Abundance Of Animal Populations Research Articles

Validation of satellite imagery for quantitative population assessment and monitoring of Atlantic walrus

Monitoring animal population abundance and distribution is essential for conservation and management. Recent advances in very high-resolution (VHR) satellite imagery allow for unprecedented detection and identification of animals, offering a potential alternative to conventional methods of population assessment such as aerial surveys. Here, we compare satellite and aerial survey images of a terrestrial walrus haul-out site in the Canadian High Arctic taken 1.5 h apart. While the 30-cm resolution of the commercially available satellite image was insufficient to reliably count individual walruses visually, a manual digitization method successfully identified and delineated image areas confirmed visually to have walrus. Estimates of numbers of hauled out walrus obtained by multiplying the detected area by a range of densities in the aerial image (231) agreed well with actual counts in 35 and 55 mm aerial images (217–240). Potential applications of this approach include quantitative abundance estimation or more simple monitoring of presence/absence over large expanses of remote areas that are logistically difficult to cover using survey aircraft.

Computing Invasive Species Population Based on a Generalized Random Walk Process: Application to Blue Crab (Callinectes sapidus)

Animal population abundance is a significant parameter for studies on invasive species that can threaten the ecosystem. Researchers have been developing population estimation methods since the 18th century, in order to evaluate species’ evolution and environmental effects. However, studies on the population density of the invasive species Callinectes sapidus are very limited. The present work, using a simulation model combined with field measurements, examines an innovative methodology for estimating the current population of the invasive species Callinectes sapidus in a shallow Mediterranean coastal lagoon. The methodology presented here builds the first stage of modeling and predicting the evolution of this species’ population in marine environments. The simulation model’s results are validated with an estimation of the total population based on juvenile abundance, and a curvature of the species population estimation based on cage catch is implemented. The simulation experiments presented here show the possibility of a robust prediction for blue crab population estimation.

Logistic-growth models measuring density feedback are sensitive to population declines, but not fluctuating carrying capacity.

Analysis of long-term trends in abundance of animal populations provides insights into population dynamics. Population growth rates are the emergent interplay of inter alia fertility, survival, and dispersal. However, the density feedbacks operating on some vital rates ("component feedback") can be decoupled from density feedbacks on population growth rates estimated using abundance time series ("ensemble feedback"). Many of the mechanisms responsible for this decoupling are poorly understood, thereby questioning the validity of using logistic-growth models versus vital rates to infer long-term population trends. To examine which conditions lead to decoupling, we simulated age-structured populations of long-lived vertebrates experiencing component density feedbacks on survival. We then quantified how imposed stochasticity in survival rates, density-independent mortality (catastrophes, harvest-like removal of individuals) and variation in carrying capacity modified the ensemble feedback in abundance time series simulated from age-structured populations. The statistical detection of ensemble density feedback from census data was largely unaffected by density-independent processes. Long-term population decline caused from density-independentmortalitywas the main mechanism decoupling the strength of component versus ensemble density feedbacks. Our study supports the use of simple logistic-growth models to capture long-term population trends, mediated by changes in population abundance, when survival rates are stochastic, carrying capacity fluctuates, and populations experience moderate catastrophic mortality over time.

A meta‐analysis of shrub density as a predictor of animal abundance

Facilitative interactions between shrub and animal species influence the structure and composition of communities. The benefits associated with woody shrub species can critically influence local animal populations, in particular. Here, we tested the relative importance of the density of shrub species on the local abundance of animal populations using a meta‐analysis. Full‐text review for shrub density, animal abundance or density and sampling effort, resulted in a total of 113 independent observations that reported both shrub density and animal abundance. A meta‐regression of shrub density on animal density with feeding functional group of the animal species as a moderator was used to test the predictive capacity of this simple vegetation measure on animal populations. Shrub density positively predicted animal abundance in these studies – particularly in deserts and grasslands. Shrub and woody plant density can thus be used as a potential rapid proxy for habitat in predicting local animal abundances. This method can support restoration and conservation of resident animal species in impacted ecosystems structured by woody shrubs globally.

