Do stream fish track climate change? Assessing distribution shifts in recent decades

Understanding the ability of species to shift their distribution ranges in response to climate change is crucial for conservation biologists and resources managers. Although freshwater ecosystems include some of the most imperilled fauna worldwide, such range shifts have been poorly documented in streams and rivers and have never been compared to the current velocity of climate change. Based on national monitoring data, we examined the distributional changes of 32 stream fish species in France and quantified potential time lags in species responses, providing a unique opportunity to analyze range shifts over recent decades of warming in freshwater environments. A multi‐facetted approach, based on several range measures along spatial gradients, allowed us to quantify range shifts of numerous species across the whole hydrographic network between an initial period (1980–1992) and a contemporary one (2003–2009), and to contrast them to the rates of isotherm shift in elevation and stream distance. Our results highlight systematic species shifts towards higher elevation and upstream, with mean shifts in range centre of 13.7 m decade^?1 and 0.6 km decade^?1, respectively. Fish species displayed dispersal‐driven expansions along the altitudinal gradient at their upper range limit (61.5 m decade^?1), while substantial range contractions at the lower limit (6.3 km decade^?1) were documented for most species along the upstream–downstream gradient. Despite being consistent with the geographic variation in climate change velocities, these patterns reveal that the majority of stream fish have not shifted at a pace sufficient to track changing climate, in particular at their range centre where range shifts lag far behind expectation. Our study provides evidence that stream fish are currently responding to recent climate warming at a greater rate than many terrestrial organisms, although not as much as needed to cope with future climate modifications.     

Does the interpolation accuracy of species distribution models come at the expense of transferability?

Model transferability (extrapolative accuracy) is one important feature in species distribution models, required in several ecological and conservation biological applications. This study uses 10 modelling techniques and nationwide data on both (1) species distribution of birds, butterflies, and plants and (2) climate and land cover in Finland to investigate whether good interpolative prediction accuracy for models comes at the expense of transferability – i.e. markedly worse performance in new areas. Models’ interpolation and extrapolation performance was primarily assessed using AUC (the area under the curve of a receiver characteristic plot) and Kappa statistics, with supplementary comparisons examining model sensitivity and specificity values. Our AUC and Kappa results show that extrapolation to new areas is a greater challenge for all included modelling techniques than simple filling of gaps in a well‐sampled area, but there are also differences among the techniques in the degree of transferability. Among the machine‐learning modelling techniques, MAXENT, generalized boosting methods (GBM), and artificial neural networks (ANN) showed good transferability while the performance of GARP and random forest (RF) decreased notably in extrapolation. Among the regression‐based methods, generalized additive models (GAM) and generalized linear models (GLM) showed good transferability. A desirable combination of good prediction accuracy and good transferability was evident for three modelling techniques: MAXENT, GBM, and GAM. However, examination of model sensitivity and specificity revealed that model types may differ in their tendencies to either increased over‐prediction of presences or absences in extrapolation, and some of the methods show contrasting changes in sensitivity vs specificity (e.g. ANN and GARP). Among the three species groups, the best transferability was seen with birds, followed closely by butterflies, whereas reliable extrapolation for plant species distribution models appears to be a major challenge at least at this scale. Overall, detailed knowledge of the behaviour of different techniques in various study settings and with different species groups is of utmost importance in predictive modelling.     

Do traits of plant species predict the efficacy of species distribution models for finding new occurrences?

Species distribution models (SDMs) are used to test ecological theory and to direct targeted surveys for species of conservation concern. Several studies have tested for an influence of species traits on the predictive accuracy of SDMs. However, most used the same set of environmental predictors for all species and/or did not use truly independent data to test SDM accuracy. We built eight SDMs for each of 24 plant species of conservation concern, varying the environmental predictors included in each SDM version. We then measured the accuracy of each SDM using independent presence and absence data to calculate area under the receiver operating characteristic curve (AUC) and true positive rate (TPR). We used generalized linear mixed models to test for a relationship between species traits and SDM accuracy, while accounting for variation in SDM performance that might be introduced by different predictor sets. All traits affected one or both SDM accuracy measures. Species with lighter seeds, animal‐dispersed seeds, and a higher density of occurrences had higher AUC and TPR than other species, all else being equal. Long‐lived woody species had higher AUC than herbaceous species, but lower TPR. These results support the hypothesis that the strength of species–environment correlations is affected by characteristics of species or their geographic distributions. However, because each species has multiple traits, and because AUC and TPR can be affected differently, there is no straightforward way to determine a priori which species will yield useful SDMs based on their traits. Most species yielded at least one useful SDM. Therefore, it is worthwhile to build and test SDMs for the purpose of finding new populations of plant species of conservation concern, regardless of these species’ traits.     

