Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology

In the past decade, ecologists have witnessed vast improvements in our ability to collect animal movement data through animal-borne technology, such as through GPS or ARGOS systems. However, more data does not necessarily yield greater knowledge in understanding animal ecology and conservation. In this paper, we provide a review of the major benefits, problems and potential misuses of GPS/Argos technology to animal ecology and conservation. Benefits are obvious, and include the ability to collect fine-scale spatio-temporal location data on many previously impossible to study animals, such as ocean-going fish, migratory songbirds and long-distance migratory mammals. These benefits come with significant problems, however, imposed by frequent collar failures and high cost, which often results in weaker study design, reduced sample sizes and poorer statistical inference. In addition, we see the divorcing of biologists from a field-based understanding of animal ecology to be a growing problem. Despite these difficulties, GPS devices have provided significant benefits, particularly in the conservation and ecology of wide-ranging species. We conclude by offering suggestions for ecologists on which kinds of ecological questions would currently benefit the most from GPS/Argos technology, and where the technology has been potentially misused. Significant conceptual challenges remain, however, including the links between movement and behaviour, and movement and population dynamics.     

State-space models of individual animal movement

Detailed observation of the movement of individual animals offers the potential to understand spatial population processes as the ultimate consequence of individual behaviour, physiological constraints and fine-scale environmental influences. However, movement data from individuals are intrinsically stochastic and often subject to severe observation error. Linking such complex data to dynamical models of movement is a major challenge for animal ecology. Here, we review a statistical approach, state-space modelling, which involves changing how we analyse movement data and draw inferences about the behaviours that shape it. The statistical robustness and predictive ability of state-space models make them the most promising avenue towards a new type of movement ecology that fuses insights from the study of animal behaviour, biogeography and spatial population dynamics.     

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.     

Human evolutionary psychology and animal behaviour

Homo sapiens is increasingly being studied within the evolutionary (adaptationist, selectionist) framework favoured by animal behaviour researchers. There are various labels for such work, including evolutionary psychology, human behavioural ecology and human sociobiology. Collectively, we call these areas 'human evolutionary psychology' (HEP) because their shared objective is an evolutionary understanding of human information processing and decision making. Sexual selection and sex differences have been especially prominent in recent HEP research, but many other topics have been addressed, including parent-offspring relations, reciprocity and exploitation, foraging strategies and spatial cognition. Many HEP researchers began their scientific careers in animal behaviour, and in many ways, HEP research is scarcely distinguishable from other animal behaviour research. Currently controversial issues in HEP, such as the explanation(s) for observed levels of heritable diversity, the kinds of data needed to test adaptationist hypotheses, and the characterization of a species-typical 'environment of evolutionary adaptedness', are issues in animal behaviour as well. What gives HEP a distinct methodological flavour is that the research animal can talk, an ability that has both advantages and pitfalls for researchers. The proper use of self-reports and other verbal data in HEP might usefully become a subject of future research in its own right. Copyright 1999 The Association for the Study of Animal Behaviour.     

How our view of animal phylogeny was reshaped by molecular approaches: lessons learned

In the late 1980s, researchers began applying molecular sequencing tools to questions of deep animal phylogeny. These advances in sequencing were accompanied with improvements in computation and phylogenetic methods, and served to significantly reshape our understanding of metazoan evolution. Prior to this time, researchers asserted phylogenetic hypotheses based on their experience with taxa and to some degree, their authority. Molecular phylogenetic tools provided discrete methods and objective characters for reconstructing phylogeny. Nonetheless, major changes to widely accepted views, such as animal phylogeny, take time to be accepted. Development and acceptance of our current understanding of animal evolution occurred in three main phases: initial hypotheses based on 18S data, confirmation with additional molecular markers, and continued refinement with phylogenomics. With the advent of ideas such as Lophotrochozoa and Ecdysozoa, flaws in the traditional view became apparent. We now understand that complex morphological and embryological features (e.g., segmentation, coelom formation, development of body cavities) are much more evolutionarily plastic than previously recognized. Here, I explore how the transition from the traditional to the modern phylogenetic understanding of animal phylogeny occurred and examine some implications of this change in understanding. As the field moves forward, the utility of morphological and embryological characters for reconstruction of deep animal phylogeny should be discouraged. Instead, these characters should be interpreted in the light of independent phylogeny.     

