Macdonald D, Al-Hajiri A, Al-Jabiry H, Yamaguchi N. Characteristics and Demography of a Free-Ranging Ethiopian Hedgehog, Paraechinus aethiopicus, Population in Qatar

Simple Summary

Information on population characteristics of Paraechinusis is valuable for ensuring long term survival of populations, however, studies are currently lacking. Here we investigate the population dynamics of Ethiopian hedgehogs based on a capture study in Qatar by fitting several statistical models. Over the 19 months of the study, we estimate a mean population of 60 hedgehogs, giving a density of 7 hedgehogs per km² in our 8.5 km² search area. The monthly abundance of hedgehogs decreased over the study and although survival was constant over the study period, with a mean monthly rate of 75%, there was a decline in the number of new entrants over time. We also studied these parameters over one year, excluding winter, and found that monthly estimates of juvenile and subadult survival decreased over time. We surmise that survival of juveniles may be a factor in the decrease in abundance and there may be implications for the persistence of this population in the future, with human influenced resources playing an important role. We caught between 91.3% and 100% of the estimated population at this site, indicating that our capture methodology was efficient. We conclude that the methodology used here is transferrable to other hedgehog species.

Abstract

Information on population characteristics of Paraechinusis is valuable for ensuring long term survival of populations, however, studies are currently lacking. Here we investigate the population dynamics of Ethiopian hedgehogs based on a capture-mark-recapture study in Qatar by fitting Jolly-Seber and Cormack-Jolly-Seber models. Over the 19 months of the study, we estimate a mean population of 60 hedgehogs, giving a density of 7 hedgehogs per km² in our 8.5 km² search area. The monthly abundance of hedgehogs decreased over the study and although survival was constant over the study period, with a mean monthly rate of 75%, there was a decline in the number of new entrants over time. We also studied these parameters over one year, excluding winter, and found that monthly estimates of juvenile and subadult survival decreased over time. We surmise that survival of juveniles may be a factor in the decrease in abundance and there may be implications for the persistence of this population, with anthropogenic influenced resources playing an important role. We caught between 91.3% and 100% of the estimated population at this site, indicating that our capture methodology was efficient. We conclude that the methodology used here is transferrable to other hedgehog species.

Insights from the study of complex systems for the ecology and evolution of animal populations

Populations of animals comprise many individuals, interacting in multiple contexts, and displaying heterogeneous behaviors. The interactions among individuals can often create population dynamics that are fundamentally deterministic yet display unpredictable dynamics. Animal populations can, therefore, be thought of as complex systems. Complex systems display properties such as nonlinearity and uncertainty and show emergent properties that cannot be explained by a simple sum of the interacting components. Any system where entities compete, cooperate, or interfere with one another may possess such qualities, making animal populations similar on many levels to complex systems. Some fields are already embracing elements of complexity to help understand the dynamics of animal populations, but a wider application of complexity science in ecology and evolution has not occurred. We review here how approaches from complexity science could be applied to the study of the interactions and behavior of individuals within animal populations and highlight how this way of thinking can enhance our understanding of population dynamics in animals. We focus on 8 key characteristics of complex systems: hierarchy, heterogeneity, self-organization, openness, adaptation, memory, nonlinearity, and uncertainty. For each topic we discuss how concepts from complexity theory are applicable in animal populations and emphasize the unique insights they provide. We finish by outlining outstanding questions or predictions to be evaluated using behavioral and ecological data. Our goal throughout this article is to familiarize animal ecologists with the basics of each of these concepts and highlight the new perspectives that they could bring to variety of subfields.

