Molecular genetics to inform spatial management in benthic invertebrate fisheries: a case study using the Australian Greenlip Abalone

Hierarchical sampling and subsequent microsatellite genotyping of >2300 Haliotis laevigata (greenlip abalone) from 19 locations distributed across five biogeographic regions have substantially advanced our knowledge of population structure and connectivity in this commercially important species. The study has found key differences in stock structure of H. laevigata compared with the sympatric and congeneric Haliotis rubra (blacklip abalone) and yielded valuable insights into the management of fisheries targeting species characterized by spatial structure at small scales (i.e. S‐fisheries). As with H. rubra, H. laevigata comprise a series of metapopulations with strong self‐recruitment. However, the spatial extent of H. laevigata metapopulations (reefal areas around 30 km²; distances of up to 135 km are effective barriers to larval dispersal) was substantially greater than that identified for H. rubra (Miller et al. 2009). Differences in the dynamics and scale of population processes, even between congeneric haliotids as made evident in this study, imply that for S‐fisheries, it is difficult to generalize about the potential consequences of life history commonalities. Consequently, species‐specific management reflective of the population structure of the target species remains particularly important. This will likely require integration of information about stock structure and connectivity with data on life history and population dynamics to determine the necessary input (e.g. number of fishers, fishing effort) and output (e.g. minimum legal size, total allowable catch) controls to underpin their sustainable management.     

Range expansion through fragmented landscapes under a variable climate

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high‐resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine‐resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine‐scale, short‐term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions.     

Isolation and characterization of 125 microsatellite DNA markers in the blacklip abalone,Haliotis rubra

Australian abalone species are subject to wild harvest and aquaculture production. This study characterized 125 polymorphic microsatellite markers in the blacklip abalone, Haliotis rubra, and evaluated cross‐species amplification in Haliotis laevigata and Haliotis coccoradiata. Segregation analysis of a mapping family revealed non‐amplifying polymerase chain reaction null alleles at 34 loci. Cross‐species amplification was achieved for 89 loci.     

Geographic range determinants of two commercially important marine molluscs

Aim We modelled the spatial abundance patterns of two abalone species (Haliotis rubra Donovan 1808 and H. laevigata Leach 1814) inhabiting inshore rocky reefs to better understand the importance of current sea surface temperature (SST) (among other predictors) and, ultimately, the effect of future climate change, on marine molluscs. Location Southern Australia. Methods We used an ensemble species distribution modelling approach that combined likelihood‐based generalized linear models and boosted regression trees. For each modelling technique, a two‐step procedure was used to predict: (1) the current probability of presence, followed by (2) current abundance conditional on presence. The resulting models were validated using an independent, spatially explicit dataset of abalone abundance patterns in Victoria. Results For both species, the presence of reef was the main driver of abalone occurrence, while SST was the main driver of spatial abundance patterns. Predictive maps at c. 1‐km resolution showed maximal abundance on shallow coastal reefs characterized by mild winter SSTs for both species. Main conclusions Sea surface temperature was a major driver of abundance patterns for both abalone species, and the resulting ensemble models were used to build fine‐resolution predictive range maps (c. 1 km) that incorporate measures of habitat suitability and quality in support of resource management. By integrating this output with structured spatial population models, a more robust understanding of the potential impacts of threatening human processes such as climate change can be established.     

How complex should models be? Comparing correlative and mechanistic range dynamics models

Criticism has been levelled at climate‐change‐induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real‐world data. We provide the first comparison of the skill of coupled ecological‐niche‐population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40‐year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological‐niche‐population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid‐cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.     

Dynamics of range margins for metapopulations under climate change

We link spatially explicit climate change predictions to a dynamic metapopulation model. Predictions of species'' responses to climate change, incorporating metapopulation dynamics and elements of dispersal, allow us to explore the range margin dynamics for two lagomorphs of conservation concern. Although the lagomorphs have very different distribution patterns, shifts at the edge of the range were more pronounced than shifts in the overall metapopulation. For Romerolagus diazi (volcano rabbit), the lower elevation range limit shifted upslope by approximately 700 m. This reduced the area occupied by the metapopulation, as the mountain peak currently lacks suitable vegetation. For Lepus timidus (European mountain hare), we modelled the British metapopulation. Increasing the dispersive estimate caused the metapopulation to shift faster on the northern range margin (leading edge). By contrast, it caused the metapopulation to respond to climate change slower, rather than faster, on the southern range margin (trailing edge). The differential responses of the leading and trailing range margins and the relative sensitivity of range limits to climate change compared with that of the metapopulation centroid have important implications for where conservation monitoring should be targeted. Our study demonstrates the importance and possibility of moving from simple bioclimatic envelope models to second-generation models that incorporate both dynamic climate change and metapopulation dynamics.     