Fine scale prediction of ecological community composition using a two-step sequential Machine Learning ensemble

Prediction is one of the last frontiers in ecology. Indeed, predicting fine-scale species composition in natural systems is a complex challenge as multiple abiotic and biotic processes operate simultaneously to determine local species abundances. On the one hand, species intrinsic performance and their tolerance limits to different abiotic pressures modulate species abundances. On the other hand, there is growing recognition that species interactions play an equally important role in limiting or promoting such abundances within ecological communities. Here, we present a joint effort between ecologists and data scientists to use data-driven models to predict species abundances using reasonably easy to obtain data. We propose a sequential data-driven modeling approach that in a first step predicts the potential species abundances based on abiotic variables, and in a second step uses these predictions to model the realized abundances once accounting for species competition. Using a curated data set over five years we predict fine-scale species abundances in a highly diverse annual plant community. Our models show a remarkable spatial predictive accuracy using only easy-to-measure variables in the field, yet such predictive power is lost when temporal dynamics are taken into account. This result suggests that predicting future abundances requires longer time series analysis to capture enough variability. In addition, we show that these data-driven models can also suggest how to improve mechanistic models by adding missing variables that affect species performance such as particular soil conditions (e.g. carbonate availability in our case). Robust models for predicting fine-scale species composition informed by the mechanistic understanding of the underlying abiotic and biotic processes can be a pivotal tool for conservation, especially given the human-induced rapid environmental changes we are experiencing. This objective can be achieved by promoting the knowledge gained with classic modelling approaches in ecology and recently developed data-driven models.     

Farm animal genomics and informatics: an update

Farm animal genomics is of interest to a wide audience of researchers because of the utility derived from understanding how genomics and proteomics function in various organisms. Applications such as xenotransplantation, increased livestock productivity, bioengineering new materials, products and even fabrics are several reasons for thriving farm animal genome activity. Currently mined in rapidly growing data warehouses, completed genomes of chicken, fish and cows are available but are largely stored in decentralized data repositories. In this paper, we provide an informatics primer on farm animal bioinformatics and genome project resources which drive attention to the most recent advances in the field. We hope to provide individuals in biotechnology and in the farming industry with information on resources and updates concerning farm animal genome projects.     

Survey of Canadian animal-based researchers' views on the Three Rs: replacement, reduction and refinement

The 'Three Rs' tenet (replacement, reduction, refinement) is a widely accepted cornerstone of Canadian and international policies on animal-based science. The Canadian Council on Animal Care (CCAC) initiated this web-based survey to obtain greater understanding of 'principal investigators' and 'other researchers' (i.e. graduate students, post-doctoral researchers etc.) views on the Three Rs, and to identify obstacles and opportunities for continued implementation of the Three Rs in Canada. Responses from 414 participants indicate that researchers currently do not view the goal of replacement as achievable. Researchers prefer to use enough animals to ensure quality data is obtained rather than using the minimum and potentially waste those animals if a problem occurs during the study. Many feel that they already reduce animal numbers as much as possible and have concerns that further reduction may compromise research. Most participants were ambivalent about re-use, but expressed concern that the practice could compromise experimental outcomes. In considering refinement, many researchers feel there are situations where animals should not receive pain relieving drugs because it may compromise scientific outcomes, although there was strong support for the Three Rs strategy of conducting animal welfare-related pilot studies, which were viewed as useful for both animal welfare and experimental design. Participants were not opposed to being offered "assistance" to implement the Three Rs, so long as the input is provided in a collegial manner, and from individuals who are perceived as experts. It may be useful for animal use policymakers to consider what steps are needed to make replacement a more feasible goal. In addition, initiatives that offer researchers greater practical and logistical support with Three Rs implementation may be useful. Encouragement and financial support for Three Rs initiatives may result in valuable contributions to Three Rs knowledge and improve welfare for animals used in science.     