Habitat quality does not predict animal population abundance on frequently disturbed landscapes

Increases in frequency of anthropogenic and natural disturbances exacerbated by climate change are disrupting animal movement patterns and, in turn, species distribution and abundance. Habitat models are a valuable approach for predicting how a species or population is distributed across habitats. However, in these models, the environmental characteristics describing habitat are typically constant over time which is inaccurate for a frequently disturbed landscape. The goal of this study is to assess the degree to which frequent disturbances can alter abundance and distribution, to the point of which inferences from static habitat maps are no longer relevant. We simulated individual animal movement in a dynamically disturbed landscape and compared the observed spatial relative abundance to the one predicted from a static habitat model fit to the simulated trajectories. We found that the prediction error is higher when the landscape is disturbed than where there are no disturbances. This result holds even with the addition of life-history and demographic processes to the model which would facilitate the discovery of novel habitat by increasing density-dependent movement, thereby bringing the spatial distribution of individuals closer to a proportion of habitat quality arising from the population at equilibrium assumption underlying most habitat models. In the context of species at risk recovery planning, using habitat models with constant environmental covariates to forecast animal locations in areas with more frequent disturbances as a result of climate change will likely produce inaccurate predictions.

Assessing the efficiency of using passive hair traps as a method for non-invasive sampling from European beavers (Castor fiber L.)

Using passive hair traps to obtain genetic material from wild mammals is an effective form of testing the abundance of animal populations. Based on genetic analysis of collected hair, it is possible to estimate the number and sex of individuals present in a given area. The aim of this study was to confirm the success of the method of collecting hair from beavers in a non-invasive way, as well as to determine the effectiveness of using passive hair traps as sampling tools that can be applied in different regions. The study was carried out in the area of Stobrawa Landscape Park (southwestern Poland) between December 2017 and May 2018. For 17 control days, 12 samples were obtained, which gave the result of 0.7 samples per control day. This study shows that the proposed method, due to its simplicity and efficiency, could be a cost-effective way of collecting hair from free-ranging beavers without the need for capturing individuals.

Where and when does the danger lie? Assessing how location, season and time of day affect the sequential stages of predation by lions in western Serengeti National Park

AbstractPredation is a fundamental ecological process influencing the distribution and abundance of animal populations and underlying how prey species perceive risk. The predation process is composed of four sequential stages – search, encounter, attack and kill – each of which has been used to describe risk across the landscape. Here, we used direct observational data of free‐ranging, radio‐collared African lions in Serengeti National Park's western corridor to (1) investigate daily and seasonal predation stage probabilities and (2) using two analytical approaches, compare four mechanisms – prey distribution, intra‐specific competition, spatially anchored landscape features and predator hunting method – that potentially drive spatial predation stage patterns. Results showed that lions encountered potential prey at night significantly less than during diurnal or crepuscular periods. Nocturnal observations were predominantly during full‐moon phases, so if this lower nocturnal encounter rate was due to moon phase it may contribute to lions' typically poor full‐moon hunting success. Predation stage probabilities did not differ between seasons despite high variability in seasonal prey abundance. Spatially, lions encountered potential prey in prey‐rich, open areas near water and spatial range centres. Compared with available areas within seasonal ranges, lion attacks were more likely where prey abundance was high, and kill locations were associated with prey‐rich areas near water and range centres, collectively suggesting opportunistic hunting. However, compared with preceding predation stage locations, attacks occurred near range peripheries and kills where hunting cover was greater, suggesting ambush predation. Our results indicate substantial temporal and spatial variation across the different stages of the predation process. They also highlight first, that results can vary in important ways depending on how analyses are approached, and second, that understanding predator‐prey dynamics depends on analyses of the different stages of predation.