Seascape genomics reveals adaptive divergence in a connected and commercially important mollusc,the greenlip abalone (Haliotis laevigata), along a longitudinal environmental gradient

Populations of broadcast spawning marine organisms often have large sizes and are exposed to reduced genetic drift. Under such scenarios, strong selection associated with spatial environmental heterogeneity is expected to drive localized adaptive divergence, even in the face of connectivity. We tested this hypothesis using a seascape genomics approach in the commercially important greenlip abalone (Haliotis laevigata). We assessed how its population structure has been influenced by environmental heterogeneity along a zonal coastal boundary in southern Australia linked by strong oceanographic connectivity. Our data sets include 9,109 filtered SNPs for 371 abalones from 13 localities and environmental mapping across ~800 km. Genotype–environment association analyses and outlier tests defined 8,786 putatively neutral and 323 candidate adaptive loci. From a neutral perspective, the species is better represented by a metapopulation with very low differentiation (global F_ST = 0.0081) and weak isolation by distance following a stepping‐stone model. For the candidate adaptive loci, however, model‐based and model‐free approaches indicated five divergent population clusters. After controlling for spatial distance, the distribution of putatively adaptive variation was strongly correlated to selection linked to minimum sea surface temperature and oxygen concentration. Around 80 candidates were annotated to genes with functions related to high temperature and/or low oxygen tolerance, including genes that influence the resilience of abalone species found in other biogeographic regions. Our study includes a documented example about the uptake of genomic information in fisheries management and supports the hypothesis of adaptive divergence due to coastal environmental heterogeneity in a connected metapopulation of a broadcast spawner.     

Observational evidence that maladaptive gene flow reduces patch occupancy in a wild insect metapopulation

Theory predicts that dispersal throughout metapopulations has a variety of consequences for the abundance and distribution of species. Immigration is predicted to increase abundance and habitat patch occupancy, but gene flow can have both positive and negative demographic consequences. Here, we address the eco‐evolutionary effects of dispersal in a wild metapopulation of the stick insect Timema cristinae, which exhibits variable degrees of local adaptation throughout a heterogeneous habitat patch network of two host‐plant species. To disentangle the ecological and evolutionary contributions of dispersal to habitat patch occupancy and abundance, we contrasted the effects of connectivity to populations inhabiting conspecific host plants and those inhabiting the alternate host plant. Both types of connectivity should increase patch occupancy and abundance through increased immigration and sharing of beneficial alleles through gene flow. However, connectivity to populations inhabiting the alternate host‐plant species may uniquely cause maladaptive gene flow that counters the positive demographic effects of immigration. Supporting these predictions, we find the relationship between patch occupancy and alternate‐host connectivity to be significantly smaller in slope than the relationship between patch occupancy and conspecific‐host connectivity. Our findings illustrate the ecological and evolutionary roles of dispersal in driving the distribution and abundance of species.     

Twenty‐five years of change in southern African passerine diversity: nonclimatic factors of change

We analysed more than 25 years of change in passerine bird distribution in South Africa, Swaziland and Lesotho, to show that species distributions can be influenced by processes that are at least in part independent of the local strength and direction of climate change: land use and ecological succession. We used occupancy models that separate species' detection from species' occupancy probability, fitted to citizen science data from both phases of the Southern African Bird Atlas Project (1987–1996 and 2007–2013). Temporal trends in species' occupancy probability were interpreted in terms of local extinction/colonization, and temporal trends in detection probability were interpreted in terms of change in abundance. We found for the first time at this scale that, as predicted in the context of bush encroachment, closed‐savannah specialists increased where open‐savannah specialists decreased. In addition, the trend in the abundance of species a priori thought to be favoured by agricultural conversion was negatively correlated with human population density, which is in line with hypotheses explaining the decline in farmland birds in the Northern Hemisphere. In addition to climate, vegetation cover and the intensity and time since agricultural conversion constitute important predictors of biodiversity changes in the region. Their inclusion will improve the reliability of predictive models of species distribution.     

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field‐based measures of abundance, demographic performance, and forecasted stochastic population growth (λ_s). Predicted climatic suitability showed a J‐shaped relationship with A. utahensis abundance, where low‐abundance populations were associated with low‐to‐intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λ_s from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM‐predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.     