CYGNSS-derived soil moisture: Status,challenges and future

In the last few years, Global Navigation Satellite System-Reflectometry (GNSS-R) technology has provided an exciting solution to retrieve fine-scale spatiotemporal soil moisture predictions. The most promising data source for this task has been Cyclone Global Navigation Satellite System (CYGNSS) of the National Aeronautics and Space Administration (NASA). Several methodologies have been proposed in the literature to repurpose CYGNSS data for soil moisture estimation. In this work, we first describe the theoretical background of GNSS-R based soil moisture retrieval. We discuss the challenges associated with using GNSS-R (in particular CYGNSS) data, and present the current issues in the CYGNSS-based methodologies for estimating soil moisture. Some of the key limitations identified are in the areas of observation geometry, improper consideration of coherent and incoherent reflections, effect of vegetation on CYGNSS recording and consideration of ancillary data sources. We finally discuss potential Machine Learning based solutions for soil moisture estimation, which may provide researchers a path forward to achieve low error estimates.     

Metabolomics Has Great Potential for Clinical and Nutritional Care and Research with Exotic Animals

This essay explores the potential of metabolomics for exotic animal research in a zoological setting. Metabolomics is a suite of analytical tools aimed at gaining a holistic understanding of animal metabolism without prior knowledge of the compounds to be measured. These metabolic fingerprints can be used to define normal metabolism for an unstudied species, to characterize the metabolic deviation of diseased animals from the normal state over time, to identify biomarker compounds that best capture such deviations, and to measure the metabolic impact of clinical and nutritional interventions. Two approaches, nuclear magnetic resonance (NMR) and mass spectrometry (MS) provide large amounts of complimentary pure and applied biological data. Metabolomic methods hold great potential for researchers, clinicians, and nutritionists studying exotic and aquatic animals because they can produce a huge data return on research effort, and because they do not require much a priori knowledge of the animals’ metabolism, which is so often then case in zoological settings. Zoo Biol. 32:246–250, 2013. © 2012 Wiley Periodicals, Inc.     

Breed Locally,Disperse Globally: Fine-Scale Genetic Structure Despite Landscape-Scale Panmixia in a Fire-Specialist

An exciting advance in the understanding of metapopulation dynamics has been the investigation of how populations respond to ephemeral patches that go ‘extinct’ during the lifetime of an individual. Previous research has shown that this scenario leads to genetic homogenization across large spatial scales. However, little is known about fine-scale genetic structuring or how this changes over time in ephemeral patches. We predicted that species that specialize on ephemeral habitats will delay dispersal to exploit natal habitat patches while resources are plentiful and thus display fine-scale structure. To investigate this idea, we evaluated the effect of frequent colonization of ephemeral habitats on the fine-scale genetic structure of a fire specialist, the black-backed woodpecker (Picoides arcticus) and found a pattern of fine-scale genetic structure. We then tested for differences in spatial structure between sexes and detected a pattern consistent with male-biased dispersal. We also detected a temporal increase in relatedness among individuals within newly burned forest patches. Our results indicate that specialist species that outlive their ephemeral patches can accrue significant fine-scale spatial structure that does not necessarily affect spatial structure at larger scales. This highlights the importance of both spatial and temporal scale considerations in both sampling and data interpretation of molecular genetic results.     

The sensory ecology of adaptive landscapes

In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions about adaptive behaviour and what is behaviourally achievable given the umwelt of the animal being studied. This may lead to erroneous conclusions about maladaptive behaviour in circumstances when the behaviour exhibited is the most adaptive possible given sensory limitations. With advances in the computational resources available to behavioural ecologists, we can now measure vast numbers of interactions among behaviours and environments to create adaptive behavioural surfaces. These surfaces have massive heuristic, predictive and analytical potential in understanding adaptive animal behaviour, but researchers using them are destined to fail if they ignore the sensory ecology of the species they study. Here, we advocate the continued use of these approaches while directly linking them to perceptual space to ensure that the topology of the generated adaptive landscape matches the perceptual reality of the animal it intends to study. Doing so will allow predictive models of animal behaviour to reflect the reality faced by the agents on adaptive surfaces, vastly improving our ability to determine what constitutes an adaptive response for the animal in question.     