Changes in prey, turbidity, and competition reduce somatic growth and cause the collapse of a fish population

AbstractSomatic growth exerts strong control on patterns in the abundance of animal populations via effects on maturation, fecundity, and survival rates of juveniles and adults. In this paper, we quantify abiotic and biotic drivers of rainbow trout growth in the Colorado River, Arizona, USA, and the resulting impact on spatial and temporal variation in abundance. Inferences are based on ~10,000 observations of individual growth rates obtained through an intensive mark–recapture effort conducted over 5 yrs (2012–2016) in a 130‐km long study segment downstream of Glen Canyon Dam. Prey availability, turbidity‐driven feeding efficiency, and intraspecific competition were the dominant drivers of rainbow trout growth. Discharge, water temperature, and solar insulation were also evaluated but had a smaller influence. Mixed‐effect models explained 79–82% of the variability in observed growth rates, with fixed covariate effects explaining 79–87% of the total variation in growth parameters across five reaches and 18 quarterly sampling intervals. Reductions in growth owing in part to a phosphorous‐driven decline in prey availability, led to a substantive loss in mass and poor fish condition. This in turn lowered survival rates and delayed maturation, which led to a rapid decline in abundance and later recruitments. Reductions in feeding efficiency, due to episodic inputs of fine sediment from tributaries, and warmer water temperatures, contributed to reduced growth in downstream reaches, which led to more severe declines in abundance. Somatic growth rates increased following the population collapse due to reduced competition, and in the absence of substantive increases in prey availability. Our study elucidates important linkages between abiotic and biotic factors, somatic growth, and vital rates, and demonstrates how variation in somatic growth influences temporal and spatial patterns in abundance.

Variation in behavioral traits of two frugivorous mammals may lead to differential responses to human disturbance.

Human activities can lead to a shift in wildlife species’ spatial distribution. Understanding the specific effects of human activities on ranging behavior can improve conservation management of wildlife populations in human‐dominated landscapes. This study evaluated the effects of forest use by humans on the spatial distribution of mammal species with different behavioral adaptations, using sympatric western lowland gorilla and central chimpanzee as focal species. We collected data on great ape nest locations, ecological and physical variables (habitat distribution, permanent rivers, and topographic data), and anthropogenic variables (distance to trails, villages, and a permanent research site). Here, we show that anthropogenic variables are important predictors of the distribution of wild animals. In the resource model, the distribution of gorilla nests was predicted by nesting habitat distribution, while chimpanzee nests were predicted first by elevation followed by nesting habitat distribution. In the anthropogenic model, the major predictors of gorilla nesting changed to human features, while the major predictors of chimpanzee nesting remained elevation and the availability of their preferred nesting habitats. Animal behavioral traits (body size, terrestrial/arboreal, level of specialization/generalization, and competitive inferiority/superiority) may influence the response of mammals to human activities. Our results suggest that chimpanzees may survive in human‐encroached areas whenever the availability of their nesting habitat and preferred fruits can support their population, while a certain level of human activities may threaten gorillas. Consequently, the survival of gorillas in human‐dominated landscapes is more at risk than that of chimpanzees. Replicating our research in other sites should permit a systematic evaluation of the influence of human activity on the distribution of mammal populations. As wild animals are increasingly exposed to human disturbance, understanding the resulting consequences of shifting species distributions due to human disturbance on animal population abundance and their long‐term survival will be of growing conservation importance.

Vocal activity of the Central European Boreal Owl population in relation to varying environmental conditions

Vocal activity is one of the main attributes that enables assessment of the presence and abundance of animal populations. However, the factors affecting vocal activity are rarely studied, especially in owls. We studied the vocal activity of Boreal Owl (Aegolius funereus) using acoustic monitoring in relation to environmental factors in Central Europe (Czech Republic), over an area of 100 km2. We analysed a total of 1,310 hours of sound recordings collected over two years (2015 and 2016) at the turn of March/April and April/May. The frequency of sampling points in which we recorded Boreal Owl vocalizations varied from 0.17 to 0.59 and was higher in the year of increased prey abundance (2015) and earlier in the breeding season (March/April). The duration of Boreal Owl vocal activity varied from 1 to 60 minutes per hour and was related to temporal factors. In particular, the duration of Boreal Owl vocalization increased late in the breeding season (April/May) and in the year of higher prey abundance (2015), and it showed two peaks of vocal activity during the night.

