Genetic data are often used to assess 'population connectivity' because it is difficult to measure dispersal directly at large spatial scales. Genetic connectivity, however, depends primarily on the ...absolute number of dispersers among populations, whereas demographic connectivity depends on the relative contributions to population growth rates of dispersal vs. local recruitment (i.e. survival and reproduction of residents). Although many questions are best answered with data on genetic connectivity, genetic data alone provide little information on demographic connectivity. The importance of demographic connectivity is clear when the elimination of immigration results in a shift from stable or positive population growth to negative population growth. Otherwise, the amount of dispersal required for demographic connectivity depends on the context (e.g. conservation or harvest management), and even high dispersal rates may not indicate demographic interdependence. Therefore, it is risky to infer the importance of demographic connectivity without information on local demographic rates and how those rates vary over time. Genetic methods can provide insight on demographic connectivity when combined with these local demographic rates, data on movement behaviour, or estimates of reproductive success of immigrants and residents. We also consider the strengths and limitations of genetic measures of connectivity and discuss three concepts of genetic connectivity that depend upon the evolutionary criteria of interest: inbreeding connectivity, drift connectivity, and adaptive connectivity. To conclude, we describe alternative approaches for assessing population connectivity, highlighting the value of combining genetic data with capture-mark-recapture methods or other direct measures of movement to elucidate the complex role of dispersal in natural populations.
Environmental DNA (eDNA) is being rapidly adopted as a tool to detect rare animals. Quantitative PCR (qPCR) using probe-based chemistries may represent a particularly powerful tool because of the ...method’s sensitivity, specificity, and potential to quantify target DNA. However, there has been little work understanding the performance of these assays in the presence of closely related, sympatric taxa. If related species cause any cross-amplification or interference, false positives and negatives may be generated. These errors can be disastrous if false positives lead to overestimate the abundance of an endangered species or if false negatives prevent detection of an invasive species. In this study we test factors that influence the specificity and sensitivity of TaqMan MGB assays using co-occurring, closely related brook trout (Salvelinus fontinalis) and bull trout (S. confluentus) as a case study. We found qPCR to be substantially more sensitive than traditional PCR, with a high probability of detection at concentrations as low as 0.5 target copies/µl. We also found that number and placement of base pair mismatches between the Taqman MGB assay and non-target templates was important to target specificity, and that specificity was most influenced by base pair mismatches in the primers, rather than in the probe. We found that insufficient specificity can result in both false positive and false negative results, particularly in the presence of abundant related species. Our results highlight the utility of qPCR as a highly sensitive eDNA tool, and underscore the importance of careful assay design.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Is dispersal neutral? Lowe, Winsor H.; McPeek, Mark A.
Trends in ecology & evolution (Amsterdam),
08/2014, Letnik:
29, Številka:
8
Journal Article
Recenzirano
•Dispersal is a fundamental biological process, but difficult to observe directly.•We know little about how natural selection shapes individual dispersal traits.•This information is crucial to ...understanding how dispersal influences biodiversity.•There are conceptual obstacles and exciting opportunities in this area of research.•Advances require a bottom-up approach built on data on individual dispersal traits.
Dispersal is difficult to quantify and often treated as purely stochastic and extrinsically controlled. Consequently, there remains uncertainty about how individual traits mediate dispersal and its ecological effects. Addressing this uncertainty is crucial for distinguishing neutral versus non-neutral drivers of community assembly. Neutral theory assumes that dispersal is stochastic and equivalent among species. This assumption can be rejected on principle, but common research approaches tacitly support the ‘neutral dispersal’ assumption. Theory and empirical evidence that dispersal traits are under selection should be broadly integrated in community-level research, stimulating greater scrutiny of this assumption. A tighter empirical connection between the ecological and evolutionary forces that shape dispersal will enable richer understanding of this fundamental process and its role in community assembly.