Isolation,Cryopreservation and Culture of Human Amnion Epithelial Cells for Clinical Applications

Human amnion epithelial cells (hAECs) derived from term or pre-term amnion membranes have attracted attention from researchers and clinicians as a potential source of cells for regenerative medicine. The reason for this interest is evidence that these cells have highly multipotent differentiation ability, low immunogenicity, and anti-inflammatory functions. These properties have prompted researchers to investigate the potential of hAECs to be used to treat a variety of diseases and disorders in pre-clinical animal studies with much success.hAECs have found widespread application for the treatment of a range of diseases and disorders. Potential clinical applications of hAECs include the treatment of stroke, multiple sclerosis, liver disease, diabetes and chronic and acute lung diseases. Progressing from pre-clinical animal studies into clinical trials requires a higher standard of quality control and safety for cell therapy products. For safety and quality control considerations, it is preferred that cell isolation protocols use animal product-free reagents. We have developed protocols to allow researchers to isolate, cryopreserve and culture hAECs using animal product-free reagents. The advantage of this method is that these cells can be isolated, characterized, cryopreserved and cultured without the risk of delivering potentially harmful animal pathogens to humans, while maintaining suitable cell yields, viabilities and growth potential. For researchers moving from pre-clinical animal studies to clinical trials, these methodologies will greatly accelerate regulatory approval, decrease risks and improve the quality of their therapeutic cell population.     

Fine-scale spatial genetic structure and dispersal among spotted salamander (Ambystoma maculatum) breeding populations

We examined fine-scale genetic variation among breeding aggregations of the spotted salamander (Ambystoma maculatum) to quantify dispersal, interpopulation connectivity and population genetic structure. Spotted salamanders rely on temporary ponds or wetlands for aggregate breeding. Adequate breeding sites are relatively isolated from one another and field studies suggest considerable adult site fidelity; therefore, we expected to find population structure and differentiation at small spatial scales. We used microsatellites to estimate population structure and dispersal among 29 breeding aggregations in Tompkins County, New York, USA, an area encompassing 1272 km(2). Bayesian and frequency-based analyses revealed fine-scale genetic structure with two genetically defined demes: the North deme included seven breeding ponds, and the South deme included 13 ponds. Nine ponds showed evidence of admixture between these two genetic pools. Bayesian assignment tests for detection of interpopulation dispersal indicate that immigration among ponds is common within demes, and that certain populations serve as sources of immigrants to neighbouring ponds. Likewise, spatial genetic correlation analyses showed that populations < or = 4.8 km distant from each other show significant genetic correlation that is not evident at higher scales. Within-population levels of relatedness are consistently larger than expected if mating were completely random across ponds, and in the case of a few ponds, within-population processes such as inbreeding or reproductive skew contribute significantly to differentiation from neighbouring ponds. Our data underscore the importance of these within-population processes as a source of genetic diversity across the landscape, despite considerable population connectivity. Our data further suggest that spotted salamander breeding groups behave as metapopulations, with population clusters as functional units, but sufficient migration among demes to allow for potential rescue and recolonization. Amphibian habitats are becoming increasingly fragmented and a clear understanding of dispersal and patterns of population connectivity for taxa with different ecologies and life histories is crucial for their conservation.     