Conservation management and sustainable harvest quotas are sensitive to choice of climate modelling approach for two marine gastropods

Aim

To establish the robustness of two alternative methods for predicting the future ranges and abundances for two wild‐harvested abalone species (Haliotis rubra Donovan 1808 and H. laevigata Leach 1814): single atmosphere–ocean general circulation model (GCM) or ensemble‐averaged GCM forecasts.

Location

South Australia.

Methods

We assessed the ability of 20 GCMs to simulate observed seasonal sea surface temperature (SST) between 1980–1999, globally, and regionally for the Indian and Pacific Oceans south of the Equator. We used model rankings to characterize a set of representative climate futures, using three different‐sized GCM ensembles and two individual GCMs (the Parallel Climate Model and the Community Climate System Model, version 3.0). Ecological niche models were then coupled to physiological information to compare forecast changes in area of occupancy, population size and harvest area based on forecasts using the various GCM selection methods, as well as different greenhouse gas emission scenarios and climate sensitivities.

Results

We show that: (1) the skill with which climate models reproduce recent SST records varies considerably amongst GCMs, with multimodel ensemble averages showing closer agreement to observations than single models; (2) choice of GCM, and the decision on whether or not to use ensemble‐averaged climate forecasts, can strongly influence spatiotemporal predictions of range, abundance and fishing potential; and (3) comparable hindcasting skill does not necessarily guarantee that GCM forecasts and ecological and evolutionary responses to these forecast changes, will be similar amongst closely ranked models.

Conclusion

By averaging across an ensemble of seven highly ranked skilful GCMs, inherent uncertainties stemming from GCM differences are incorporated into forecasts of change in species range, abundance and sustainable fishing area. Our results highlight the need to make informed and explicit decisions on GCM choice, model sensitivity and emission scenarios when exploring conservation options for marine species and the sustainability of future harvests using ecological niche models.

     

Dispersal and species’ responses to climate change

Dispersal is fundamental in determining biodiversity responses to rapid climate change, but recently acquired ecological and evolutionary knowledge is seldom accounted for in either predictive methods or conservation planning. We emphasise the accumulating evidence for direct and indirect impacts of climate change on dispersal. Additionally, evolutionary theory predicts increases in dispersal at expanding range margins, and this has been observed in a number of species. This multitude of ecological and evolutionary processes is likely to lead to complex responses of dispersal to climate change. As a result, improvement of models of species’ range changes will require greater realism in the representation of dispersal. Placing dispersal at the heart of our thinking will facilitate development of conservation strategies that are resilient to climate change, including landscape management and assisted colonisation. Synthesis This article seeks synthesis across the fields of dispersal ecology and evolution, species distribution modelling and conservation biology. Increasing effort focuses on understanding how dispersal influences species' responses to climate change. Importantly, though perhaps not broadly widely‐recognised, species' dispersal characteristics are themselves likely to alter during rapid climate change. We compile evidence for direct and indirect influences that climate change may have on dispersal, some ecological and others evolutionary. We emphasise the need for predictive modelling to account for this dispersal realism and highlight the need for conservation to make better use of our existing knowledge related to dispersal.     

Host plant density and patch isolation drive occupancy and abundance at a butterfly's northern range margin

Marginal populations are usually small, fragmented, and vulnerable to extinction, which makes them particularly interesting from a conservation point of view. They are also the starting point of range shifts that result from climate change, through a process involving colonization of newly suitable sites at the cool margin of species distributions. Hence, understanding the processes that drive demography and distribution at high‐latitude populations is essential to forecast the response of species to global changes. We investigated the relative importance of solar irradiance (as a proxy for microclimate), habitat quality, and connectivity on occupancy, abundance, and population stability at the northern range margin of the Oberthür's grizzled skipper butterfly Pyrgus armoricanus. For this purpose, butterfly abundance was surveyed in a habitat network consisting of 50 habitat patches over 12 years. We found that occupancy and abundance (average and variability) were mostly influenced by the density of host plants and the spatial isolation of patches, while solar irradiance and grazing frequency had only an effect on patch occupancy. Knowing that the distribution of host plants extends further north, we hypothesize that the actual variable limiting the northern distribution of P. armoricanus might be its dispersal capacity that prevents it from reaching more northern habitat patches. The persistence of this metapopulation in the face of global changes will thus be fundamentally linked to the maintenance of an efficient network of habitats.     