Environmental DNA (eDNA) detection has emerged as a powerful tool for monitoring aquatic organisms, but much remains unknown about the dynamics of aquatic eDNA over a range of environmental ...conditions. DNA concentrations in streams and rivers will depend not only on the equilibrium between DNA entering the water and DNA leaving the system through degradation, but also on downstream transport. To improve understanding of the dynamics of eDNA concentration in lotic systems, we introduced caged trout into two fishless headwater streams and took eDNA samples at evenly spaced downstream intervals. This was repeated 18 times from mid‐summer through autumn, over flows ranging from approximately 1–96 L/s. We used quantitative PCR to relate DNA copy number to distance from source. We found that regardless of flow, there were detectable levels of DNA at 239.5 m. The main effect of flow on eDNA counts was in opposite directions in the two streams. At the lowest flows, eDNA counts were highest close to the source and quickly trailed off over distance. At the highest flows, DNA counts were relatively low both near and far from the source. Biomass was positively related to eDNA copy number in both streams. A combination of cell settling, turbulence and dilution effects is probably responsible for our observations. Additionally, during high leaf deposition periods, the presence of inhibitors resulted in no amplification for high copy number samples in the absence of an inhibition‐releasing strategy, demonstrating the necessity to carefully consider inhibition in eDNA analysis.
Populations optimize the match of phenotype to environment by localized natural selection, adaptive phenotypic plasticity, and habitat choice. Habitat choice may also be achieved by several ...mechanisms, including matching habitat choice, where individuals distribute themselves based on self-assessment of the phenotype–environment match. Matching habitat choice is a relatively untested concept, but one that could advance our understanding of the interplay of movement ecology and intraspecific phenotypic variation. Morphology of the salamander Gyrinophilus porphyriticus differs in riffles and pools, the dominant habitats in headwater streams where this species occurs. Specifically, individuals found in riffles have shorter limbs than those found in pools. Here, we used 4 yr of spatially explicit capture–mark–recapture data from three streams to test the contributions of phenotypic plasticity and matching habitat choice to this phenotype–environment covariation. We quantified morphological variation in G. porphyriticus with size-corrected principal component (PC) scores and assessed phenotype–environment match based on the difference between habitats in these PC scores. We found that both phenotypic plasticity and matching habitat choice contribute to phenotype–environment covariation in G. porphyriticus. The phenotypes of individuals that switched habitats (i.e., riffle→pool, pool→riffle) changed to become better matched to the recipient habitat, indicating a plastic response to local habitat conditions. Consistent with matching habitat choice, individuals were also more likely to switch habitats if their initial phenotype was a better match to the alternative habitat, independent of subsequent changes in morphology due to plasticity. Realized performance, survival adjusted for the likelihood of remaining in each habitat, was higher in individuals with phenotypes matched to each habitat than in those with mismatched phenotypes, but performance was generally lower in riffles than pools, suggesting that other factors influence the use of riffles. Our results underscore the value of considering how matching habitat choice interacts with other mechanisms that allow organisms to maximize performance when faced with environmental heterogeneity. More broadly, our study shows that it is important to account for movement in any study of the causes or consequences of intraspecific trait variation, a challenge that may require novel research approaches and experimental designs.
Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, ...where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.
The interplay of ecology and evolution has been a rich area of research for decades. A surge of interest in this area was catalyzed by the observation that evolution by natural selection can operate ...at the same contemporary timescales as ecological dynamics. Specifically, recent eco-evolutionary research focuses on how rapid adaptation influences ecology, and vice versa. Evolution by non-adaptive forces also occurs quickly, with ecological consequences, but understanding the full scope of ecology–evolution (eco–evo) interactions requires explicitly addressing population-level processes – genetic and demographic. We show the strong ecological effects of non-adaptive evolutionary forces and, more broadly, the value of population-level research for gaining a mechanistic understanding of eco–evo interactions. The breadth of eco-evolutionary research should expand to incorporate the breadth of evolution itself.
Eco–evo interactions are mediated by population genetics and demography, but current research often fails to consider this population context.
