Animal Population Dynamics Research Articles

Reproduction probabilities and size distributions of the smooth snake Coronella austriaca in the Netherlands and Norway

Abstract Whether females participate in reproduction every year or rather skip years is pivotal information for understanding the dynamics of animal populations. In ectotherms this reproduction frequency might depend on factors like temperature, individual size, and prey availability. Here we studied the reproduction rate of the smooth snake Coronella austriaca at two latitudes: in Norway and The Netherlands. Reproductive and morphological data were collected in Norway (34 years) and The Netherlands (5 years). To account for differential resighting probabilities of pregnant and non-pregnant females, we performed multi-state mark-recapture analyses. Reproductive rate, quantified as the probability of participating in reproduction in consecutive years, was calculated for both pregnant and non-pregnant females. The results showed a clear difference in reproductive rate between the two latitudes, with only 15% of pregnant females reproducing again in the following year in Norway versus 93% in The Netherlands. Furthermore, in Norway females grew larger and started reproduction at a higher age. Litter size and juvenile total length and body mass were also significantly higher in Norwegian smooth snakes.

Ecological Forecasts Reveal Limitations of Common Model Selection Methods: Predicting Changes in Beaver Colony Densities

Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and predictions. While the widespread use of model selection using information criteria has pushed ecology toward placing a higher emphasis on prediction, few attempts have been made to validate the ability of information criteria to correctly identify the most parsimonious model with the greatest predictive accuracy. Here, we used an ecological forecasting framework to test the ability of information criteria to accurately predict the relative contribution of density dependence and density-independent factors (forage availability, harvest, weather, wolf [Canis lupus] density) on inter-annual fluctuations in beaver (Castor canadensis) colony densities. We modeled changes in colony densities using a discrete-time Gompertz model, and assessed the performance of four models using information criteria values: density-independent models with (1) and without (2) environmental covariates; and density-dependent models with (3) and without (4) environmental covariates. We then evaluated the forecasting accuracy of each model by withholding the final one-third of observations from each population and compared observed vs. predicted densities. Information criteria and our forecasting accuracy metrics both provided strong evidence of compensatory density dependence in the annual dynamics of beaver colony densities. However, despite strong within-sample performance by the most complex model (density-dependent with covariates) as determined using information criteria, hindcasts of colony densities revealed that the much simpler density-dependent model without covariates performed nearly as well predicting out-of-sample colony densities. The hindcast results indicated that the complex model over-fit our data, suggesting that parameters identified by information criteria as important predictor variables are only marginally valuable for predicting landscape-scale beaver colony dynamics. Our study demonstrates the importance of evaluating ecological models and predictions with long-term data and revealed how a known limitation of information criteria (over-fitting of complex models) can affect our interpretation of ecological dynamics. While incorporating knowledge of the factors that influence animal population dynamics can improve population forecasts, we suggest that comparing forecast performance metrics can likewise improve our knowledge of the factors driving population dynamics.

Livestock prevalence in the Egyptian vulture diet during European sanitary restrictions on carcass disposal

Food is a primary factor driving animal population dynamics. Low quality food (e.g. poisoned carrion) has caused large declines of Asian and African vulture populations pushing some species to the brink of extinction. Although Europe emerges as a stronghold for the guild, European vultures face potential food shortages due to sanitary restrictions banning the disposal of livestock carcasses in the field after the Bovine Spongiform Encephalopathy (BSE). Determining the diet of European vultures and in particular the role livestock plays in it is needed for preserving these species and their scavenging role in food webs. We analysed the diet composition of 13 nests of the endangered Egyptian vulture (Neophron percnopterus) in a species stronghold in Europe (NW Spain), during the period of BSE restrictions (2007, 2009 and 2010). We identified 312 remains from 25 species, mainly mammals (70.8%), birds (17.0%) and fishes (7.7%). Livestock dominated the Egyptian vulture diet, comprising 23.9% of total items (11.8% of sheep-goat, 7.0% of bovine). Differences in diet composition among nests responded to habitat characteristics determining the availability of some food items (e.g. water for fishes). Our findings support a major role of livestock in the Egyptian vulture diet, suggesting a lack of compliance with sanitary restrictions banning the disposal of livestock carcasses in the field, with potential to affect vulture conservation and their scavenging function in ecosystems.