Primed to be strong, primed to be fast: modeling benefits of microbial stress responses

Organisms are prone to different stressors and have evolved various defense mechanisms. One such defense mechanism is priming, where a mild preceding stress prepares the organism toward an improved stress response. This improved response can strongly vary, and primed organisms have been found to respond with one of three response strategies: a shorter delay to stress, a faster buildup of their response or a more intense response. However, a universal comparative assessment, which response is superior under a given environmental setting, is missing. We investigate the benefits of the three improved responses for microorganisms with an ordinary differential equation model, simulating the impact of an external stress on a microbial population that is either naïve or primed. We systematically assess the resulting population performance for different costs associated with priming and stress conditions. Our results show that independent of stress type and priming costs, the stronger primed response is most beneficial for longer stress phases, while the faster and earlier responses increase population performance and survival probability under short stresses. Competition increases priming benefits and promotes the early stress response. This dependence on the ecological context highlights the importance of including primed response strategies into microbial stress ecology.

Population Dynamics of Hyalomma dromedarii on Camels in the United Arab Emirates

Hyalomma dromedarii is the most important tick species infesting camels in the Middle East. So far, there are no studies on the population dynamics of H. dromedarii ticks on camels in the United Arab Emirates (UAE). Thus, the current study was performed: (1) to assess H. dromedarii population dynamics under common camel breeding and management practices in the study area, (2) to evaluate H. dromedarii life stage changes and sex ratio over time, and (3) to measure parasitological indicators of H. dromedarii infestation. We conducted monthly on-site tick visual counts and collection from camels in Al Ain, UAE, over 12 months. Our results show that the infestation prevalence was very high during the whole study period, with a mean of 94.33%. The maximum infestation intensity occurred in June, while the minimum occurred in January. Overall, H. dromedarii ticks were found on camels during the entire year in spite of monthly applications of an acaricide. This study reveals that H. dromedarii has a very high prevalence and continuous presence on camels in the UAE regardless of the weather fluctuations and acaricide applications and showed the need for an effective control strategy.

Mortality of a large wide-ranging mammal largely caused by anthropogenic activities

With efforts to restore large mammal populations following extirpations, it is vital to quantify how they are impacted by human activities and gain insights into population dynamics in relation to conservation goals. Our objective was to characterize cause-specific mortality of black bears (Ursus americanus) throughout their range. We first quantified cause-specific mortality for 247 black bears in one harvested and two non-harvested populations. We then simulated a small recolonizing population with and without anthropogenic mortality. Lastly, we conducted a meta-analysis of all published black bear mortality studies throughout North America (31 studies of 2630 bears). We found anthropogenic mortality was greater than natural mortality, non-harvest anthropogenic mortality (e.g. poaching, defense of property, etc.) was greater in non-harvested populations, and harvesting was one of the major causes of mortality for bears throughout their range. Our simulation indicated that removing anthropogenic mortality increased population size by an average of 23% in 15 years. We demonstrated that bears are exposed to high levels of anthropogenic mortality, and the potential for human activities to slow population growth in expanding populations. Management and conservation of wide-ranging mammals will depend on holistic strategies that integrate ecological factors with socio-economic issues to achieve successful conservation and coexistence.

Density-dependence tips the change of plant-plant interactions under environmental stress

Facilitation studies typically compare plants under differential stress levels with and without neighbors, while the density of neighbors has rarely been addressed. However, recent empirical studies indicate that facilitation may be density-dependent too and peak at intermediate neighbor densities. Here, we propose a conceptual model to incorporate density-dependence into theory about changes of plant-plant interactions under stress. To test our predictions, we combine an individual-based model incorporating both facilitative response and effect, with an experiment using salt stress and Arabidopsis thaliana. Theoretical and experimental results are strikingly consistent: (1) the intensity of facilitation peaks at intermediate density, and this peak shifts to higher densities with increasing stress; (2) this shift further modifies the balance between facilitation and competition such that the stress-gradient hypothesis applies only at high densities. Our model suggests that density-dependence must be considered for predicting plant-plant interactions under environmental change.