Light-induced swimming of Daphnia: can laboratory experiments predict diel vertical migration?

Vertical displacement velocity of a Daphniagaleata × hyalina clone was quantified inrelation to changes in the relative rate of lightchange. An increase in the latter variable triggers anenhanced swimming response, and this response is againelicited when a second increase in the rate ofrelative light increase is applied. Decreases in therate of light increase affect phototactic swimming ina similar way. The acceleration/deceleration assistedstimulus-response system is an extension of the ideaof phototaxis as the underlying behavioural mechanismfor vertical migration, and suggests that continuousaccelerations in light change also affect verticaldisplacements observed in the field. A simple dielvertical migration simulation model was used tocalculate the vertical displacement of Daphniain relation to the natural light change at sunrise.The calculated vertical displacement fits nicely inthe temporal range of the observed averaged downwardmigration of adult Daphnia in Lake Maarsseveen.The calculated migration amplitude, however, islarger than the change in mean population depthobserved in nature.     

Mechanisms structuring stream fish assemblages: Are there lessons from introduced species?

Synopsis Stream fish faunas are being increasingly subjected to non-native fishes. Successful establishment of non-native forms varies widely between geographic regions (38–77%), but is generally greater in areas that are either altered by man or initially depauperate in fish species. While such introductions have generally had undesirable effects on native fish species, they show no signs of decreasing. Thus, this essay is an attempt to determine if the introduction of non-native fishes may provide insights into processes structuring stream fish assemblages. There are, unfortunately, few detailed ecological studies documenting the response of stream fish assemblages to introduced fishes. Of the 31 studies included in my analysis, the majority (77%) documents a decline in native fishes following the introduction of exotic or transplanted forms. Only 10 studies examined shifts in resource use, of which 5 documented or suggested shifts in habitat. Overall, the responses of native stream fish assemblages to non-native fishes suggest that biotic interactions are important in structuring the impacted assemblages, being implicated in 62% of the studies. Proposed or demonstrated mechanisms are divided equally between competition and predation. Unfortunately, pre-disturbance data are generally lacking so that processes important in structuring native fish assemblages cannot be determined.     

Unravelling insect declines: can space replace time?

Temporal trends in insect numbers vary across studies and habitats, but drivers are poorly understood. Suitable long-term data are scant and biased, and interpretations of trends remain controversial. By contrast, there is substantial quantitative evidence for drivers of spatial variation. From observational and experimental studies, we have gained a profound understanding of where insect abundance and diversity is higher—and identified underlying environmental conditions, resource change and disturbances. We thus propose an increased consideration of spatial evidence in studying the causes of insect decline. This is because for most time series available today, the number of sites and thus statistical power strongly exceed the number of years studied. Comparisons across sites allow quantifying insect population risks, impacts of land use, habitat destruction, restoration or management, and stressors such as chemical and light pollution, pesticides, mowing or harvesting, climatic extremes or biological invasions. Notably, drivers may not have to change in intensity to have long-term effects on populations, e.g. annually repeated disturbances or mortality risks such as those arising from agricultural practices. Space-for-time substitution has been controversially debated. However, evidence from well-replicated spatial data can inform on urgent actions required to halt or reverse declines—to be implemented in space.     

Distance,dams and drift: what structures populations of an endangered,benthic stream fish?

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Primary glioblastoma cultures: can profiling of stem cell markers predict radiotherapy sensitivity?

Human glioblastomas may be hierarchically organized. Within this hierarchy, glioblastoma‐initiating cells have been proposed to be more resistant to radiochemotherapy and responsible for recurrence. Here, established stem cell markers and stem cell attributed characteristics such as self‐renewal capacity and tumorigenicity have been profiled in primary glioblastoma cultures to predict radiosensitivity. Furthermore, the sensitivity to radiotherapy of different subpopulations within a single primary glioblastoma culture was analyzed by a flow cytometric approach using Nestin, SRY (sex‐determining region Y)‐box 2 (SOX2) and glial fibrillary acidic protein. The protein expression of Nestin and SOX2 as well as the mRNA levels of Musashi1, L1 cell adhesion molecule, CD133, Nestin, and pleiomorphic adenoma gene‐like 2 inversely correlated with radioresistance in regard to the clonogenic potential. Only CD44 protein expression correlated positively with radioresistance. In terms of proliferation, Nestin protein expression and Musashi1, pleiomorphic adenoma gene‐like 2, and CD133 mRNA levels are inversely correlated with radioresistance. Higher expression of stem cell markers does not correlate with resistance to radiochemotherapy in the cancer genome atlas glioblastoma collective. SOX2 expressing subpopulations exist within single primary glioblastoma cultures. These subpopulations predominantly form the proliferative pool of the primary cultures and are sensitive to irradiation. Thus, profiling of established stem cell markers revealed a surprising result. Except CD44, the tested stem cell markers showed an inverse correlation between expression and radioresistance.