Re-constructing nutritional history of Serengeti wildebeest from stable isotopes in tail hair: seasonal starvation patterns in an obligate grazer.

RationaleNutritional bottlenecks often limit the abundance of animal populations and alter individual behaviours; however, establishing animal condition over extended periods of time using non‐invasive techniques has been a major limitation in population ecology. We test if the sequential measurement of δ15N values in a continually growing tissue, such as hair, can be used as a natural bio‐logger akin to tree rings or ice cores to provide insights into nutritional stress.MethodsNitrogen stable isotope ratios were measured by continuous‐flow isotope‐ratio mass spectrometry (IRMS) from 20 sequential segments along the tail hairs of 15 migratory wildebeest. Generalized Linear Models were used to test for variation between concurrent segments of hair from the same individual, and to compare the δ15N values of starved and non‐starved animals. Correlations between δ15N values in the hair and periods of above‐average energy demand during the annual cycle were tested using Generalized Additive Mixed Models.ResultsThe time series of nitrogen isotope ratios in the tail hair are comparable between strands from the same individual. The most likely explanation for the pattern of 15N enrichment between individuals is determined by life phase, and especially the energetic demands associated with reproduction. The mean δ15N value of starved animals was greater than that of non‐starved animals, suggesting that higher δ15N values correlate with periods of nutritional stress.ConclusionsHigh δ15N values in the tail hair of wildebeest are correlated with periods of negative energy balance, suggesting they may be used as a reliable indicator of the animal's nutritional history. This technique might be applicable to other obligate grazers. Most importantly, the sequential isotopic analysis of hair offers a continuous record of the chronic condition of wildebeest (effectively converting point data into time series) and allows researchers to establish the animal's nutritional diary.

Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia

Accurate information on the density and abundance of animal populations is essential for understanding species' ecology and for conservation planning, but is difficult to obtain. The endangered orangutan (Pongo spp.) is an example; due to its elusive behavior and low densities, researchers have relied on methods that convert nest counts to orangutan densities and require substantial effort for reliable results. Camera trapping and spatial capture–recapture (SCR) models could provide an alternative but have not been used for primates. We compared density estimates calculated using the two methods for orangutans in the Wehea Forest, East Kalimantan, Indonesia. Camera trapping/SCR modeling produced a density estimate of 0.16±0.09–0.29 indiv/km2, and nest counts produced a density estimate of 1.05±0.18–6.01 indiv/km2. The large confidence interval of the nest count estimate is probably due to high variance in nest encounter rates, indicating the need for larger sample size and the substantial effort required to produce reliable results using this method. The SCR estimate produced a very low density estimate and had a narrower but still fairly wide confidence interval. This was likely due to unmodeled heterogeneity and small sample size, specifically a low number of individual captures and recaptures. We propose methodological fixes that could address these issues and improve precision. A comparison of the overall costs and benefits of the two methods suggests that camera trapping/SCR modeling can potentially be a useful tool for assessing the densities of orangutans and other elusive primates, and warrant further investigation to determine broad applicability and methodological adjustments needed.

Peculiarities of biotic interactions in the soil system

The heterogeneity of the soil environment is an important factor in the taxonomic and ecological diversity of the soil animal population. The contribution of invertebrates to the formation of aerial space in mineral soil horizons, in the form of a stable system of biopores, is considered on the basis of the author’s original materials and literature data. Aerial space is the necessary condition for the life of aerobiotic forms in the mineral soil, which comprise the bulk of soil invertebrates belonging to meso- and macrofauna. Zoogenic mechanisms of the formation of soil pores and soil aggregates are analyzed. Pore walls and aggregate surfaces are populated by different groups of pedobionts. !e partial isolation of these loci decreases predation, which creates conditions for the maintenance of high diversity and abundance of animal populations in the restricted volume of the populated soil profile.