Potential sex-dependent effects of weather on apparent survival of a high-elevation specialist

Mountain ecosystems are inhabited by highly specialised and endemic species which are particularly susceptible to climatic changes. However, the mechanisms by which climate change affects species population dynamics are still largely unknown, particularly for mountain birds. We investigated how weather variables correlate with survival or movement of the white-winged snowfinch Montifringilla nivalis, a specialist of high-elevation habitat. We analysed a 15-year (2003-2017) mark-recapture data set of 671 individuals from the Apennines (Italy), using mark-recapture models. Mark-recapture data allow estimating, forgiven time intervals, the probability that individuals stay in the study area and survive, the so called apparent survival. We estimated annual apparent survival to be around 0.44-0.54 for males and around 0.51-0.64 for females. Variance among years was high (range: 0.2-0.8), particularly for females. Apparent survival was lower in winter compared to summer. Female annual apparent survival was negatively correlated with warm and dry summers, whereas in males these weather variables only weakly correlated with apparent survival. Remarkably, the average apparent survival measured in this study was lower than expected. We suggest that the low apparent survival may be due to recent changes in the environment caused by global warming. Possible, non-exclusive mechanisms that potentially also could explain sexual differential apparent survival act via differential breeding dispersal, hyperthermia, weather-dependent food availability, and weather-dependent trade-off between reproduction and self-maintenance. These results improve our current understanding of the mechanisms driving population dynamics in high-elevation specialist birds, which are particularly at risk due to climate change.

Ketamine anaesthesia induces gain enhancement via recurrent excitation in granular input layers of the auditory cortex

KEY POINTS

Ketamine is a common anaesthetic agent used in research and more recently as medication in treatment of depression. It has known effects on inhibition of interneurons and cortical stimulus-locked responses, but the underlying functional network mechanisms are still elusive. Analysing population activity across all layers within the auditory cortex, we found that doses of this anaesthetic induce a stronger activation and stimulus-locked response to pure-tone stimuli. This cortical response is driven by gain enhancement of thalamocortical input processing selectively within granular layers due to an increased recurrent excitation. Time-frequency analysis indicates a higher broadband magnitude response and prolonged phase coherence in granular layers, possibly pointing to disinhibition of this recurrent excitation. These results further the understanding of ketamine's functional mechanisms, which will improve the ability to interpret physiological studies moving from anaesthetized to awake paradigms and may lead to the development of better ketamine-based depression treatments with lower side effects.

ABSTRACT

Ketamine is commonly used as an anaesthetic agent and has more recently gained attention as an antidepressant. It has been linked to increased stimulus-locked excitability, inhibition of interneurons and modulation of intrinsic neuronal oscillations. However, the functional network mechanisms are still elusive. A better understanding of these anaesthetic network effects may improve upon previous interpretations of seminal studies conducted under anaesthesia and have widespread relevance for neuroscience with awake and anaesthetized subjects as well as in medicine. Here, we investigated the effects of anaesthetic doses of ketamine (15 mg kg^-1  h^-1 i.p.) on the network activity after pure-tone stimulation within the auditory cortex of male Mongolian gerbils (Meriones unguiculatus). We used laminar current source density (CSD) analysis and subsequent layer-specific continuous wavelet analysis to investigate spatiotemporal response dynamics on cortical columnar processing in awake and ketamine-anaesthetized animals. We found thalamocortical input processing within granular layers III/IV to be significantly increased under ketamine. This layer-dependent gain enhancement under ketamine was not due to changes in cross-trial phase coherence but was rather attributed to a broadband increase in magnitude reflecting an increase in recurrent excitation. A time-frequency analysis was indicative of a prolonged period of stimulus-induced excitation possibly due to a reduced coupling of excitation and inhibition in granular input circuits - in line with the common hypothesis of cortical disinhibition via suppression of GABAergic interneurons.