Synchronization in leader-follower switching dynamics

The features of animal population dynamics, for instance, flocking and migration, are often synchronized for survival under large-scale climate change or perceived threats. These coherent phenomena have been explained using synchronization models. However, such models do not take into account asynchronous and adaptive updating of an individual's status at each time. Here, we modify the Kuramoto model slightly by classifying oscillators as leaders or followers, according to their angular velocity at each time, where individuals interact asymmetrically according to their leader/follower status. As the angular velocities of the oscillators are updated, the leader and follower status may also be reassigned. Owing to this adaptive dynamics, oscillators may cooperate by taking turns acting as a leader or follower. This may result in intriguing patterns of synchronization transitions, including hybrid phase transitions, and produce the leader-follower switching pattern observed in bird migration patterns.

Hurricane-induced demographic changes in a non-human primate population.

Major disturbance events can have large impacts on the demography and dynamics of animal populations. Hurricanes are one example of an extreme climatic event, predicted to increase in frequency due to climate change, and thus expected to be a considerable threat to population viability. However, little is understood about the underlying demographic mechanisms shaping population response following these extreme disturbances. Here, we analyse 45 years of the most comprehensive free-ranging non-human primate demographic dataset to determine the effects of major hurricanes on the variability and maintenance of long-term population fitness. For this, we use individual-level data to build matrix population models and perform perturbation analyses. Despite reductions in population growth rate mediated through reduced fertility, our study reveals a demographic buffering during hurricane years. As long as survival does not decrease, our study shows that hurricanes do not result in detrimental effects at the population level, demonstrating the unbalanced contribution of survival and fertility to population fitness in long-lived animal populations.

Ecological forecasts reveal limitations of common model selection methods: predicting changes in beaver colony densities.

Over the past two decades, there have been numerous calls to make ecology a more predictive science through direct empirical assessments of ecological models and predictions. While the widespread use of model selection using information criteria has pushed ecology toward placing a higher emphasis on prediction, few attempts have been made to validate the ability of information criteria to correctly identify the most parsimonious model with the greatest predictive accuracy. Here, we used an ecological forecasting framework to test the ability of information criteria to accurately predict the relative contribution of density dependence and density‐independent factors (forage availability, harvest, weather, wolf [Canis lupus] density) on inter‐annual fluctuations in beaver (Castor canadensis) colony densities. We modeled changes in colony densities using a discrete‐time Gompertz model, and assessed the performance of four models using information criteria values: density‐independent models with (1) and without (2) environmental covariates; and density‐dependent models with (3) and without (4) environmental covariates. We then evaluated the forecasting accuracy of each model by withholding the final one‐third of observations from each population and compared observed vs. predicted densities. Information criteria and our forecasting accuracy metrics both provided strong evidence of compensatory density dependence in the annual dynamics of beaver colony densities. However, despite strong within‐sample performance by the most complex model (density‐dependent with covariates) as determined using information criteria, hindcasts of colony densities revealed that the much simpler density‐dependent model without covariates performed nearly as well predicting out‐of‐sample colony densities. The hindcast results indicated that the complex model over‐fit our data, suggesting that parameters identified by information criteria as important predictor variables are only marginally valuable for predicting landscape‐scale beaver colony dynamics. Our study demonstrates the importance of evaluating ecological models and predictions with long‐term data and revealed how a known limitation of information criteria (over‐fitting of complex models) can affect our interpretation of ecological dynamics. While incorporating knowledge of the factors that influence animal population dynamics can improve population forecasts, we suggest that comparing forecast performance metrics can likewise improve our knowledge of the factors driving population dynamics.

Pre- to post-fledging carryover effects and the adaptive significance of variation in wing development for juvenile songbirds.

