From individual behavior to metapopulation dynamics: unifying the patchy population and classic metapopulation models

Spatially structured populations in patchy habitats show much variation in migration rate, from patchy populations in which individuals move repeatedly among habitat patches to classic metapopulations with infrequent migration among discrete populations. To establish a common framework for population dynamics in patchy habitats, we describe an individual-based model (IBM) involving a diffusion approximation of correlated random walk of individual movements. As an example, we apply the model to the Glanville fritillary butterfly (Melitaea cinxia) inhabiting a highly fragmented landscape. We derive stochastic patch occupancy model (SPOM) approximations for the IBMs assuming pure demographic stochasticity, uncorrelated environmental stochasticity, or completely correlated environmental stochasticity in local dynamics. Using realistic parameter values for the Glanville fritillary, we show that the SPOMs mimic the behavior of the IBMs well. The SPOMs derived from IBMs have parameters that relate directly to the life history and behavior of individuals, which is an advantage for model interpretation and parameter estimation. The modeling approach that we describe here provides a unified framework for patchy populations with much movements among habitat patches and classic metapopulations with infrequent movements.     

Correlations of daily activity with avian cholera mortality among wildfowl.

We tested the hypothesis that wildfowl activities can influence the risk of avian cholera (Pasteurella multocida infection) for susceptible birds at Centerville, Humboldt County, California (USA). Avian cholera mortality characteristics from past epizootics were correlated with variations in flock size, habitat use and 11 feeding and nonfeeding behaviors among six empirically defined groups of wildfowl: American coots (Fulica americana), tundra swans (Cygnus columbianus), American wigeon (Anas americana), northern pintails (A. acuta), northern shovelers (A. clypeata)/mallards (A. platyrhynchos), and teal (A. discors, A. crecca, A. cyanoptera). The position of these wildfowl groups in past mortality sequences was directly correlated with mean flock size, time spent on land, and time spent grazing on land or in shallow water. We propose that variations in bird density, habitat use and frequency of grazing may serve as predisposing factors to avian cholera among wildfowl.     

Information thresholds,habitat loss and population persistence in breeding birds

The combination of spatial structure and non‐linear population dynamics can promote the persistence of coupled populations, even when the average population growth rate of the patches seen in isolation would predict otherwise. This phenomenon has generally been conceptualized and investigated through the movement of individuals among patches that each holds many individuals, as in metapopulation models. However, population persistence can likewise increase as the result of individuals moving among sites (e.g. breeding territories) within in a single patch. Here I examine the latter: individuals making small‐scale informed decisions with respect to where to breed can promote population persistence in poor environments. Based on a simple algebraic model, I demonstrate information thresholds, and predict that greater information use is required for population persistence under lower spatial heterogeneity in habitat quality, all else equal. Second, I implement an individual‐based model to explore prior experience and prospecting on conspecific success within a more complex, and spatially heterogeneous environment. Uniquely, I jointly examine the effects of simulated habitat loss, spatial heterogeneity prior to habitat, and variation in information gathering on population persistence. I find that habitat loss accelerates population quasi‐extinction risk; however, information use reduces extinction probabilities in proportion to the level of information gathering. Per capita reproductive success declines with number of breeding sites, suggesting that information‐mediated Allee effects may contribute to extinction risk. In conclusion, my study suggests that populations in a changing world may be increasingly vulnerable to extinction where patch size and spatial heterogeneity constrain the effectiveness of information‐use strategies.     

Predicting the effect of disturbance on coastal birds

Assessments of whether disturbance is having a deleterious effect on populations have often measured behavioural responses to disturbance and assumed that populations with a larger behavioural response are more susceptible to disturbance. However, there is no guarantee that the behavioural response to disturbance is related to the population consequence, measured in terms of decreased reproduction or increased mortality. Individual-based models, consisting of fitness-maximizing individuals, are one means of linking the behavioural responses to disturbance to population consequences. This paper reviews how individual-based models have been used to predict the effect of disturbance on populations of shorebirds and wildfowl at several European sites, and shows how these models could be improved in the future by incorporating a range of alternative responses to disturbance.     

