Cover Image Gallery
Animals often display a marked tendency to return to previously visited locations that contain important resources, such as water, food, or developing brood that must be provisioned. Ant colonies typically consist of different worker castes which each exhibit ﬁdelity to different sites within the nest; nurses stay inside and tend to the brood, whereas outside-nest workers forage and guard the nest entrance. This image depicts brood and workers of the rock ant Temnothorax albipennis, which displays strong site ﬁdelity.
In this issue, Richardson et al identify the important sites to which individuals are attracted through statistical comparisons between the observed spatial trajectories (gathered from workers each marked with a unique combination of coloured paint dots), and null model trajectories that lack spatial biases. By quantifying the overlap between the sites visited by different workers, they construct spatial networks in which individuals are strongly connected if they frequent the same spatial locations, or weakly connected if they frequent different parts of the nest. Whilst many studies have used encounter patterns to identify sub-populations within animal groups, the spatial networks provide an alternative framework for identifying sub-groups within large societies in which individuals may visit the same places, but never make contact.
Photo © N. R. Franks, University of Bristol
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Measuring site fidelity and spatial segregation within animal societies
Thomas O. Richardson, Luca Giuggioli, Nigel R. Franks and Ana B. Sendova-Franks
This month’s cover image shows the bare-bottomed sunburst lichen (Xanthomendoza fulva (Hoffm.) Søchting, Kärnefelt & S.Y. Kondr.) growing in a tree trunk in a forest located in Siskiyou County along the border between Oregon and California, USA. It can grow up to 1 cm or may coalesce over large areas forming rosettes or colonies of small ascending lobes, like those in the image. This species can be found in several boreal and temperate regions of the world, both in semi-open and shaded habitats growing over bark, wood or rocks.
In the related article, Matos et al. design a novel framework to incorporate surrogates of lichen species richness, shifts in species composition and metrics of functional diversity collected by different sampling methodologies. Lichens, such as the species depicted in the image, have been used as ecological indicators of the effects of the major drivers of global change since the beginning of the industrial revolution to the present. The framework developed will enable future cross-continental analysis of lichen biodiversity change from North America and Europe, enabling a more thoroughly comprehension of biodiversity response to global change.
Photo © Paula Matos
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Tracking global change using lichen diversity: towards a global-scale ecological indicator
Paula Matos, Linda Geiser, Amanda Hardman, Doug Glavich, Pedro Pinho, Alice Nunes, Amadeu M.V.M. Soares and Cristina Branquinho
The cover image of this special issue was taken along West Maroon Pass near Gothic, Colorado, home of the Rocky Mountain Biological Laboratory (RMBL). Instituted in 1928, thousands of students and scientists have conducted research in this area, making the ecosystems around RMBL some of the most intensively studied in the world. Long-term climate monitoring, natural history data sets, and field experiments have established RMBL as an internationally renowned center for studies of climate change and local adaptation.
In this special issue, Wadgymar et al. advocate for studies to move beyond establishing patterns of local adaptation to uncovering the processes that generate it. A literature survey revealed the need for studies to examine the genetic basis of local adaptation in a variety of natural systems. Furthermore, studies are needed to investigate interactions among the multitude of environmental factors often involved in the generation and maintenance of local adaptation. The authors demonstrate that manipulative field experiments combined with genetic, genomic, and molecular techniques hold the most promise for propelling us forward in our understanding of local adaptation. From an applied perspective, this knowledge can be used to optimize crops, conserve endangered species, and predict how anthropogentic forces will affect natural populations.
Photo © Susana Wadgymar
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Identifying targets and agents of selection: innovative methods to evaluate the processes that contribute to local adaptation
Susana M. Wadgymar, David B. Lowry, Billie A. Gould, Caitlyn N. Byron, Rachel M. Mactavish and Jill T. Anderson
Macrozoobenthic organisms are widely used to assess stream ecosystem health. Traditionally, this was done by morphological determination. However, the mostly larval specimens can often not be reliably identiﬁed to species level. DNA metabarcoding provides reliable solutions here. Rather than studying individual specimens, the complete invertebrate sample is thoroughly homogenised using liquid nitrogen for DNA extraction of the whole community, as shown on the picture. Then a speciﬁc “barcoding” gene fragment is ampliﬁed using PCR, sequenced on a high-throughput sequencer and compared against available reference databases for taxonomic assignment. As benthic communities are usually very diverse, the PCR primers have to be designed to work on all the targeted groups like may- stone- and caddisﬂies, aquatic beetles and molluscs. Here the R package PrimerMiner assists in primer development by automated batch downloading and processing of sequence data from public databases, as well as visualising sequence diversity for each group to ﬁnd potential universal primer binding sites.