Stochastic phenomena in pattern formation for distributed nonlinear systems

We study a stochastic spatially extended population model with diffusion, where we find the coexistence of multiple non-homogeneous spatial structures in the areas of Turing instability. Transient processes of pattern generation are studied in detail. We also investigate the influence of random perturbations on the pattern formation. Scenarios of noise-induced pattern generation and stochastic transformations are studied using numerical simulations and modality analysis. This article is part of the theme issue 'Patterns in soft and biological matters'.

Museomics identifies genetic erosion in two butterfly species across the 20th century in Finland

Erosion of biodiversity generated by anthropogenic activities has been studied for decades and in many areas at the species level, using taxa monitoring. In contrast, genetic erosion within species has rarely been tracked, and is often studied by inferring past population dynamics from contemporaneous estimators. An alternative to such inferences is the direct examination of past genes, by analysing museum collection specimens. While providing direct access to genetic variation over time, historical DNA is usually not optimally preserved, and it is necessary to apply genotyping methods based on hybridization-capture to unravel past genetic variation. In this study, we apply such a method (i.e., HyRAD), to large time series of two butterfly species in Finland, and present a new bioinformatic pipeline, namely PopHyRAD, that standardizes and optimizes the analysis of HyRAD data at the within-species level. In the localities for which the data retrieved have sufficient power to accurately examine genetic dynamics through time, we show that genetic erosion has increased across the last 100 years, as revealed by signatures of allele extinctions and heterozygosity decreases, despite local variations. In one of the two butterflies (Erebia embla), isolation by distance also increased through time, revealing the effect of greater habitat fragmentation over time.

The interplay of phenotypic variability and fitness in finite microbial populations

In isogenic microbial populations, phenotypic variability is generated by a combination of stochastic mechanisms, such as gene expression, and deterministic factors, such as asymmetric segregation of cell volume. Here we address the question: how does phenotypic variability of a microbial population affect its fitness? While this question has previously been studied for exponentially growing populations, the situation when the population size is kept fixed has received much less attention, despite its relevance to many natural scenarios. We show that the outcome of competition between multiple microbial species can be determined from the distribution of phenotypes in the culture using a generalization of the well-known Euler-Lotka equation, which relates the steady-state distribution of phenotypes to the population growth rate. We derive a generalization of the Euler-Lotka equation for finite cultures, which relates the distribution of phenotypes among cells in the culture to the exponential growth rate. Our analysis reveals that in order to predict fitness from phenotypes, it is important to understand how distributions of phenotypes obtained from different subsets of the genealogical history of a population are related. To this end, we derive a mapping between the various ways of sampling phenotypes in a finite population and show how to obtain the equivalent distributions from an exponentially growing culture. Finally, we use this mapping to show that species with higher growth rates in exponential growth conditions will have a competitive advantage in the finite culture.

Predicting collapse of complex ecological systems: quantifying the stability-complexity continuum

Dynamical shifts between the extremes of stability and collapse are hallmarks of ecological systems. These shifts are limited by and change with biodiversity, complexity, and the topology and hierarchy of interactions. Most ecological research has focused on identifying conditions for a system to shift from stability to any degree of instability-species abundances do not return to exact same values after perturbation. Real ecosystems likely have a continuum of shifting between stability and collapse that depends on the specifics of how the interactions are structured, as well as the type and degree of disturbance due to environmental change. Here we map boundaries for the extremes of strict stability and collapse. In between these boundaries, we find an intermediate regime that consists of single-species extinctions, which we call the extinction continuum. We also develop a metric that locates the position of the system within the extinction continuum-thus quantifying proximity to stability or collapse-in terms of ecologically measurable quantities such as growth rates and interaction strengths. Furthermore, we provide analytical and numerical techniques for estimating our new metric. We show that our metric does an excellent job of capturing the system's behaviour in comparison with other existing methods-such as May's stability criteria or critical slowdown. Our metric should thus enable deeper insights about how to classify real systems in terms of their overall dynamics and their limits of stability and collapse.