The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling

Distance sampling is being extensively used to estimate the abundance of animal populations. Nevertheless, the great variety of ways in which data can be analyzed may limit comparisons due to the lack of standardization of such protocols. In this study, the influence of analytical procedures for distance sampling data on density estimates and their precision was assessed. We have used data from 21 surveys of mountain ungulates in the Iberian Peninsula, France and the Italian Alps. Data from such surveys were analyzed with the program Distance 6.0. Our analyses show that estimated density can be higher for higher levels of data truncation. We also confirm that the estimates tend to be more precise when data are analyzed without binning and without truncating. We found no evidence of size biased sampling as group size and distances were uncorrelated in most of our surveys. Despite distance sampling being a fairly robust methodology, it can be sensitive to some data analysis strategies.

Accommodating species identification errors in transect surveys

Ecologists often use transect surveys to estimate the density and abundance of animal populations. Errors in species classification are often evident in such surveys, yet few statistical methods exist to properly account for them. In this paper, we examine biases that result from species misidentification when ignored, and we develop statistical models to provide unbiased estimates of density in the face of such errors. Our approach treats true species identity as a latent variable and requires auxiliary information on the misclassification process (such as informative priors, experiments using known species, or a double-observer protocol). We illustrate our approach with simulated census data and with double-observer survey data for ice-associated seals in the Bering Sea. For the seal analysis, we integrated misclassification into a model-based framework for distance-sampling data. The simulated data analysis demonstrated reliable estimation of animal density when there are experimental data to inform misclassification rates; double-observer protocols provided robust inference when there were "unknown" species observations but no outright misclassification, or when misclassification probabilities were symmetric and a symmetry constraint was imposed during estimation. Under our modeling framework, we obtained reasonable apparent densities of seal species even under considerable imprecision in species identification. We obtained more reliable inferences when modeling variation in density among transects. We argue that ecologists should often use spatially explicit models to account for differences in species distributions when trying to account for species misidentification. Our results support using double-observer sampling protocols that guard against species misclassification (i.e., by recording uncertain observations as "unknown").

Why are some animal populations unaffected or positively affected by roads?

In reviews on effects of roads on animal population abundance we found that most effects are negative; however, there are also many neutral and positive responses [Fahrig and Rytwinski (Ecol Soc 14:21, 2009; Rytwinski and Fahrig (Biol Conserv 147:87-98, 2012)]. Here we use an individual-based simulation model to: (1) confirm predictions from the existing literature of the combinations of species traits and behavioural responses to roads that lead to negative effects of roads on animal population abundance, and (2) improve prediction of the combinations of species traits and behavioural responses to roads that lead to neutral and positive effects of roads on animal population abundance. Simulations represented a typical situation in which road mitigation is contemplated, i.e. rural landscapes containing a relatively low density (up to 1.86 km/km(2)) of high-traffic roads, with continuous habitat between the roads. In these landscapes, the simulations predict that populations of species with small territories and movement ranges, and high reproductive rates, i.e. many small mammals and birds, should not be reduced by roads. Contrary to previous suggestions, the results also predict that populations of species that obtain a resource from roads (e.g. vultures) do not increase with increasing road density. In addition, our simulations support the predation release hypothesis for positive road effects on prey (both small- and large-bodied prey), whereby abundance of a prey species increased with increasing road density due to reduced predation by generalist road-affected predators. The simulations also predict an optimal road density for the large-bodied prey species if it avoids roads or traffic emissions. Overall, the simulation results suggest that in rural landscapes containing high-traffic roads, there are many species for which road mitigation may not be necessary; mitigation efforts should be tailored to the species that show negative population responses to roads.

Mechanistic approaches to understanding and predicting mammalian space use: recent advances, future directions

The coming of age of global positioning system telemetry, in conjunction with recent theoretical innovations for formulating quantitative descriptions of how different ecological forces and behavioral mechanisms shape patterns of animal space use, has led to renewed interest and insight into animal home-range patterns. This renaissance is likely to continue as a result of ongoing synergies between these empirical and theoretical advances. In this article I review key developments that have occurred over the past decade that are furthering our understanding of the ecology of animal home ranges. I then outline what I perceive as important future directions for furthering our ability to understand and predict mammalian home-range patterns. Interesting directions for future research include improved insights into the environmental and social context of animal movement decisions and resulting patterns of space use; quantifying the role of memory in animal movement decisions; and examining the relevance of these advances in our understanding of animal movement behavior and space use to questions concerning the demography and abundance of animal populations.