Photo © Vasco Elbrecht
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PrimerMiner: an r package for development and in silico validation of DNA metabarcoding primers
Vasco Elbrecht and Florian Leese
This month’s cover image was used as the banner for the Eco-Stats’ 15 Conference “Technological advances between Ecology and Statistics” held at the University of New South Wales Sydney, Australia, in December 2015. The outcomes of the conference are the subject of a Special Feature in this issue. The image shows a ﬂock of sulphur-crested cockatoos (Cacatua galerita) morphing into a residual plot, to symbolise the merging of ideas between ecology and statistics. It was conceptualised by David Warton and realised by Susannah Waters (UNSW Sydney, Australia) The Special Feature consists of ﬁve papers showcasing interdisciplinary collaboration, centred around problems estimating biodiversity and how it changes over space and time. It highlights the potential of interdisciplinary research, and of meetings designed to bring together researchers across disciplines, as a vehicle for scientiﬁc advances.
Photo © Susannah Waters (UNSW Sydney, Australia)
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Technical advances at the interface between ecology and statistics: improving the biodiversity knowledge generation workflow
David I. Warton and Melodie A. McGeoch
This issue’s cover image shows an endangered green turtle (Chelonia mydas) recovering at the Turtle Clinic in Moorea Island, French Polynesia, after being injured by a spear gun. Turtles continue to be exposed to intense fishing effort in French Polynesia despite their protected status. This highlights the importance of regular monitoring, and proper assessment of conservation interventions in general, to derive reliable conclusions and information to managers and decision-makers. However, it is often challenging to reliably estimate the true effect of an intervention, owing to the diverse sources of spatial and temporal variability in the studied ecosystem.
Thiault et al. developed a new statistical approach – called Progressive-Change BACIPS (Before-After Control-Impact Paired-Series) – that extends and generalizes the scope of BACIPS analyses to time-dependent effects. After quantifying the statistical power and accuracy of the method with simulated datasets, they used marine and terrestrial case studies to illustrate and validate their approach. They found that the Progressive-Change BACIPS leads to better estimates of the effects of environmental impacts and the time-scales over which they operate.
Photo © Lauric Thiault
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Progressive-Change BACIPS: a flexible approach for environmental impact assessment
Lauric Thiault, Laëtitia Kernaléguen, Craig W. Osenberg and Joachim Claudet
This month’s cover image looks into the eye of a Verreaux's eagle (Aquila verreauxii). This species is found in mountainous regions of sub-Saharan Africa, where cliffs provide suitable nesting habitat. The eagle pictured here is equipped with a tracking device from the University of Amsterdam Bird Tracking System (www.UvA-BiTS.nl). In South Africa concerns over the impacts of land use change and the development of wind farms have led to the implementation of tracking studies to better understand movement patterns of this majestic bird. Such studies have provided a wealth of high-resolution data and opportunities to explore sophisticated statistical methods for analysis of animal behaviour.
Leos-Barajas et al use accelerometer data from aerial (Verreaux’s eagle) and marine (blacktip reef shark) systems to demonstrate the use of hidden Markov models (HMMs) in providing quantitative measures of behaviour. HMMs are well suited to analysing animal accelerometer data because they account for serial autocorrelation in data and importantly they allow for inferences to be made about relative activity and behaviour when animals cannot be directly observed. In addition, HMMs provide data-driven estimates of the underlying distributions of the acceleration metrics, and the probability of switching between states, possibly as a function of covariates. The framework provided in the author’s paper “Analysis of animal accelerometer data using hidden Markov models” can be applied to a wide range of activity data, thereby providing exciting opportunities for understanding drivers of individual animal behaviour.