Activity Patterns of Free-Ranging Koalas (Phascolarctos cinereus) Revealed by Accelerometry

An understanding of koala activity patterns is important for measuring the behavioral response of this species to environmental change, but to date has been limited by the logistical challenges of traditional field methodologies. We addressed this knowledge gap by using tri-axial accelerometer data loggers attached to VHF radio collars to examine activity patterns of adult male and female koalas in a high-density population at Cape Otway, Victoria, Australia. Data were obtained from 27 adult koalas over two 7-d periods during the breeding season: 12 in the early-breeding season in November 2010, and 15 in the late-breeding season in January 2011. Multiple 15 minute observation blocks on each animal were used for validation of activity patterns determined from the accelerometer data loggers. Accelerometry was effective in distinguishing between inactive (sleeping, resting) and active (grooming, feeding and moving) behaviors. Koalas were more active during the early-breeding season with a higher index of movement (overall dynamic body acceleration [ODBA]) for both males and females. Koalas showed a distinct temporal pattern of behavior, with most activity occurring from mid-afternoon to early morning. Accelerometry has potential for examining fine-scale behavior of a wide range of arboreal and terrestrial species.     

Predictive Modelling to Identify Near-Shore,Fine-Scale Seabird Distributions during the Breeding Season

During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney’s coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney’s seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making.     

Reactive oxygen species in cardiovascular disease

Based on the “free radical theory” of disease, researchers have been trying to elucidate the role of oxidative stress from free radicals in cardiovascular disease. Considerable data indicate that reactive oxygen species and oxidative stress are important features of cardiovascular diseases including atherosclerosis, hypertension, and congestive heart failure. However, blanket strategies with antioxidants to ameliorate cardiovascular disease have not generally yielded favorable results. However, our understanding of reactive oxygen species has evolved to the point at which we now realize these species have important roles in physiology as well as pathophysiology. Thus, it is overly simplistic to assume a general antioxidant strategy will yield specific effects on cardiovascular disease. Indeed, there are several sources of reactive oxygen species that are known to be active in the cardiovascular system. This review addresses our understanding of reactive oxygen species sources in cardiovascular disease and both animal and human data defining how reactive oxygen species contribute to physiology and pathology.     

Individual variation in dispersal associated with phenotype influences fine-scale genetic structure in weasels

In general, landscape genetic studies have ignored the potential role that the phenotype of individuals plays in determining fine-scale genetic structure in species. This potential over-simplification ignores an important component that dispersal is both condition- and phenotype-dependent. In order to investigate the relationship between potential dispersal, habitat selection and phenotype, we examined the spatial ecology, body mass and fine-scale genetic structure of weasels (Mustela nivalis) in Bia?owie?a Forest in Poland. Our study population is characterized by an almost three-fold phenotypic variation in adult body mass and weasels were segregated in certain habitats according to size. We detected significant genetic structuring associated with habitat within the studied area and analyses of radio-tracking and re-capture data showed that the maximum extent of movement was achieved by weasels of medium body size, whereas the smallest and largest individuals exhibited higher site fidelity. With the unrestricted movement of the medium-sized individuals across optimal habitat, genetic admixture does occur. However, the presence of a barrier leads to unidirectional gene flow, with larger individuals outcompeting smaller individuals and therefore maintaining the genetic break in the study area. This highlights the importance of considering both intrinsic (phenotype) and extrinsic (environmental) factors in understanding dispersal patterns and ultimately, gene flow in complex landscapes.     

Uniting pattern and process in plant�Canimal mutualistic networks: a review

Background

Ecologists and evolutionary biologists are becoming increasingly interested in networks as a framework to study plant–animal mutualisms within their ecological context. Although such focus on networks has brought about important insights into the structure of these interactions, relatively little is still known about the mechanisms behind these patterns.

Scope

The aim in this paper is to offer an overview of the mechanisms influencing the structure of plant–animal mutualistic networks. A brief summary is presented of the salient network patterns, the potential mechanisms are discussed and the studies that have evaluated them are reviewed. This review shows that researchers of plant–animal mutualisms have made substantial progress in the understanding of the processes behind the patterns observed in mutualistic networks. At the same time, we are still far from a thorough, integrative mechanistic understanding. We close with specific suggestions for directions of future research, which include developing methods to evaluate the relative importance of mechanisms influencing network patterns and focusing research efforts on selected representative study systems throughout the world.Key words: Ant–plant interactions, forbidden links, mutualism, neutrality, trait matching, plant–animal interactions, pollination, seed dispersal