Thermodynamic modelling of synthetic communities predicts minimum free energy requirements for sulfate reduction and methanogenesis

Microbial communities are complex dynamical systems harbouring many species interacting together to implement higher-level functions. Among these higher-level functions, conversion of organic matter into simpler building blocks by microbial communities underpins biogeochemical cycles and animal and plant nutrition, and is exploited in biotechnology. A prerequisite to predicting the dynamics and stability of community-mediated metabolic conversions is the development and calibration of appropriate mathematical models. Here, we present a generic, extendable thermodynamic model for community dynamics and calibrate a key parameter of this thermodynamic model, the minimum energy requirement associated with growth-supporting metabolic pathways, using experimental population dynamics data from synthetic communities composed of a sulfate reducer and two methanogens. Our findings show that accounting for thermodynamics is necessary in capturing the experimental population dynamics of these synthetic communities that feature relevant species using low energy growth pathways. Furthermore, they provide the first estimates for minimum energy requirements of methanogenesis (in the range of −30 kJ mol⁻¹) and elaborate on previous estimates of lactate fermentation by sulfate reducers (in the range of −30 to −17 kJ mol⁻¹ depending on the culture conditions). The open-source nature of the developed model and demonstration of its use for estimating a key thermodynamic parameter should facilitate further thermodynamic modelling of microbial communities.

A unifying framework for the transient parasite dynamics of migratory hosts

Migrations allow animals to track seasonal changes in resources, find mates, and avoid harsh climates, but these regular, long-distance movements also have implications for parasite dynamics and animal health. Migratory animals have been dubbed "superspreaders" of infection, but migration can also reduce parasite burdens within host populations via migratory escape from contaminated habitats and transmission hotspots, migratory recovery due to parasite mortality, and migratory culling of infected individuals. Here, we show that a single migratory host-macroparasite model can give rise to these different phenomena under different parametrizations, providing a unifying framework for a mechanistic understanding of the parasite dynamics of migratory animals. Importantly, our model includes the impact of parasite burden on host movement capability during migration, which can lead to "parasite-induced migratory stalling" due to a positive feedback between increasing parasite burdens and reduced movement. Our results provide general insight into the conditions leading to different health outcomes in migratory wildlife. Our approach lays the foundation for tactical models that can help understand, predict, and mitigate future changes of disease risk in migratory wildlife that may arise from shifting migratory patterns, loss of migratory behavior, or climate effects on parasite development, mortality, and transmission.

Airborne Optical Sectioning for Nesting Observation

We describe how a new and low-cost aerial scanning technique, airborne optical sectioning (AOS), can support ornithologists in nesting observation. After capturing thermal and color images during a seven minutes drone flight over a 40 × 12 m patch of the nesting site of Austria's largest heron population, a total of 65 herons and 27 nests could be identified, classified, and localized in a sparse 3D reconstruction of the forest. AOS is a synthetic aperture imaging technique that removes occlusion caused by leaves and branches. It registers recorded images to a common 3D coordinate system to support the reconstruction and analysis of the entire forest volume, which is impossible with conventional 2D or 3D imaging techniques. The recorded data is published with open access.

Coexisting attractors in the context of cross-scale population dynamics: measles in London as a case study

Patterns of measles infection in large urban populations have long been considered the paradigm of synchronized nonlinear dynamics. Indeed, recurrent epidemics appear approximately mass-action despite underlying heterogeneity. However, using a subset of rich, newly digitized mortality data (1897–1906), we challenge that proposition. We find that sub-regions of London exhibited a mixture of simultaneous annual and biennial dynamics, while the aggregate city-level dynamics appears firmly annual. Using a simple stochastic epidemic model and maximum-likelihood inference methods, we show that we can capture this observed variation in periodicity. We identify agreement between theory and data, indicating that both changes in periodicity and epidemic coupling between regions can follow relatively simple rules; in particular we find local variation in seasonality drives periodicity. Our analysis underlines that multiple attractors can coexist in a strongly mixed population and follow theoretical predictions.