Evolutionary ecologists have long been interested in the adaptive significance of morphological traits across stages of animal life. In some cases, traits that are not adaptive in one life stage may be adaptive in a subsequent stage. As such, morphological traits may generate important carryover effects, whereby conditions experienced during one life-history stage influence fitness during subsequent stages. Carryover effects are particularly relevant in young animals, as early life stages are thought to be critical with respect to animal life-history evolution and population dynamics. In songbirds, pre- to post-fledging carryover effects operating within species may be critical for survival and shape life histories among species, but remain poorly understood. Among potential songbird traits, wing development and its associated flight ability may be the most important for post-fledging survival. Thus, to assess the adaptive significance of wing development for juvenile songbirds under Arnold's (Integrative and Comparative Biology, 23, 1983, 347) classic performance-morphology-fitness paradigm, we tested for pre- to post-fledging carryover effects among 20 coexisting species (nine focal species) of an avian community in east-central Illinois, USA. We found evidence for pre- to post-fledging carryover effects of wing development in all species, by which individuals with less developed wings exhibited poorer flight ability and experienced higher rates of mortality after fledging. Furthermore, our findings suggest that carryover effects operating at the species level ultimately help shape patterns of life-history variation among species. Specifically, we found that species with higher rates of nest predation had shorter nestling periods, fledged young with less developed wings and exhibited higher rates of post-fledging mortality. Our results highlight the adaptive significance of wing development as a key factor generating pre- to post-fledging carryover effects among songbirds, and demonstrate how morphological traits, locomotor performance, and age-specific survival may trade-off and interact across juvenile life stages to shape animal life histories.

Contrasting effects of climate change on seasonal survival of a hibernating mammal

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics.

The Fox and the Crow. A need to update pest control strategies

The recent discovery that cats and mustelids can be infected by SARS-CoV-2 may raise the question of monitoring domestic, feral and wild populations of such animals, as an adjunct to the elimination of COVID-19 in humans. Emergency solutions might consider large scale control of these animals in the wild. However, looking at science recently published on native vertebrate pest control reveals first that usual controls do not succeed in reducing animal numbers and associated damages, second that controlling can be counter-productive in increasing the infectious risks for humans and livestock. The examples of red fox and corvids are detailed in a European context, illustrating the urgent need for an ethical evaluation of ecological and economic costs and benefits of pest control strategies. A complete scientific evaluation process must be implemented and up-dated regularly, to be organized in four major steps, once the aim of the control strategy has been defined: (1) evaluating damages/risks caused by the animals, to be balanced with the ecosystem services they may provide, also in terms of economic costs; (2) unravelling spatial and temporal population dynamics of target animals to identify, if any, optimal control scenarios – which could be done within an adaptive management framework; (3) estimating the economic costs of implementing those optimal control scenarios, to be compared to the economic costs of damages/diseases; (4) finally evaluating how the control strategy reached its aims. A modern fable of the Fox and the Crow should deliver a timely moral for an ethical, ecological and economical appraisal of pest control strategies in Europe.

The Australian Roadkill Reporting Project-Applying Integrated Professional Research and Citizen Science to Monitor and Mitigate Roadkill in Australia.

Simple SummaryAustralia has no database of national roadkill. The current research project fills that knowledge gap by developing a roadkill reporting application that enables professional and citizen scientists to record photographs of roadkill with location, time and date. This embodies the concept of ‘One Welfare’ as it affects humans, animals and the environment. Uploaded to a website, these data can identify roadkill hotspots, tabulate species of animals killed and potentially be used for ecological studies of roadkill numbers, species distribution, population trends, animal behaviour and disease. Initial results indicate that mammal roadkill mostly occurs at night and that of birds and reptiles during daytime. Mammals make up three-quarters of the roadkill recorded and this includes endangered species. Two examples of roadkill hotspots are shown in Queensland and Tasmania. These will enable further research to suggest how roadkill mitigation measures may be optimally employed.Australia has no national roadkill monitoring scheme. To address this gap in knowledge, a roadkill reporting application (app) was developed to allow members of the public to join professional researchers in gathering Australian data. The app is used to photograph roadkill and simultaneously records the GPS location, time and date. These data are uploaded immediately to a website for data management. To illustrate the capacity to facilitate cost-effective mitigation measures the article focuses on two roadkill hotspots—in Queensland and Tasmania. In total, 1609 reports were gathered in the first three months of the project. They include data on mammals (n = 1203, 75%), birds (n = 125, 7.8%), reptiles (n = 79, 4.9%), amphibians (n = 4, 0.025%), unidentified (n = 189, 11.8%) and unserviceable ones (n = 9). A significant finding is variance in the distribution of mammals and birds at different times of day. These findings reflect diurnal variation in the activity levels of different species and underline the need for data on a targeted species to be collected at appropriate times of day. By continuing to facilitate roadkill monitoring, it is anticipated that the data generated by the app will directly increase knowledge of roadkill numbers and hotspots. Indirectly, it will provide value-added information on animal behaviour, disease and population dynamics as well as for species distribution mapping.