The distribution and abundance of animal populations in a climate of uncertainty

Current predictions regarding the ecological consequences of climate change on animal populations are generally autecological and species‐specific, and/or non‐mechanistic extrapolations of recent short‐term patterns. To better understand and predict the effects of climate change on the distribution of species and the abundance of populations we offer a novel, broad theoretical framework. Climate‐induced changes in trophic structure may actually be more predictable than effects on individual species. The logic is that there are general differences in climatic sensitivity among trophic levels – specifically, that as one moves up trophic levels, there is an increase in the temperature sensitivity of vital rates. More precisely, we provide: (1) a formal mathematical definition of distribution limits that is both operational and conceptual, introducing the concept DL50, defined as the geographic and climatic isoline representing an equilibrium occupancy of half of the suitable habitats; (2) a matrix of the possible changes in trophic structure from climate change and the general theoretical consequences; and (3) a new idea that predicts broad effects of climatic warming on trophic systems. Our intention is to help meet the challenge of developing and testing general theoretical models that can predict which species will be winners and losers in ecological time, which evolutionary traits will be favoured or selected against, and what will be consequences for ecosystem structure and function.

Spoor density as a measure of true density of a known population of free‐ranging wild cheetah in Botswana

AbstractKnowledge of the abundance of animal populations is essential for their management and conservation. Determining reliable measures of abundance is, however, difficult, especially with wide‐ranging species such as cheetah Acinonyx jubatus. This study generated a correction factor to calculate true cheetah density from spoor survey data and subsequently tested its accuracy using the following season's data. Data were collected from October 2005 to December 2006 on a known population of wild, free‐ranging cheetah in the Jwana Game Reserve, Botswana. The cheetahs in the area were captured, tagged and photographed. The reserve was divided into twelve 9 km transects covering all vegetation types and prey densities. The total sampling distance was 8226 km, with a spoor density of 2.32 individual cheetah spoor per 100 km2. To determine a precise and accurate spoor density, it was necessary to sample for a longer period during the dry season (April–September) than during the wet season (October–March). This difference may be due to cheetah behavioural changes with seasonal variations in habitat and prey. The true density was 5.23 cheetahs per 100 km2 ranging from 3.33 to 7.78 at the low and high points of the population, respectively. A positive linear correlation between spoor and true density was observed. This relationship differed in the wet and dry season and required refinement with the following season's data. Correction factors may be viable, but require further testing taking the behavioural responses to seasonal, habitat and prey variations into consideration.

Reducing complexity when studying seed dispersal at community scales: a functional classification of vertebrate seed dispersers in tropical forests

The process of seed dispersal has a profound effect on vegetation structure and diversity in tropical forests. However, our understanding of the process and our ability to predict its outcomes at a community scale are limited by the frequently large number of interactions associated with it. Here, we outline an approach to dealing with this complexity that reduces the number of unique interactions considered by classifying the participants according to their functional similarity. We derived a classification of dispersers based on the nature of the dispersal service they provide to plants. We described the quantities of fruit handled, the quality of handling and the diversity of plants to which the service is provided. We used ten broad disperser traits to group 26 detailed measures for each disperser. We then applied this approach to vertebrate dispersers in Australia's tropical forests. Using this we also develop a classification that may be more generally applicable. For each disperser, data relating to each trait was obtained either from the field or published literature. First, we identified dispersers whose service outcomes were so distinct that statistical analysis was not required and assigned them to functional groups. The remaining dispersers were assigned to functional groups using cluster analysis. The combined processes created 15 functional groups from 65 vertebrate dispersers in Australian tropical forests. Our approach--grouping dispersers on the basis of the type of dispersal service provided and the fruit types it is provided to--represents a means of reducing the complexity encountered in tropical seed dispersal systems and could be effectively applied in community level studies. It also represents a useful tool for exploring changes in dispersal services when the distribution and abundance of animal populations change due to human impacts.