     

Are comparisons of species distribution models biased? Are they biologically meaningful?

A major problem in ecology is to understand how environmental requirements change over space and time. To this end, numerous authors have attempted to use comparisons of species’ distributions as a surrogate for comparisons of environmental requirements. Unfortunately, it is currently unclear when comparisons of species’ distributions produce reliable inferences about changes in environmental requirements. To address this problem, I develop an analytic model that identifies the conditions under which a comparison of species’ distribution models can serve as surrogate for a comparison of environmental requirements. This work demonstrates that 1) comparisons of species’ distributions typically produce biased comparisons of environmental requirements, 2) assuming distribution models are fit appropriately, it is possible to compare environmental requirements of distinct taxa, 3) there are multiple biologically relevant questions we can address using comparisons of distribution models, with each question corresponding to a distinct measure of the difference between distribution models. By developing an analytic model for comparisons of species’ distributions this work helps to clarify and remedy poorly understood sources of error associated with existing methods.     

Environmental variability and fisheries: what can models do?

This review is based on 58 climate-fisheries models published over the last 28 years that describe the impacts of fishery pressure and environmental variability on populations and ecosystems and include basic principles of population dynamics. It points out that the incorporation of environmental factors in fishery models has already been done and is of great importance for future models used in the assessment of marine resources. The work is guided by the questions to what extent have these models a) enhanced our understanding of the interrelationships between the environment, the fishery and the state of the exploited resources and b) helped to improve the prediction of population dynamics and the assessment of marine resources. For each of the six most commonly used model categories a case study is critically analyzed. The problems of “breaking relationships” between environmental factors and the biological response used in models, the trade-off between model complexity (realism) and simplicity (data availability) and the potential of multivariate climate indices for forecasting ecosystem states and for use as proxies for combined models are discussed, as are novel non-linear and spatially explicit modeling approaches. Approaches differ in terms of model complexity, use of linear or non-linear equations, number of parameters, forecast time horizon and type of resource modelled. A majority of the models were constructed for fish and invertebrate stocks of the northeast Pacific and the epicontinental seas of the Atlantic, reflecting the advancement of fisheries science in these regions. New, in parts highly complex models and sophisticated approaches were identified. The reviewed studies demonstrate that the performance of fished stocks can better be described if environmental or climatic variability is incorporated into the fisheries models. We conclude that due to the already available knowledge, the greatly enhanced computer power, new methods and recent findings of large-scale climatic/oceanographic cycles, fisheries modeling should progress greatly in the coming years.     

Culvert replacements: improvement of stream biotic integrity?

Roads and associated stream crossings can modify and degrade natural hydrology of a system and alter organism movement. Culvert replacement and stream crossing improvements are extremely common and often done with the intent to improve biotic integrity of a system. We evaluated 3 sites where poor road‐stream crossings were improved by replacing improper culverts with full‐span natural bottom structures. We used a before‐after‐control‐impact paired series (BACIPS) design to determine if there was evidence of associated improvement in biotic integrity of the stream communities. Biotic integrity indices developed for coldwater fish and macroinvertebrates in the Northern Lakes and Forests Ecoregion were used to estimate responses of the biotic communities adjacent to culvert replacements. With poor to fair fish and macroinvertebrate communities prior to culvert replacement, we predicted communities would show improvement into the good range of the indices. With 2–4 years of pre‐data and 3–5 years of postdata, we were not able to detect improvements in overall biotic integrity utilizing fish or macroinvertebrate index scores. Road crossing improvements may synergistically restore stream ecosystems, restore natural sediment dynamics, and improve passage; however, in these cases local biotic integrity scores were not significantly improved. Culvert replacements are often developed based on the potential, or the perception, that they will restore ecological integrity and biological communities or fisheries; however, as restoration practitioners, researchers, and managers, assessing these claims and learning from prior restoration attempts is necessary.     