Managed relocation as an adaptation strategy for mitigating climate change threats to the persistence of an endangered lizard

The distributional ranges of many species are contracting with habitat conversion and climate change. For vertebrates, informed strategies for translocations are an essential option for decisions about their conservation management. The pygmy bluetongue lizard, Tiliqua adelaidensis, is an endangered reptile with a highly restricted distribution, known from only a small number of natural grassland fragments in South Australia. Land‐use changes over the last century have converted perennial native grasslands into croplands, pastures and urban areas, causing substantial contraction of the species' range due to loss of essential habitat. Indeed, the species was thought to be extinct until its rediscovery in 1992. We develop coupled‐models that link habitat suitability with stochastic demographic processes to estimate extinction risk and to explore the efficacy of potential climate adaptation options. These coupled‐models offer improvements over simple bioclimatic envelope models for estimating the impacts of climate change on persistence probability. Applying this coupled‐model approach to T. adelaidensis, we show that: (i) climate‐driven changes will adversely impact the expected minimum abundance of populations and could cause extinction without management intervention, (ii) adding artificial burrows might enhance local population density, however, without targeted translocations this measure has a limited effect on extinction risk, (iii) managed relocations are critical for safeguarding lizard population persistence, as a sole or joint action and (iv) where to source and where to relocate animals in a program of translocations depends on the velocity, extent and nonlinearities in rates of climate‐induced habitat change. These results underscore the need to consider managed relocations as part of any multifaceted plan to compensate the effects of habitat loss or shifting environmental conditions on species with low dispersal capacity. More broadly, we provide the first step towards a more comprehensive framework for integrating extinction risk, managed relocations and climate change information into range‐wide conservation management.     

Oxygen concentration drives local adaptation in the greenlip abalone (Haliotis laevigata)

Understanding adaptation has become one of the major biological questions especially in the light of rapid environmental changes induced by climate change. Ocean temperatures are rising which triggers massive changes in water chemistry and thereby alters the living environment of all marine organisms. Studying adaptation, however, can be tricky because spatial genetic patterns might also occur due to random effects, for example, genetic drift. Genetic drift is reduced in very large and well‐connected populations, such as in broadcast marine spawning organisms. Here, spatial genetic divergence is likely to be produced by selection. In this issue of Molecular Ecology, Sandoval‐Castillo et al. (2018) investigated patterns of spatial genetic divergence and their association with environmental factors in the greenlip abalone (Haliotis laevigata). This commercially important species of mollusc is a broadcast spawner with large population sizes, rendering genetic drift an unlikely factor in the genetic divergence of wild populations. Sandoval‐Castillo et al. (2018) used a ddRAD genomic approach to test for genetic divergence between sampled populations while also measuring different environmental factors, for example, water temperature and oxygen content. The majority of identified SNPs was putatively neutral and showed only low levels of genetic divergence between field sites. However, 323 candidate adaptive markers were identified that clearly separated the individuals into five different clusters. These genetic clusters correlated with environmental clusters mainly determined by water temperature and (correlated) oxygen concentration. Gene annotation of the candidate SNPs revealed a large proportion of loci being involved in biological processes influenced by oxygen availability. The study by Sandoval‐Castillo et al. (2018) in this issue of Molecular Ecology exemplifies the benefits of combining genomic studies with ecological data. It is a great starting point for more detailed (gene function, physiology) as well as broader (biodiversity) investigations that might help us to better understand adaptation and predict ecosystems' resilience and resistance to environmental disturbances. In addition, this information can be applied to implement optimal conservation regime policies and sustainable harvesting strategies, hopefully protecting biodiversity as well as commercial interests in marine life.     

Metapopulation dynamics in a changing climate: Increasing spatial synchrony in weather conditions drives metapopulation synchrony of a butterfly inhabiting a fragmented landscape

Habitat fragmentation and climate change are both prominent manifestations of global change, but there is little knowledge on the specific mechanisms of how climate change may modify the effects of habitat fragmentation, for example, by altering dynamics of spatially structured populations. The long‐term viability of metapopulations is dependent on independent dynamics of local populations, because it mitigates fluctuations in the size of the metapopulation as a whole. Metapopulation viability will be compromised if climate change increases spatial synchrony in weather conditions associated with population growth rates. We studied a recently reported increase in metapopulation synchrony of the Glanville fritillary butterfly (Melitaea cinxia) in the Finnish archipelago, to see if it could be explained by an increase in synchrony of weather conditions. For this, we used 23 years of butterfly survey data together with monthly weather records for the same period. We first examined the associations between population growth rates within different regions of the metapopulation and weather conditions during different life‐history stages of the butterfly. We then examined the association between the trends in the synchrony of the weather conditions and the synchrony of the butterfly metapopulation dynamics. We found that precipitation from spring to late summer are associated with the M. cinxia per capita growth rate, with early summer conditions being most important. We further found that the increase in metapopulation synchrony is paralleled by an increase in the synchrony of weather conditions. Alternative explanations for spatial synchrony, such as increased dispersal or trophic interactions with a specialist parasitoid, did not show paralleled trends and are not supported. The climate driven increase in M. cinxia metapopulation synchrony suggests that climate change can increase extinction risk of spatially structured populations living in fragmented landscapes by altering their dynamics.     