Migration health crisis associated with climate change: A systematic review

BACKGROUND

The empirical assessment of the health outcomes associated with migration caused by climate change is still unclear. However, health outcomes in the early stages are expected to be similar to the health outcomes associated with refugees. The objective of the present study was a systematic review of the health effects of migration caused by climate change.

METHODOLOGY

A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Online databases (PubMed, Scopus, Web of Science, and Google Scholar) were used to identify papers published that evaluated the health effects of migration caused by climate change. The search, article selection, and data extraction were carried out by two researchers independently. All English-language articles on the health effects of migration caused by climate change were included in this study.

RESULTS

An analysis of the complex ways in which climate change influences populations can be facilitated using a three-class classification: compulsory displacement, resettlement planning, and migration. Subsequent to climate changes, other changes, and environmental deficiencies, compulsory displacement may occur in case of inadequacy of compatibility responses. A part of migration-related health outcomes caused by climate change is from displacement from rural to urban areas, especially in developing countries. There is significant documentation on health and livelihood inequalities between migrant groups and host populations in developed countries.

CONCLUSION

If climate change continues in its current direction, it is likely that the number of refugees and crises will increase in the coming decades. Although the domain and the extent of health hazards caused by the displacement of the population associated with climate change cannot be clearly predicted, by reducing global greenhouse gas emissions, along with social and environmental adaptation strategies, migration caused by climate change, health risks and its relevant crises can be greatly reduced.

Mazes to Study the Effects of Spatial Complexity, Predation and Population Density on Mate Finding

The difficulty to locate mates and overcome predation can hamper species establishment and population maintenance. The effects of sparseness between individuals or the effect of predators on the probability of population growth can be difficult to measure experimentally. For testing hypotheses about population density and predation, we contend that habitat complexity can be simulated using insect mazes of varying mathematical difficulty. To demonstrate the concept, we investigated whether the use of 3D printed mazes of varying complexity could be used to increase spatial separation between sexes of Drosophila simulans, and whether the presence of a generalist predator hampered mate-finding. We then examined how increasing D. simulans population density might overcome the artificially created effects of increasing the distance between mates and having a predator present. As expected, there was an increase in time taken to find a mate and a lower incidence of mating as habitat complexity increased. Increasing the density of flies reduced the searching time and increased mating success, and overcame the effect of the predator in the maze. Printable 3D mazes offer the opportunity to quickly assess the effects of spatial separation on insect population growth in the laboratory, without the need for large enclosed spaces. Mazes could be scaled up for larger insects and can be used for other applications such as learning.

Spatially Explicit Changes in Potato Psyllid (Hemiptera: Triozidae) Populations in Three South Texas Potato Fields

Insect abundance is commonly recorded in the form of discrete counts taken from plants. Analyses of these counts provide information about spatial distributions and population structure. A study was conducted in the Lower Rio Grande Valley of Texas during April and May 2014 to determine how populations of potato psyllids [Bactericera cockerelli (Šulc)] within three potato fields change over time. It was found that potato psyllid populations in these potato fields frequently changed both spatially and temporally. Chi-square goodness of fit tests and Akaike's Information Criterion indicated that the frequency distributions of potato psyllid counts conformed to a negative binomial distribution, implying an aggregated spatial pattern. Variance-mean ratios were always much larger than one, also implying spatially clumped populations. However, with a few exceptions, a Spatial Analysis by Distance IndicEs analysis showed that potato psyllid counts were mostly random in space, the clumping generally occurring on individual potato plants and rarely involving groups of potato plants in close proximity. Trends in proportions of plants infested by at least one potato psyllid and the clumping parameter k were similar for all three potato fields. Potato psyllid spatial population structure is a dynamic process that involves continuous adult movements leading to substantial redistribution of potato psyllids over limited time spans of 2 to 3 d. By capturing elements of their spatial and temporal patterns of redistribution, the study reported here is a step towards a better understanding of the population dynamics and movement of potato psyllids.