Searching for the fundamental niche using individual‐based habitat selection modelling across populations

Strictly speaking, fundamental niches are inestimable. Nevertheless, ecologists attempt approximating them to understand species’ distribution and plasticity to environmental changes, with invaluable repercussions on both theoretical and applied ecology. So far, individual‐based habitat selection models only characterized realized niches of populations delimited by physical (e.g. fences), historical (colonization) and biotic (competition) barriers constraining access to a subset of resources available to the species. As populations with different realized niches share the same fundamental niche, we developed a novel framework to scale‐up response curves from population‐scale habitat selection models to approximate the species’ optimal habitat choices, unbiased by barriers constraining accessibility. We used GPS‐locations from 147 wild mountain reindeer Rangifer t. tarandus, belonging to 7 of the remaining populations scattered throughout the subspecies’ range. We linked individual choices to accessible habitat features using conditional‐logistic regression with log‐link function in a use‐available design. Focal variables were modeled using 2nd degree polynomials on log‐scale, which correspond to a Gaussian curve used to approximate the fundamental niche optimum (curve mean) and breadth (variance). Using both real and simulated data we demonstrate that robust approximations of a fundamental niche optimum and breadth can be estimated using a relatively small number of representative populations with relatively few individuals. While each classical realized niche model had strong predictive power for the focal population but poorly predicted across populations, the approximation of the fundamental niche allowed for robust inter‐population comparisons in habitat quality. The proposed approach brings individual‐based habitat selection models forward along the continuum from investigating the realized niche of a population towards investigating a species’ fundamental niche, and allows us to quantify empirically the relationship between realized and fundamental niches. This allows improving the understanding of differences in fitness among populations, the prediction of species’ distributions and plasticity to environmental changes, and suggestions for mitigation priorities.     

Determinants of species‐area relationships for marsh‐nesting birds

ABSTRACT To clarify the underlying causes of the species‐area relationship in marsh‐nesting birds, I studied eight freshwater tidal marshes of the Connecticut River that differed in area, degree of isolation, mudflat cover, water cover, tidal regime, and extent of individual plant communities. I measured these habitat variables on aerial infrared photos, and surveyed bird populations by mapping the distribution of all birds in marshes under 5 ha in area and establishing 50‐m radius plots in marshes over 5 ha. From surveys, I determined species richness, population densities, and total populations. Analysis revealed a positive relationship between species richness and area, but no correlation between area and habitat heterogeneity. Other habitat variables were poor predictors of species richness. The lack of a relationship between habitat and species richness appeared to be a consequence of most vegetation types present not being sufficiently distinct for birds to differentially associate with them. I also found no relationship between bird population density and area, suggesting that habitat quality in marshes did not improve with increasing size, and species evenness declined with increasing richness because greater richness was associated with the presence of more rare species. Larger marshes had more rare species, species with larger populations, and species with a minimum threshold area for occurrence. Thus, my results are consistent with theoretical predictions that larger populations are less prone to local extinction and, as individuals are added to a community, more rare species are present.     

Estimating demographic models for the range dynamics of plant species

Aims To better understand how demographic processes shape the range dynamics of woody plants (in this case, Proteaceae), we introduce a likelihood framework for fitting process‐based models of range dynamics to spatial abundance data. Location The fire‐prone Fynbos biome (Cape Floristic Region, South Africa). Methods Our process‐based models have a spatially explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) as well as an observation submodel (describing imperfect detection of individuals), and are constrained by species‐specific predictions of habitat distribution models and process‐based models for seed dispersal by wind. Free model parameters were varied to find parameter sets with the highest likelihood. After testing this approach with simulated data, we applied it to eight Proteaceae species that differ in breeding system (monoecy versus dioecy) and adult fire survival. We assess the importance of Allee effects and negative density dependence for range dynamics, by using the Akaike information criterion to select between alternative models fitted for the same species. Results The best model for all dioecious study species included Allee effects, whereas this was true for only one of four monoecious species. As expected, sprouters (in which adults survive fire) were estimated to have lower rates of reproduction and catastrophic population extinction than related non‐sprouters. Overcompensatory population dynamics seem important for three of four non‐sprouters. We also found good quantitative agreement between independent data and most estimates of reproduction, carrying capacity and extinction probability. Main conclusions This study shows that process‐based models can quantitatively describe how large‐scale abundance distributions arise from the movement and interaction of individuals. It stresses links between the life history, demography and range dynamics of Proteaceae: dioecious species seem more susceptible to Allee effects which reduce migration ability and increase local extinction risk, and sprouters seem to have high persistence of established populations, but their low reproduction limits habitat colonization and migration.     