Photo © Andrew Jenkins
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Analysis of animal accelerometer data using hidden Markov models
Vianey Leos-Barajas, Theoni Photopoulou, Roland Langrock, Toby A. Patterson, Yuuki Y. Watanabe, Megan Murgatroyd and Yannis P. Papastamatiou
This cover image shows the Trupchun Valley, located in the Swiss National Park (SNP). Studying the development of nature in the absence of human interference has been a key objective since the SNP was established in 1914. Assessing dynamic vegetation changes has played an important role in the SNP’s research tradition, with the establishment of ? rst long-term observation plots by Josias Braun-Blanquet already in 1917. Comparing vegetation maps produced for nearly 100 years motivated our research on “How to predict plant functional types using imaging spectroscopy: Linking vegetation community traits, plant functional types and spectral response”. Despite these maps being elaborate, they either lack the spatial coverage or detail to allow us to understand how inter- and intraspeci? c plant trait variability and diversity patterns are in? uenced by topography, microclimate, herbivory and former land use. We were thus excited to ? nd strong relationships between plant life/growth forms, strategy types and indicators, and biochemical and structural vegetation traits which determine the spectral response in optical remote sensing instruments. Linking vegetation community’s functional signatures to spectral signatures allows us to accurately predict plant functional types using airborne imaging spectroscopy, substantially advancing our understanding of ecosystem processes in space and time.
Photo © Christian Schmid
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How to predict plant functional types using imaging spectroscopy: linking vegetation community traits, plant functional types and spectral response
Anna K. Schweiger, Martin Schütz, Anita C. Risch, Mathias Kneubühler, Rudolf Haller and Michael E. Schaepman
This month’s cover image shows a beautiful, brilliantly coloured fairy pitta (Pitta nympha) perched on a bamboo branch. The migratory fairy pitta breeds in Northeast Asia (Japan, South Korea, east China and Taiwan) from late April to September and winters mainly in Borneo from October to March. In Taiwan, the fairy pitta is also called the “eight colored bird” (as there are eight colors in its plumage: beige, yellow, green, brown, black, white, red on the vent area, and shiny blue on its wings) or the “little forest fairy” (as its body length is around 16–19 cm). The fairy pitta is rare and elusive, and is classi? ed as Vulnerable on the IUCN Red List, mainly due to the destruction of its primary habitats.
The majestic beauty of this fairy has provided the authors of ‘iNEXT: An R package for rarefaction and extrapolation of species diversity (Hill numbers)’ with a wealth of inspiration in formulating their methodology and relevant software to compute and plot the seamless sample-size- and sample-coverage-based rarefaction and extrapolation sampling curves for species diversity. Hsieh, Ma and Chao developed the iNEXT (iNterpolation and EXTrapolation) R package, which features an easy-to-use interface and ef? ciently uses all data to not only make robust and detailed inferences about the sampled assemblages, but also to make objective comparisons of species diversity among multiple assemblages.
Photo © Jia Hong Chen
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iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers)
T. C. Hsieh, K. H. Ma and Anne Chao
The Oostvaardersplassen nature reserve, Netherlands, was established on polder land reclaimed from Lake IJsselmeer in 1968. Re-wilding was initiated at this site from 1983 with the introduction of Heck cattle (Bos taurus), Konik horses (Equus ferus caballus) and red deer (Cervus elaphus). Moreover, a multitude of ponds were created throughout the reserve between 1985 and 2000 for avian biodiversity. The site is managed with a policy of minimal intervention, i.e. the population size of freely roaming large herbivores is not controlled by culling, no supplementary feeding is given during winter and vegetation is not managed. The only intervention is aimed to avoid unnecessary suffering and consist in shooting animals identi?ed as too weak to survive winter.
Most of the research examining the relationship between large herbivores and their impact on landscapes has used extant studies. An alternative approach is to estimate the impact of variations in herbivore populations through time using fossil dung fungal spores and pollen in sedimentary sequences. The ponds at Oostvaardersplassen provided the ideal settings for Baker et al. to develop further the dung fungal spore method and determine the relationship between spore abundance in sediments and herbivore biomass densities. Their results indicate that this method provides a robust quantitative measure of herbivore population size over time.