Integrating satellite and unmanned aircraft system (UAS) imagery to model livestock population dynamics in the Longbao Wetland National Nature Reserve, China

The collection of field-based animal data is laborious, risky and costly in some areas, such as various nature reserves. Although multiple studies have used satellite imagery, aerial imagery, and field data individually for some animal species surveys, several technical issues still need to be addressed before full standardization of remote sensing methods for modeling animal population dynamics over large areas. This study is the first to model the population dynamics of livestock in the Longbao Wetland National Nature Reserve, China by utilizing yak estimations from Worldview-2 satellite imagery (0.5 m) collected in 2010 and yaks counted in a ground-based survey conducted in 2011 in combination with the animal population structure precisely extracted from UAS imagery captured in 2016. As a consequence, 5501, 5357, and 5510 yaks were estimated to appear in the reserve in 2010, 2011 and 2016, respectively. In total, 1092, 1062 and 1092 sheep were estimated to appear in the reserve in 2010, 2011 and 2016, respectively. The uncertainty of the presented method is also discussed. Primary experiments show that both the satellite imagery and UAS imagery are promising for use in yak censuses, but no sheep were observed in the satellite imagery because of the low resolution. Compared to the ground-based survey conducted in 2011, the UAS image estimate and satellite imagery count deviated in yak quantity by 2.69% and 2.86%, respectively. UASs are a reliable and low-budget alternative to animal surveys. No discernable changes in animal behaviors and animal distributions were observed as the UAS passed at a height of 700 m, and the accuracy of UAS imagery counts were not significantly affected by the short-distance animal movement and image mosaicking errors. The experimental results illustrate the advantages of the combination of satellite and UAS imagery in modeling animal population dynamics.

How does increasing mast seeding frequency affect population dynamics of seed consumers? Wild boar as a case study.

Mast seeding in temperate oak populations shapes the dynamics of seed consumers and numerous communities. Mast seeding responds positively to warm spring temperatures and is therefore expected to increase under global warming. We investigated the potential effects of changes in oak mast seeding on wild boar population dynamics, a widespread and abundant consumer species. Using long-term monitoring data, we showed that abundant acorn production enhances the proportion of breeding females. With a body-mass-structured population model and a fixed hunting rate of 0.424, we showed that high acorn production over time would lead to an average wild boar population growth rate of 1.197 whereas non-acorn production would lead to a stable population. Finally, using climate projections and a mechanistic model linking weather data to oak reproduction, we predicted that mast seeding frequency might increase over the next century, which would lead to increase in both wild boar population size and the magnitude of its temporal variation. Our study provides rare evidence that some species could greatly benefit from global warming thanks to higher food availability and therefore highlights the importance of investigating the cascading effects of changing weather conditions on the dynamics of wild animal populations to reliably assess the effects of climate change.

Mast seeding patterns are asynchronous at a continental scale.

Resource pulses are rare events with a short duration and high magnitude that drive the dynamics of both plant and animal populations and communities1. Mast seeding is perhaps the most common type of resource pulse that occurs in terrestrial ecosystems2, is characterized by the synchronous and highly variable production of seed crops by a population of perennial plants3,4, is widespread both taxonomically and geographically5, and is often associated with nutrient scarcity6. The rare production of abundant seed crops (mast events) that are orders of magnitude greater than crops during low seed years leads to high reproductive success in seed consumers and has cascading impacts in ecosystems2,7. Although it has been suggested that mast seeding is potentially synchronized at continental scales8, studies are largely constrained to local areas covering tens to hundreds of kilometres. Furthermore, summer temperature, which acts as a cue for mast seeding9, shows patterns at continental scales manifested as a juxtaposition of positive and negative anomalies that have been linked to irruptive movements of boreal seed-eating birds10,11. Here, we show a breakdown in synchrony of mast seeding patterns across space, leading to asynchrony at the continental scale. In an analysis of synchrony for a transcontinental North America tree species spanning distances of greater than 5,200 km, we found that mast seeding patterns were significantly asynchronous at distances of greater than 2,000 km apart (all P < 0.05). Other studies have shown declines in synchrony across distance, but not asynchrony. Spatiotemporal variation in summer temperatures at the continental scale drives patterns of synchrony in mast seeding, and we anticipate that this affects the spatial dynamics of numerous seed-eating communities, from insects to small mammals to the large-scale migration patterns of boreal seed-eating birds.

Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data.

State‐space models (SSMs) are a popular tool for modeling animal abundances. Inference difficulties for simple linear SSMs are well known, particularly in relation to simultaneous estimation of process and observation variances. Several remedies to overcome estimation problems have been studied for relatively simple SSMs, but whether these challenges and proposed remedies apply for nonlinear stage‐structured SSMs, an important class of ecological models, is less well understood. Here we identify improvements for inference about nonlinear stage‐structured SSMs fit with biased sequential life stage data. Theoretical analyses indicate parameter identifiability requires covariates in the state processes. Simulation studies show that plugging in externally estimated observation variances, as opposed to jointly estimating them with other parameters, reduces bias and standard error of estimates. In contrast to previous results for simple linear SSMs, strong confounding between jointly estimated process and observation variance parameters was not found in the models explored here. However, when observation variance was also estimated in the motivating case study, the resulting process variance estimates were implausibly low (near‐zero). As SSMs are used in increasingly complex ways, understanding when inference can be expected to be successful, and what aids it, becomes more important. Our study illustrates (a) the need for relevant process covariates and (b) the benefits of using externally estimated observation variances for inference about nonlinear stage‐structured SSMs.

Oceans of stimuli: an individual-based model to assess the role of olfactory cues and local enhancement in seabirds' foraging behaviour.

Oceans are extremely dynamic environments, which poses challenges for top-predators such as seabirds to find food resources. Yet, seabirds evolved sensorial abilities (olfactory senses) along with complex behaviours (social information transfer through local enhancement) to improve foraging efficiency. Using the Cory's shearwater (Calonectris borealis) as a model species, we developed an individual-based model to explore the complementary role of different searching mechanisms (olfactory foraging and local enhancement) for the optimal foraging behaviour of pelagic seabirds during 1-day foraging trips around breeding colonies. Model outputs were compared with observed patterns of Cory's shearwaters distribution during local foraging trips. Also, the foraging efficiency of virtual individuals was analysed considering hypothetical scenarios of foraging conditions and densities of foraging individuals around breeding colonies. The results support the use of a combination of searching strategies by Cory's shearwaters, which produced representative patterns of space use from tracked individuals, including spatial foraging segregation of neighbouring sub-colonies. Furthermore, while the mechanisms underpinning local enhancement played a key role in mitigating sub-optimal foraging conditions, the use of olfactory senses conferred great adaptive foraging advantages over a wide range of environmental conditions. Our results also indicate a synergistic effect between the two strategies, which suggests that a multimodal foraging strategy is useful to forage in extremely dynamic environments. The developed model provides a basis for further investigation regarding the role of foraging mechanisms in the population dynamics of colonial animals, including the adaptive foraging behaviour of marine top predators to dynamic environmental conditions.

Urbanisation and forest size affect the infestation rates of plant-galling arthropods and damage by herbivorous insects

Urbanisation is increasing globally and is considered to be a main driver of environmental change. Urbanisation-related factors include reduced habitat size and increased spatial isolation of the remaining habitats. As a consequence, the dynamics of plant and animal populations may change, which in turn might influence the quality and quantity of plant resources. Thus, urbanisation has the potential to disturb plant-animal interactions such as herbivory or galling. In the urban-rural setting of Basel (Switzerland), we aimed to assess whether the degree of urbanisation and forest size influence plant-galling infestation rates and leaf damage by mining and chewing arthropods on three tree species (sycamore, beech, and ash). We recorded species-specific responses to the degree of urbanisation and forest size. Gall infestation rate on sycamore leaves was affected by urbanisation but not by forest size. In contrast, gall infestation rates of beech gall midges responded sensitively to increasing urbanisation and decreasing forest size. The total leaf area damage caused by mining and chewing arthropods on sycamore was influenced by urbanisation and increased with increasing forest size. Leaf area damage by miners in beech tended to be affected by the degree of urbanisation, but not in ash. Urbanisation and forest size have the potential to alter herbivorous insect abundances. However, the effects depend on tree species and herbivore guild.