Normal giants? Temporal and latitudinal shifts of Palaeozoic marine invertebrate gigantism and global change

During and after the Cambrian explosion, very large marine invertebrate species have evolved in several groups. Gigantism in Carboniferous land invertebrates has been explained by a peak in atmospheric oxygen concentrations, but Palaeozoic marine invertebrate gigantism has not been studied empirically and explained comprehensively. By quantifying the spatiotemporal distribution of the largest representatives of some of the major marine invertebrate clades (orthoconic cephalopods, ammonoids, trilobites, marine eurypterids), we assessed possible links between environmental parameters (atmospheric or oceanic oxygen concentrations, ocean water temperature or sea level) and maximum body size, but we could not find a straightforward relationship between both. Nevertheless, marine invertebrate gigantism within these groups was temporally concentrated within intervals of high taxonomic diversity (Ordovician, Devonian) and spatially correlated with latitudes of high occurrence frequency. Regardless of whether temporal and spatial variation in sampled diversity and occurrence frequency reflect true biological patterns or sampling controls, we find no evidence that the occurrences of giants in these groups were controlled by optimal conditions other than those that controlled the group as a whole; if these conditions shift latitudinally, occurrences of giants will shift as well. It is tempting to attribute these shifts to contemporary changes in temperature, oxygen concentrations in the atmosphere and the oceans as well as global palaeogeography over time, but further collection‐based studies are necessary on finer stratigraphic and phylogenetic resolution to corroborate such hypotheses and rule out sampling or collection biases.     

To what extent can linear finite element models of human femora predict failure under stance and fall loading configurations?

Proximal femur strength estimates from computed tomography (CT)-based finite element (FE) models are finding clinical application. Published models reached a high in-vitro accuracy, yet many of them rely on nonlinear methodologies or internal best-fitting of parameters. The aim of the present study is to verify to what extent a linear FE modelling procedure, fully based on independently determined parameters, can predict the failure characteristics of the proximal femur in stance and sideways fall loading configurations.     

Continental scale patterns of biodiversity: can higher taxa accurately predict African plant distributions?

The distribution maps of a total of 3563 species, which represent 8.9% of the known African angiosperm flora, were entered into cells representing a one-degree latitude–longitude grid of Sub-Saharan Africa. The computer programme WORLDMAP was used to explore continental scale patterns of biodiversity. The maps were used to assess the use of higher taxa as a surrogate measure for predicting patterns of species richness. Genera were found to predict species richness distributions most closely, with higher taxa (families, orders, subclasses) exhibiting progressively worse correlations. However in two areas, the Cape Region of South Africa and coastal Cameroon, there was a higher species to genus ratio than in other areas of Africa. In the Cape Region this meant that generic richness failed to predict species richness. Hotspots, defined as the 5% of grid cells with the highest scores for richness and range-size rarity, were identified for species and higher taxa. Whilst a high percentage of species richness hotspots were predicted by higher taxa, there were important exceptions like the Cape Region. Species range-size rarity hotspots were not well predicted by higher taxa. Hotspots of higher taxa (families and orders) do not therefore accurately predict the location of species hotspots. Higher taxa appear to provide a powerful and accurate tool that can be used to predict large scale patterns of species biodiversity in Sub-Saharan Africa. However care must be taken when using taxa higher than genera, especially if selecting areas of highest conservation priority. The special case of the Cape Region indicates the danger of extending predictive generalizations as the ecological mechanisms that promote and retain species may not be the same in all places. © 2002 The Linnean Society of London, Botanical Journal of the Linnean Society , 138 , 225–235.     

Animal models of human amyloidoses: Are transgenic mice worth the time and trouble?

The amyloidoses are the prototype gain of toxic function protein misfolding diseases. As such, several naturally occurring animal models and their inducible variants provided some of the first insights into these disorders of protein aggregation. With greater analytic knowledge and the increasing flexibility of transgenic and gene knockout technology, new models have been generated allowing the interrogation of phenomena that have not been approachable in more reductionist systems, i.e. behavioral readouts in the neurodegenerative diseases, interactions among organ systems in the transthyretin amyloidoses and taking pre-clinical therapeutic trials beyond cell culture. The current review describes the features of both transgenic and non-transgenic models and discusses issues that appear to be unresolved even when viewed in their organismal context.