Photo © Henk Hupkes, Staatsbosbeheer
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Quantification of population sizes of large herbivores and their long-term functional role in ecosystems using dung fungal spores
Ambroise G. Baker, Perry Cornelissen, Shonil A. Bhagwat, Fransciscus W. M. Vera and Katherine J. Willis
Pictured here is a Mountain-yellow legged frog (Rana muscosa), an endangered amphibian living in high elevation lakes and streams in California's Sierra Nevada mountains. This species has experienced drastic population declines across its native range largely due to the devastating effects of the amphibian chytrid fungus. This fungal pathogen infects the skin of amphibians as they reside in their aquatic habitats, eventually leading to amphibian morbidity and often death.
In our study, we build a novel framework for linking individual-level measurements of host-pathogen interactions to population-level predictions of epizootic dynamics. We use this modeling framework to gain insight into the temperature-dependent dynamics of chytrid fungus-induced Mountain-yellow legged frog declines. This framework can also be used to understand the dynamics of other diseases of conservation concern such as white-nose syndrome in bats and facial tumour disease in Tasmanian devils.
Photo © Mark Wilber
Mark Q. Wilber, Kate E. Langwig, Auston Marm Kilpatrick, Hamish I. McCallum and Cheryl J. Briggs
This month’s cover image shows a Hoary Bat or Hawaiian Hoary Bat (Lasiurus cinereus), a charismatic species due to its beautiful and unique fur colouration. It is an insectivorous and migratory bat, widely distributed across the Americas, that mainly inhabits forested areas. This species, like many other Mexican bats, is poorly known and is under threat due to the high rates of climate and land-use change in the country. The individual shown in the picture was captured in the state of Chihuahua, Mexico. It was measured, identified, recorded and immediately released on site as part of a project to ensemble a national bat acoustic library.
Zamora-Gutierrez et al. compiled the biggest library of bat sounds to identify bats from their echolocation calls in a megadiverse country. They have shown that it is possible to acoustically identify a high number of bat species for rapid biodiversity assessments. Acoustic surveys are increasingly used to monitor biodiversity and bats are ideal candidates for this as they constantly emit sound to explore their surroundings. It is vital to map ecological communities and track their changes through time in order to better understand and counteract the effects of the Anthropocene.
Photo © Veronica Zamora-Gutierrez
Veronica Zamora-Gutierrez, Celia Lopez-Gonzalez, M. Cristina MacSwiney Gonzalez, Brock Fenton, Gareth Jones, Elisabeth K. V. Kalko, Sebastien J. Puechmaille, Vassilios Stathopoulos and Kate E. Jones
This month’s cover image shows two male sleepy lizards (Tiliqua rugosa) fighting. Fights in these long-lived lizards allow males to exclude others from their core home range, and to follow their monogamous female partners throughout the breeding season. Since this species is the main host for some local ticks, it is also a suitable model system for studying the effects of host-behavior on parasite transmission. Hence, identifying the ecological factors that shape the structure of lizards’ social networks is important both for understanding their biology and for disease ecology. Indeed, separating the contributions of ecological constraints and social preference is a general challenge in social networks studies (i.e., did two animals meet since they had to share a resource or since they were attracted to each other?).
Spiegel et al present a new method for analyzing social networks and teasing apart these contributions. After validating the method with synthetic datasets obtained from computer simulations they use the lizards tracking dataset to explore these questions and demonstrate the utility of the method. They find that lizards show strong conspecific attraction, interacting more frequently and with more neighbors than expected by chance. Note, however, that these interactions are not necessarily friendly, as the two males in the picture remind us.
Photo © Dale Burzacott 2015
Orr Spiegel, Stephan T. Leu, Andrew Sih and C. Michael Bull
This month’s cover image shows a leaf of a grape vine (vitis vinifera) in the region of Las Alpujarras, Spain. The veins of the leaf form a complex tree which tapers out towards extremes. We can view this as an analogy for the process of inferring phylogenetic trees: the strong veins represent clear relationships, but as we approach the edges it is more difﬁcult to make accurate connections.
