model organisms and not the species we typically work with in the field (Travers 2007). However, the potential payoff (in terms of scope and scale of the ecological problems addressed) reinforces the benefits of pursuing collaborative, multidisciplinary approaches to solving ecological questions, especially as genomic data become available for more species.
Quantifying nutrient cycling of specific elements (e.g. carbon or nitrogen) by different species is also important to understanding ecosystem functioning. The discipline of ecological stoichiometry explicitly links food web interactions to the synthesis of bio-molecules within individuals. Interestingly, the components of this research program that are least explored are also those most empowered by molecular techniques. For example, phosphorus is typically a limiting element in the biosynthesis of rRNA molecules, and the production of rRNA is critical to several traits that impact ecological interactions, including growth and reproduction (Sterner and Elser 2002, Jeyasingh and Weider 2007). Hence, understanding how limited elemental resources are allocated within organisms can tell us a great deal about the role of nutrient cycling on individual traits that ultimately govern ecological interactions. Modern molecular approaches like qPCR can be used to measure the number of copies of rDNA genes, and microarrays can be used to measure the abundance and diversity of rRNA molecules produced from these genes – comparisons can then be readily made among different populations and species over varying environmental gradients to understand the role of limiting resources governing key ecological traits.
Finally, ecologists today are clearly interested in knowing if the effect of climate change on ecosystem functioning is predictable. There is good evidence that changes in the geophysical environment (e.g. temperature, precipitation, etc.) shape the distributions of extant biodiversity (Guralnick 2006), and the distribution of biodiversity in turn impacts ecosystem functioning (Barrett et al. 2004, 2006a,b). Hence, given these known links, we are now positioned to use molecular tools to explore how biogeochemical cycles governed by climate can alter community structure. For example, in a low-diversity polar ecosystem it has been shown that climate-induced changes (over decadal timescales) can result in altered hydrology, biological productivity, and ultimately community composition (Doran et al. 2002). Recently, Barrett et al. used stable isotope (13C) probes to explore the implications of climate-induced changes on soil invertebrates and carbon cycling. In this particular case, relatively small changes in temperature over a 14-year period altered the soil invertebrate community structure (as determined by genetic barcodes), leading to an estimated 32% loss of function in carbon cycling (Barrett et al. 2008).