Understanding species distribution in dynamic populations: a new approach using spatio‐temporal point process models

Understanding and predicting a species’ distribution across a landscape is of central importance in ecology, biogeography and conservation biology. However, it presents daunting challenges when populations are highly dynamic (i.e. increasing or decreasing their ranges), particularly for small populations where information about ecology and life history traits is lacking. Currently, many modelling approaches fail to distinguish whether a site is unoccupied because the available habitat is unsuitable or because a species expanding its range has not arrived at the site yet. As a result, habitat that is indeed suitable may appear unsuitable. To overcome some of these limitations, we use a statistical modelling approach based on spatio‐temporal log‐Gaussian Cox processes. These model the spatial distribution of the species across available habitat and how this distribution changes over time, relative to covariates. In addition, the model explicitly accounts for spatio‐temporal dynamics that are unaccounted for by covariates through a spatio‐temporal stochastic process. We illustrate the approach by predicting the distribution of a recently established population of Eurasian cranes Grus grus in England, UK, and estimate the effect of a reintroduction in the range expansion of the population. Our models show that wetland extent and perimeter‐to‐area ratio have a positive and negative effect, respectively, in crane colonisation probability. Moreover, we find that cranes are more likely to colonise areas near already occupied wetlands and that the colonisation process is progressing at a low rate. Finally, the reintroduction of cranes in SW England can be considered a human‐assisted long‐distance dispersal event that has increased the dispersal potential of the species along a longitudinal axis in S England. Spatio‐temporal log‐Gaussian Cox process models offer an excellent opportunity for the study of species where information on life history traits is lacking, since these are represented through the spatio‐temporal dynamics reflected in the model.     

Partitioning within‐species variance in behaviour to within‐ and between‐population components for understanding evolution

Phenotypes vary at multiple hierarchical levels, of which the interspecific variance is the primary focus of phylogenetic comparative studies. However, the evolutionary role of particular within‐species variance components (between‐population, between‐ or within‐individual variances) remains neglected. Here, we partition the variance in an anti‐predator behaviour, flight initiation distance (FID), and assess how its within‐ and between‐population variance are related to life history, distribution, dispersal and habitat ecology. Although the composition of within‐species variance in FID depended on the phylogeny, most variance occurred within populations. When accounting for allometry, density‐dependence, uncertainty in the phylogenetic hypothesis and heterogeneity in data quality, within‐population variance was significantly associated with habitat diversity and population size. Between‐population variance was a significant predictor of natal dispersal, senescence and habitat diversity. Accordingly, not only species‐specific mean values of a behavioural trait, but also its variance within and among populations can shape the evolutionary ecology of species.     

Ensemble modeling to predict habitat suitability for a large‐scale disturbance specialist

To conserve habitat for disturbance specialist species, ecologists must identify where individuals will likely settle in newly disturbed areas. Habitat suitability models can predict which sites at new disturbances will most likely attract specialists. Without validation data from newly disturbed areas, however, the best approach for maximizing predictive accuracy can be unclear (Northwestern U.S.A.). We predicted habitat suitability for nesting Black‐backed Woodpeckers (Picoides arcticus; a burned‐forest specialist) at 20 recently (≤6 years postwildfire) burned locations in Montana using models calibrated with data from three locations in Washington, Oregon, and Idaho. We developed 8 models using three techniques (weighted logistic regression, Maxent, and Mahalanobis D² models) and various combinations of four environmental variables describing burn severity, the north–south orientation of topographic slope, and prefire canopy cover. After translating model predictions into binary classifications (0 = low suitability to unsuitable, 1 = high to moderate suitability), we compiled “ensemble predictions,” consisting of the number of models (0–8) predicting any given site as highly suitable. The suitability status for 40% of the area burned by eastside Montana wildfires was consistent across models and therefore robust to uncertainty in the relative accuracy of particular models and in alternative ecological hypotheses they described. Ensemble predictions exhibited two desirable properties: (1) a positive relationship with apparent rates of nest occurrence at calibration locations and (2) declining model agreement outside surveyed environments consistent with our reduced confidence in novel (i.e., “no‐analogue”) environments. Areas of disagreement among models suggested where future surveys could help validate and refine models for an improved understanding of Black‐backed Woodpecker nesting habitat relationships. Ensemble predictions presented here can help guide managers attempting to balance salvage logging with habitat conservation in burned‐forest landscapes where black‐backed woodpecker nest location data are not immediately available. Ensemble modeling represents a promising tool for guiding conservation of large‐scale disturbance specialists.     