The associated article, ‘MO-Phylogenetics: A phylogenetic inference software tool with multi-objective evolutionary metaheuristics’, is about a software tool for phylogenetic inference. The tool searches for the best phylogenetic tree to explain the evolutionary relationships among different species. It is a NP-hard problem, so ﬁnding the optimal tree among all the possible solutions is computationally expensive. MO-Phylogenetics includes a number of non-exact multi-objective techniques known as metaheuristics, which produce satisfactory solutions in a reasonable amount of time.
Photo © Antonio J. Nebro
Cristian Zambrano-Vega, Antonio J. Nebro and José F. Aldana-Montes
This issue’s cover image depicts the ‘Eye of the Sahara’, Mauritania. It illustrates the geologically unique nature of desert environments and showcases openly-accessible satellite remote sensing (SRS) datasets for use in their monitoring. The image is a ‘false-colour composite’ image, containing data from both Landsat 8 (optical) and Sentinel 1a (C-band radar) satellites. The near- and shortwave-infrared Landsat 8 channels highlight vegetation (green) and desert (blue), while extreme topographical gradients are highlighted red from Sentinel 1a.
The Sahara contains unique but rapidly declining biodiversity and supports the livelihoods of 6% of world’s population. It is projected to be heavily impacted by climate change and is currently experiencing increasing anthropogenic pressures. SRS offers an opportunity to monitor ecosystems and biodiversity freely and repeatedly at a global scale. However, currently limited dialogue currently exists between the conservation and SRS communities, hindering the full potential for SRS in biodiversity monitoring. In this issue, the article “How do we want Satellite Remote Sensing to support biodiversity conservation globally?” identiﬁes and processes multiple SRS-derived biodiversity-relevant variables across the Sahara. It then examines the relative applicability of these existing freely-available SRS-derived to inform the aims of existing biodiversity monitoring frameworks.
Photo © Harry Owen
Nathalie Pettorelli, Harry Jon Foord Owen, Clare Duncan
Few birds are as characteristic of recently burned forests in western North America as the Black-backed Woodpecker (Picoides arcticus). Within months after ﬂames have died out, these woodpeckers colonize charred montane conifer forests feeding primarily on wood-boring beetles (e.g., Cerambycidae). The beetles are also new arrivals, beneﬁtting from the vast expanses of standing dead trees called snags. Post-ﬁ re forest management largely focuses on the removal versus retention of snags, which can cause conﬂict where forest management goals fail to align with species conservation. Not all snags are created equal, however, and patches with more woodpeckers could be retained over less populous ones. If only the secretive, smoky-colored woodpeckers were not so hard to ﬁnd.
In this month’s issue, Tingley et al. develop a new predictive abundance model aimed toward imperfectly detected, territorial vertebrates. The Bayesian implementation of the model combines information on where species are likely to occur with their expected density, utilizing both occupancy-based surveys and home-range scaling models. Using the case study of the Black-backed Woodpecker, Tingley et al.’s model accurately predicts spatial patterns of abundance in 4 recent ﬁ res, highlighting the use of the model for both conservation and management.
Photo © Tara Tanaka
Morgan W. Tingley, Robert L. Wilkerson, Christine A. Howell and Rodney B. Siegel
This month’s cover image shows a ﬂapper skate (Dipturus intermedia) caught by anglers of the Scottish Sea Anglers Conservation Network (SSACN) in the Sound of Jura off the west coast of Scotland. During the study for the related article a total of 17 individuals where tagged with data storage tags (DSTs) between 2011 and 2012 in order to better understand their behaviour and deﬁne conservation measures for this endangered marine apex predator. In total only four individuals were recaptured in 2012 – one mature female and three males – and their depth proﬁles showed high individual variability. All individuals were rod-caught thanks to the expertise of SSACN’s members who target ﬂapper skate in a catch and release ﬁshing programme.
The analysis of individual behaviour is quickly developing thanks to computational advances and the development of electronic tags that are able to collect high quantities of high frequency data. Such data are necessary to obtain useful information on the detailed behaviour of individuals. These data help us to understand the processes that relate animals to their environment. Therefore it is essential to develop methods which can deal with the issues that these data intrinsically carry – such as long memory, non-normality, non-stationarity and nonlinearity.