Climate,physiological tolerance and sex‐biased dispersal shape genetic structure of Neotropical orchid bees

Understanding the impact of past climatic events on the demographic history of extant species is critical for predicting species' responses to future climate change. Palaeoclimatic instability is a major mechanism of lineage diversification in taxa with low dispersal and small geographical ranges in tropical ecosystems. However, the impact of these climatic events remains questionable for the diversification of species with high levels of gene flow and large geographical distributions. In this study, we investigate the impact of Pleistocene climate change on three Neotropical orchid bee species (Eulaema bombiformis, E. meriana and E. cingulata) with transcontinental distributions and different physiological tolerances. We first generated ecological niche models to identify species‐specific climatically stable areas during Pleistocene climatic oscillations. Using a combination of mitochondrial and nuclear markers, we inferred calibrated phylogenies and estimated historical demographic parameters to reconstruct the phylogeographical history of each species. Our results indicate species with narrower physiological tolerance experienced less suitable habitat during glaciations and currently exhibit strong population structure in the mitochondrial genome. However, nuclear markers with low and high mutation rates show lack of association with geography. These results combined with lower migration rate estimates from the mitochondrial than the nuclear genome suggest male‐biased dispersal. We conclude that despite large effective population sizes and capacity for long‐distance dispersal, climatic instability is an important mechanism of maternal lineage diversification in orchid bees. Thus, these Neotropical pollinators are susceptible to disruption of genetic connectivity in the event of large‐scale climatic changes.     

Mutualist‐mediated effects on species' range limits across large geographic scales

Understanding the processes determining species range limits is central to predicting species distributions under climate change. Projected future ranges are extrapolated from distribution models based on climate layers, and few models incorporate the effects of biotic interactions on species' distributions. Here, we show that a positive species interaction ameliorates abiotic stress, and has a profound effect on a species' range limits. Combining field surveys of 92 populations, 10 common garden experiments throughout the range, species distribution models and greenhouse experiments, we show that mutualistic fungal endophytes ameliorate drought stress and broaden the geographic range of their native grass host Bromus laevipes by thousands of square kilometres (~ 20% larger) into drier habitats. Range differentiation between fungal‐associated and fungal‐free grasses was comparable to species‐level range divergence of congeners, indicating large impacts on range limits. Positive biotic interactions may be underappreciated in determining species' ranges and species' responses to future climates across large geographic scales.     

Tests of species‐specific models reveal the importance of drought in postglacial range shifts of a Mediterranean‐climate tree: insights from integrative distributional,demographic and coalescent modelling and ABC model selection

Past climate change has caused shifts in species distributions and undoubtedly impacted patterns of genetic variation, but the biological processes mediating responses to climate change, and their genetic signatures, are often poorly understood. We test six species‐specific biologically informed hypotheses about such processes in canyon live oak (Quercus chrysolepis) from the California Floristic Province. These hypotheses encompass the potential roles of climatic niche, niche multidimensionality, physiological trade‐offs in functional traits, and local‐scale factors (microsites and local adaptation within ecoregions) in structuring genetic variation. Specifically, we use ecological niche models (ENMs) to construct temporally dynamic landscapes where the processes invoked by each hypothesis are reflected by differences in local habitat suitabilities. These landscapes are used to simulate expected patterns of genetic variation under each model and evaluate the fit of empirical data from 13 microsatellite loci genotyped in 226 individuals from across the species range. Using approximate Bayesian computation (ABC), we obtain very strong support for two statistically indistinguishable models: a trade‐off model in which growth rate and drought tolerance drive habitat suitability and genetic structure, and a model based on the climatic niche estimated from a generic ENM, in which the variables found to make the most important contribution to the ENM have strong conceptual links to drought stress. The two most probable models for explaining the patterns of genetic variation thus share a common component, highlighting the potential importance of seasonal drought in driving historical range shifts in a temperate tree from a Mediterranean climate where summer drought is common.