Population Viability and Vital Rate Sensitivity of an Endangered Avian Cooperative Breeder,the White-Breasted Thrasher (Ramphocinclus brachyurus)

Social behaviors can significantly affect population viability, and some behaviors might reduce extinction risk. We used population viability analysis to evaluate effects of past and proposed habitat loss on the White-breasted Thrasher (Ramphocinclus brachyurus), a cooperatively breeding songbird with a global population size of <2000 individuals. We used an individual-based approach to build the first demographic population projection model for this endangered species, parameterizing the model with data from eight years of field study before and after habitat loss within the stronghold of the species’ distribution. The recent habitat loss resulted in an approximately 18% predicted decline in population size; this estimate was mirrored by a separate assessment using occupancy data. When mortality rates remained close to the pre-habitat loss estimate, quasi-extinction probability was low under extant habitat area, but increased with habitat loss expected after current plans for resort construction are completed. Post-habitat loss mortality rate estimates were too high for projected populations to persist. Vital rate sensitivity analyses indicated that population growth rate and population persistence were most sensitive to juvenile mortality. However, observed values for adult mortality were closest to the threshold value above which populations would crash. Adult mortality, already relatively low, may have the least capacity to change compared to other vital rates, whereas juvenile mortality may have the most capacity for improvement. Results suggest that improving mortality estimates and determining the cause(s) of juvenile mortality should be research priorities. Despite predictions that aspects of cooperative systems may result in variation in reproduction or juvenile mortality being the most sensitive vital rates, adult mortality was the most sensitive in half of the demographic models of other avian cooperative breeders. Interestingly, vital rate sensitivity differed by model type. However, studies that explicitly modeled the species’ cooperative breeding system found reproduction to be the most sensitive rate.     

Using nested clade analysis to assess the history of colonization and the persistence of populations of an Iberian Lizard

The distribution of the lizard Lacerta schreiberi is likely to have been severely affected by the climatic cycles that have influenced the Iberian Peninsula. Information about the species ecology and Iberian physiogeography was used to generate specific hypotheses about episodes of colonization and subsequent population persistence. These hypotheses generated predictions about the distribution of genetic variation, which were tested using nested clade analysis (NCA) supplemented by analysis of molecular variance (amova). Two predictions were confirmed by NCA; that is those that specified multiple and allopatric refugia. However, the remaining three predictions were not corroborated by the analyses. Firstly, a simple analysis of the distribution of genetic variability failed to detect an expected difference in the pattern of colonization between the inland mountain system and the coastal region. Moreover, while NCA did detect the expected genetic pattern in southern coastal populations, it was explained in terms of long-distance migration, which seems implausible because of the extent of unsuitable habitat. A more likely cause of the pattern is population fragmentation and a reduction in population size caused during the Holocene. Finally, NCA also failed to detect a northwestern population expansion, which is supported by other evidence. We conclude that NCA has a limited ability to detect range expansion led by individuals with more ancestral (interior) haplotypes.     

Predicting the population consequences of human disturbance for Ringed Plovers Charadrius hiaticula: a game theory approach

Human disturbance and its potential impacts upon bird populations are currently topical and contentious issues for conservationists. Although many studies have revealed a behavioural impact, or even direct effect on breeding success or survival, these cannot usually be extended to predict the impact on population size. Here we present a population model that allows predictions of the effect that changes in human numbers, visiting a 9-km-long section of the coastline, may have upon the size of a Ringed Plover Charadrius hiaticula population. Human disturbance affects Ringed Plovers in our study area through birds avoiding areas of high disturbance and, in addition, through the accidental trampling of a small number of nests by people walking on the beach. Using the level of human disturbance and habitat variables (which define territory quality) it is possible to predict which areas of beach are occupied and therefore the sites available to the population. Breeding success, for a given area of beach, can be predicted from habitat data. Incorporating known, density-independent, adult mortality allows the equilibrium population size to be predicted. This provides a model that predicts population size. This model is then used to predict the population that the site would support with different, hypothetical, levels of disturbance. If nest loss from human activity was prevented, for example by fencing nests, we predict the Plover population size would increase by 8%. A complete absence of human disturbance would cause a population increase of 85%. If the numbers of people were to double, we predict the population would decrease by 23%.     