Photo © Ian Burrett/SSACN
Cecilia Pinto and Luigi Spezia
This month’s cover image shows a wild Canada lynx (Lynx canadensis), outﬁtted with a new GPS collar, in central Colorado. Following their extirpation in the 1970s, Colorado Parks and Wildlife reintroduced 218 wild-caught lynx, ﬁ t with Argos satellite/radio-telemetry collars, from 1999-2006. The pictured individual was trapped, collared, and immediately released in the spring of 2013 near Leadville, Colorado. He is the offspring of a lynx reintroduced to Colorado from Alaska in 2000 and was PIT-tagged as a kitten in 2005, making him approximately 8 years old in the photo.
Movement modeling is a rapidly growing ﬁeld due to recent technological developments that have increased the temporal resolution and accuracy of animal location data. However, many historical data sets, such as the data associated with the lynx reintroduction, were not collected explicitly to model animal movement but may contain a wealth of location information. These data sets may have been collected using multiple methods, be temporally sparse, or contain large measurement error. In this issue, Buderman et al. develop a functional model for location data that are not amenable to analysis with other contemporary movement models. They demonstrate the utility of this model by analyzing the locations from two Canada lynx following their reintroduction to Colorado.
Photo © Steve Sunday, Steve Sunday
Frances E. Buderman, Mevin B. Hooten, Jacob S. Ivan and Tanya M. Shenk
Sagebrush steppe in eastern Idaho, USA. In this community, population dynamics of the dominant perennial grasses and shrubs respond to both climate variation and competition. A mechanistic understanding of these dynamics requires high resolution spatial and temporal data, which are available for this site thanks to decades of mapped censuses in permanent quadrats. However, traditional model selection routines are not ideal for analyzing these data because of the large number of potential covariates.
In “Linking demography with drivers: climate and competition,” Teller, Adler, Edwards, Hooker & Ellner develop the use of spline methods that statistically link growth and survival data to high resolution competition and climate data. The authors demonstrate that spline methods can accurately reﬂect the spatial effects of neighbors and the temporal effects of climate covariates like precipitation and temperature. In a simulation, the authors show that spline methods for climate covariates are superior to comparable machine learning methods given enough data.
Photo © Brittany J. Teller
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Linking demography with drivers: climate and competition
Brittany J. Teller, Peter B. Adler, Collin B. Edwards, Giles Hooker and Stephen P. Ellner
Daphnia zooplankton are a plentiful meal for ﬁsh predators in freshwater systems. They are not helpless, however, as they have evolved a number of mechanisms for predator avoidance, including the ability to increase rates of development and produce defensive morphologies in the presence of predators. Furthermore, these traits are sometimes passed onto their offspring. This month’s cover image depicts an adult Daphnia in the foreground, with a looming predator nearby. This Daphnia carries a number of eggs, and the growth rates and morphologies of these offspring may be inﬂuenced by the mother’s detection of the ﬁsh predator.
In the article associated with this image, the authors sought to develop a method for understanding the degree to which genome-wide epigenetic changes across generations are associated with changes in environmental variables (such as chemicals associated with predators). The resulting method, epiRADseq, which is a restriction enzyme DNA fragment associated next generation sequencing technique, allows for the detection of continuously variable methylation states throughout the genome. While applicable to many diverse questions related to epigenetic regulation, the method was demonstrated on a clonal Daphnia system. First generation Daphnia were introduced to ﬁsh predator cues and the second generation was raised in the absence of predator cues. Using epiRADseq, the authors discovered signiﬁcant shifts in methylation state across several thousand genomic regions. Additionally, many of these loci were found to be in or nearby protein-coding genes. Due to a lack of genetic differences across clonal generations, differences in phenotype between ﬁrst and second generation Daphnia in response to predation are likely directed by epigenetic modiﬁcations like those identiﬁed using this new method.
Photo © Drew Schield, University of Texas at Arlington Original Images used to create the cover © Hajime Watanabe (Daphnia) and US Fish and Wildlife (Bluegill)
Drew R. Schield, Matthew R. Walsh, Daren C. Card, Audra L. Andrew, Richard H. Adams and Todd A. Castoe
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