Spatial variation in exploited metapopulations obscures risk of collapse

Unanticipated declines among exploited species have commonly occurred despite harvests that appeared sustainable prior to collapse. This is particularly true in the oceans where spatial scales of management are often mismatched with spatially complex metapopulations. We explore causes, consequences, and potential solutions for spatial mismatches in harvested metapopulations in three ways. First, we generate novel theory illustrating when and how harvesting metapopulations increases spatial variability and in turn masks local-scale volatility. Second, we illustrate why spatial variability in harvested metapopulations leads to negative consequences using an empirical example of a Pacific herring metapopulation. Finally, we construct a numerical management strategy evaluation model to identify and highlight potential solutions for mismatches in spatial scale and spatial variability. Our results highlight that spatial complexity can promote stability at large scales, however, ignoring spatial complexity produces cryptic and negative consequences for people and animals that interact with resources at small scales. Harvesting metapopulations magnifies spatial variability, which creates discrepancies between regional and local trends while increasing risk of local population collapses. Such effects asymmetrically impact locally constrained fishers and predators, which are more exposed to risks of localized collapses. Importantly, we show that dynamically optimizing harvest can minimize local risk without sacrificing yield. Thus, multiple nested scales of management may be necessary to avoid cryptic collapses in metapopulations and the ensuing ecological, social, and economic consequences.

Introduction to the Special Issue: The role of seed dispersal in plant populations: perspectives and advances in a changing world

Despite the importance of seed dispersal as a driving process behind plant community assembly, our understanding of the role of seed dispersal in plant population persistence and spread remains incomplete. As a result, our ability to predict the effects of global change on plant populations is hampered. We need to better understand the fundamental link between seed dispersal and population dynamics in order to make predictive generalizations across species and systems, to better understand plant community structure and function, and to make appropriate conservation and management responses related to seed dispersal. To tackle these important knowledge gaps, we established the CoDisperse Network and convened an interdisciplinary, NSF-sponsored Seed Dispersal Workshop in 2016, during which we explored the role of seed dispersal in plant population dynamics (NSF DEB Award # 1548194). In this Special Issue, we consider the current state of seed dispersal ecology and identify the following collaborative research needs: (i) the development of a mechanistic understanding of the movement process influencing dispersal of seeds; (ii) improved quantification of the relative influence of seed dispersal on plant fitness compared to processes occurring at other life history stages; (iii) an ability to scale from individual plants to ecosystems to quantify the influence of dispersal on ecosystem function; and (iv) the incorporation of seed dispersal ecology into conservation and management strategies.

Three critical factors affecting automated image species recognition performance for camera traps

Ecological camera traps are increasingly used by wildlife biologists to unobtrusively monitor an ecosystems animal population. However, manual inspection of the images produced is expensive, laborious, and time-consuming. The success of deep learning systems using camera trap images has been previously explored in preliminary stages. These studies, however, are lacking in their practicality. They are primarily focused on extremely large datasets, often millions of images, and there is little to no focus on performance when tasked with species identification in new locations not seen during training. Our goal was to test the capabilities of deep learning systems trained on camera trap images using modestly sized training data, compare performance when considering unseen background locations, and quantify the gradient of lower bound performance to provide a guideline of data requirements in correspondence to performance expectations. We use a dataset provided by Parks Canada containing 47,279 images collected from 36 unique geographic locations across multiple environments. Images represent 55 animal species and human activity with high-class imbalance. We trained, tested, and compared the capabilities of six deep learning computer vision networks using transfer learning and image augmentation: DenseNet201, Inception-ResNet-V3, InceptionV3, NASNetMobile, MobileNetV2, and Xception. We compare overall performance on "trained" locations where DenseNet201 performed best with 95.6% top-1 accuracy showing promise for deep learning methods for smaller scale research efforts. Using trained locations, classifications with <500 images had low and highly variable recall of 0.750 ± 0.329, while classifications with over 1,000 images had a high and stable recall of 0.971 ± 0.0137. Models tasked with classifying species from untrained locations were less accurate, with DenseNet201 performing best with 68.7% top-1 accuracy. Finally, we provide an open repository where ecologists can insert their image data to train and test custom species detection models for their desired ecological domain.