Unmanned aerial vehicle (UAV) survey of the Antarctic shag (Leucocarbo bransfieldensis) breeding colony at Harmony Point, Nelson Island, South Shetland Islands

Monitored seabird populations—useful sentinels of marine ecosystem health—have been declining worldwide at a rapid pace. Yet, lack of reliable long-term monitoring data constrains assessment of the conservation status of many seabird populations. Unmanned aerial vehicles (UAVs) have the potential to increase survey efficiency and count precision of seabird populations, especially where time constraints or inaccessible terrain, such as sea stacks, limit meaningful ground-based surveys. Furthermore, tremendous potential exists to combine fine-scale spatially integrated habitat mapping obtained from UAV images with occupancy to unravel how abiotic factors such as topography affect animal populations. In late December 2018, we used an UAV to create a georeferenced orthomosaic image and digital elevation model (DEM) from which we determined the size of the Antarctic shag (Leucocarbo bransfieldensis) breeding colony at Harmony Point, Nelson Island, South Shetland Islands. Our population estimate of 69 breeding pairs is approximately double that reported for the early 2000s and the highest count since the late 1980s. Most nests were located 10 to 20 m above sea level, on relatively shallow gradients that predominantly faced southeast. While it is difficult to compare historical ground-based counts with the UAV-derived estimates presented here, our new data provide robust baseline information for future monitoring of the colony population size using comparable survey methods. Our basic mapping of the topography of the breeding colony also highlights how UAV-derived habitat information can facilitate our understanding of the influence of landscape structure on animal population dynamics.

Phytochemicals Involved in Plant Resistance to Leporids and Cervids: a Systematic Review.

Non-nutritive phytochemicals (secondary metabolites and fibre) can influence plant resistance to herbivores and have ecological impacts on animal and plant population dynamics. A major hindrance to the ecological study of these phytochemicals is the uncertainty in the compounds one should measure, especially when limited by cost and expertise. With the underlying goal of identifying proxies of plant resistance to herbivores, we performed a systematic review of the effects of non-nutritive phytochemicals on consumption by leporids (rabbits and hares) and cervids (deer family). We identified 133 out of 1790 articles that fit our selection criteria (leporids = 33, cervids = 97, both herbivore types = 3). These articles cover 18 species of herbivores, on four continents. The most prevalent group of phytochemicals in the selected articles was phenolics, followed by terpenes for leporids and by fibre for cervids. In general, the results were variable but phenolic concentration seems linked with high resistance to both types of herbivores. Terpene concentration is also linked to high plant resistance; this relationship seems driven by total terpene content for cervids and specific terpenes for leporids. Tannins and fibre did not have a consistent positive effect on plant resistance. Because of the high variability in results reported and the synergistic effects of phytochemicals, we propose that the choice of chemical analyses must be tightly tailored to research objectives. While researchers pursuing ecological or evolutionary objectives should consider multiple specific analyses, researchers in applied studies could focus on a fewer number of specific analyses. An improved consideration of plant defence, based on meaningful chemical analyses, could improve studies of plant resistance and allow us to predict novel or changing plant-herbivore interactions.

Nature's dynamical complexity.

A large-scale, cross-taxa analysis reveals high nonlinearity and limited long-term predictability in the dynamics of animal populations.

Nonlinear population dynamics are ubiquitous in animals.

Nonlinear dynamics, where a change in the input is not proportional to a change in the output, are often found throughout nature, for example in biochemical kinetics. Because of the complex suite of interacting abiotic and biotic variables present in ecosystems, animal population dynamics are often thought to be driven in a nonlinear, state-dependent fashion. However, so far these have only been identified in model organisms and some natural systems. Here we show that nonlinear population dynamics are ubiquitous in nature. We use nonlinear forecasting to analyse 747 datasets of 228 species to find that insect population trends were highly nonlinear (74%), followed by mammals (58%), bony fish (49%) and birds (35%). This indicates that linear, equilibrium-based model assumptions may fail at predicting population dynamics across a wide range of animal taxa. We show that faster-reproducing animals are more likely to have nonlinear and high-dimensional dynamics, supporting past ecological theory. Lastly, only a third of time series were predictable beyond two years; therefore, the ability to predict animal population trends using these methods may be limited. Our results suggest that the complex dynamics necessary to cause regime shifts and other transitions may be inherent in a wide variety of animals.