Population genetics theory provides a framework for understanding the full scope of eco–evo interactions, including the effects of adaptive and non-adaptive forces.
Our review shows the ecological effects of non-adaptive evolution and the mechanistic insight gained in population-level research on eco–evo interactions.
Population-based approaches integrating genetic and demographic information will advance general understanding of the scope, strength, and scale of eco–evo interactions.
Spatial sorting of dispersal-enhancing traits has been implicated in substantial directional changes in the phenotypic and genotypic makeup of populations undergoing range expansion. We explore here ...the evolutionary consequences of such changes when two divergent lineages come into secondary contact. We combine instances from the study of contemporary range expansions and historical hybridizations, and highlight links between dispersal, sexual, and physiological traits during the non-equilibrium conditions imposed by range expansions. We argue that a stronger research focus on processes of spatial sorting of multiple traits will improve our understanding of subsequent hybridization dynamics and their evolutionary outcomes, including genomic introgression and speciation.
Mounting data show that substantial, rapid, and deterministic changes in the phenotypic and genotypic makeup of populations can occur during range expansions by spatial sorting of dispersal-related traits.
Traits associated with dispersal also influence other fundamental biological processes, such as reproduction, physiology, and behavior.
Dispersal, sexual, physiological, and behavioral traits are of crucial importance for hybridization dynamics between divergent lineages upon secondary contact.
A stronger focus on multiple trait associations and spatial sorting during range expansion could improve our understanding of subsequent hybridization events and their evolutionary outcomes.
Most animals have complex life cycles including metamorphosis or other discrete life stage transitions, during which individuals may be particularly vulnerable to environmental stressors. With ...climate change, individuals will be exposed to increasing thermal and hydrologic variability during metamorphosis, which may affect survival and performance through physiological, behavioral, and ecological mechanisms. Furthermore, because metamorphosis entails changes in traits and vital rates, it is likely to play an important role in how populations respond to increasing climate variability. To identify mechanisms underlying population responses and associated trait and life history evolution, we need new approaches to estimating changes in individual traits and performance throughout metamorphosis, and we need to integrate metamorphosis as an explicit life stage in analytical models.
During metamorphosis and other discrete transitions between life stages, many animals are vulnerable and depend on environmental stability.As climates continue to change, increasing thermal and hydrologic variability may pose particular risks to metamorphic species, but we lack empirical and analytical resources for assessing these risks.Many aspects of metamorphosis are sensitive to environmental conditions, including timing and duration, extent of developmental change, and energy costs. Consequently, relative to effects on pre- and postmetamorphic stages, climate variability may have disproportionately strong effects on the traits, fitness, and survival of metamorphosing individuals.In turn, proximate effects of climate variability during metamorphosis may influence population dynamics and life history evolution by imposing trait and vital rate trade-offs with pre- and postmetamorphic life stages.
Avoiding inbreeding is considered a key driver of dispersal evolution, and dispersal distances should be especially important in mediating inbreeding risk because the likelihood of mating with ...relatives decreases with dispersal distance. However, a lack of direct data on dispersal distances has limited empirical tests of this prediction, particularly in the context of the multiple selective forces that can influence dispersal. Using the headwater stream salamander Gyrinophilus porphyriticus, we tested whether spatial variation in environmental conditions leads to differences in dispersal distances, resulting in spatial variation in the effect of dispersal on inbreeding risk. Using capture-recapture and population genomic data from five streams, we found that dispersal distances were greater in downstream reaches than upstream reaches. Inbreeding risk trended lower for dispersers than nondispersers in downstream reaches but not in upstream reaches. Furthermore, stream reaches did not differ in spatial patterns of individual relatedness, indicating that variation in inbreeding risk was in fact due to differences in dispersal distances. These results demonstrate that environmentally associated variation in dispersal distances can cause the inbreeding consequences of dispersal to vary at fine spatial scales. They also show that selective pressures other than inbreeding avoidance maintain phenotypic variation in dispersal, underscoring the importance of addressing alternative hypotheses in dispersal research.
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