Metapopulation dynamics and foraging plasticity in a highly vagile seabird, the southern rockhopper penguin

Population connectivity is driven by individual dispersal potential and modulated by natal philopatry. In seabirds, high vagility facilitates dispersal yet philopatry is also common, with foraging area overlap often correlated with population connectivity. We assess the interplay between these processes by studying past and current connectivity and foraging niche overlap among southern rockhopper penguin colonies of the coast of southern South America using genomic and stable isotope analyses. We found two distinct genetic clusters and detected low admixture between northern and southern colonies. Stable isotope analysis indicated niche variability between colonies, with Malvinas/Falklands colonies encompassing the species entire isotopic foraging niche, while the remaining colonies had smaller, nonoverlapping niches. A recently founded colony in continental Patagonia differed in isotopic niche width and position with Malvinas/Falklands colonies, its genetically identified founder population, suggesting the exploitation of novel foraging areas and/or prey items. Additionally, dispersing individuals found dead across the Patagonian shore in an unusual mortality event were also assigned to the northern cluster, suggesting northern individuals reach southern localities, but do not breed in these colonies. Facilitated by variability in foraging strategies, and especially during unfavorable conditions, the number of dispersing individuals may increase and enhance the probability of founding new colonies. Metapopulation demographic dynamics in seabirds should account for interannual variability in dispersal behavior and pay special attention to extreme climatic events, classically related to negative effects on population trends.

Long-term photo-id and satellite tracking reveal sex-biased survival linked to movements in an endangered species

Sex-biased survival linked to anthropogenic threats places populations at risk. We show the utility of long-term multidecadal photo-identification (photo-id) combined with long-term high-resolution (Fastloc-GPS) satellite telemetry to investigate the links between mortality rates and patterns of movement for a wide-ranging, endangered marine vertebrate. Using a photo-identification database of 947 loggerhead turtles (Caretta caretta) compiled over 18 yr, we estimated greater annual survival rates of females (0.89; 95% confidence interval [CI] 0.87-0.90) compared to males (0.73; 95% CI 0.67-0.78). For males satellite-tracked across multiple breeding seasons, 100% (26 of 26) returned to the same breeding site, suggesting the calculated lower male survival rate was likely not due to emigration to breed elsewhere. 10,111 and 2,524 tracking days for males (n = 39 individuals) and females (n = 18 individuals), respectively, revealed different habitat-use patterns outside the breeding season: males tended to occupy foraging sites closer to shore and closer to breeding sites but, due to their generally annual breeding, compared to biennial breeding for females, males migrated further per year on average. These differences in movement patterns likely contribute to higher mortality in males through increased interaction with anthropogenic threats. Long-term identification coupled with tracking offers great promise for estimating the survival rates of other wide-ranging species.

Accounting for stochasticity in demographic compensation along the elevational range of an alpine plant

Demographic compensation arises when vital rates change in opposite directions across populations, buffering the variation in population growth rates, and is a mechanism often invoked to explain the stability of species geographic ranges. However, studies on demographic compensation have disregarded the effects of temporal variation in vital rates and their temporal correlations, despite theoretical evidence that stochastic dynamics can affect population persistence in temporally varying environments. We carried out a seven-year-long demographic study on the perennial plant Arabis alpina (L.) across six populations encompassing most of its elevational range. We discovered demographic compensation in the form of negative correlations between the means of plant vital rates, but also between their temporal coefficients of variation, correlations and elasticities. Even if their contribution to demographic compensation was small, this highlights a previously overlooked, but potentially important, role of stochastic processes in stabilising population dynamics at range margins.