Invasive plants: approaches and predictions

Successful management of invasive weeds will require active attempts to prevent new introductions, vigilant detection of nascent populations and persistent efforts to eradicate the worst invaders. To achieve these objectives, invasion ecology offers five groups of complementary approaches. (i) Stochastic approaches allow probabilistic predictions about potential invaders based on initial population size, residence time and number of introduction attempts. (ii) Empirical taxon‐specific approaches are based on previously documented invasions of particular taxa. (iii) Evaluations of the biological characters of non‐invasive taxa and successful invaders give rise either to general or to habitat‐specific screening procedures. (iv) Evaluation of environmental compatibility helps to predict whether a particular plant taxon can invade specific habitats. (v) Experimental approaches attempt to tease apart intrinsic and extrinsic factors underlying invasion success. An emerging theory of plant invasiveness based on biological characters has resulted in several rather robust predictions which are presented in this paper.     

Relationships between survival and habitat suitability of semi‐aquatic mammals

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche‐based species distribution models (SDMs) and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi‐aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30‐m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent‐predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability‐fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic SDMs incorporating local abundance and demographic rates are needed.     

Disease‐structured N‐mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark–recapture models can produce high‐quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark–recapture techniques. Recently developed N‐mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N‐mixture models are a type of state‐space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N‐mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease‐structured N‐mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.     

Bird behaviour and environmental planning: approaches in the study of wader populations

Predicting the effect of changes in land-use on bird populations requires a degree of understanding of their population dynamics which is seldom available. Such knowledge is especially difficult to acquire if the birds occupy a variety of habitats of differing quality and they are also migratory. The effects of habitat loss at a particular time of year on the year-round population dynamics are then difficult to predict. The problem is discussed using wintering waders as examples. Unless a species can extend its present range, the initial effect of habitat loss is to increase bird density. Whether this affects population size will depend on whether bird density affects either winter survival or subsequent breeding success. Measuring such density-dependent relationships is in practice extremely difficult in migratory populations. However, behavioural studies help in testing the key hypothesis that birth and death rates are affected by bird density, and may even allow the form of any density-dependent functions to be deduced. Simulation modelling then allows the effects of habitat loss on the overall population dynamics to be explored. The general point is that behavioural studies play an important part in Environmental Impact Studies because behaviour is the main way in which birds respond to environmental changes and compete for limited resources, such as diminishing habitat. They are therefore likely to provide insights when making predictions about the responses of birds and populations to habitat loss.     

Simple predictions of instream habitat model outputs for target fish populations

1. Bottom-up approaches based on individual behaviour can help to identify key variables influencing populations at larger scales. Instream habitat models have been developed to predict the consequences, for populations in stream reaches, of fish preferences for particular hydraulic conditions observed at the scale of individuals. Conventional instream habitat models (e.g. PHABSIM) predict habitat values for species or life stages in reaches, and their changes with discharge. Despite their worldwide use, they have been subject to continuing criticism and have been mainly limited to site-specific case studies.
2. We ran conventional instream habitat models in 58 French stream reaches dominated by brown trout. Using non-linear mixed effect models, we demonstrated that the outputs of instream habitat models (habitat values for three trout life stages and five other species) are predictable from average characteristics of reaches (discharge, depth, width and bed particle size).
3. Our models closely reflect variations in habitat values within-reaches (with discharge) and between-reaches. Within-reach changes are linked to the Reynolds number of reaches, while between-reach changes depend mainly on the Froude number at median daily discharge. These two dimensionless variables combine discharge, mean depth and mean width of reaches. Independent model validations showed robust model predictions that are consistent with studies of habitat values for brown trout made in larger streams from western North America.
4. Our results contribute to identifying the main hydraulic variables governing estimates of fish habitat values. They should facilitate habitat studies in multiple streams, at the basin or larger scales, while reducing their cost. They should enhance the biological validation of habitat model predictions, which remains critical.     

Climate change and coastal waterbird populations – past declines and future impacts

Considerable attention has been given to the impact of climate change on avian populations over the last decade. In this paper we examine two issues with respect to coastal bird populations in the UK: (1) is there any evidence that current populations are declining due to climate change, and (2) how might we predict the response of populations in the future? We review the cause of population decline in two species associated with saltmarsh habitats. The abundance of Common Redshank Tringa totanus breeding on saltmarsh declined by about 23% between the mid-1980s and mid-1990s, but the decline appears to have been caused by an increase in grazing pressure. The number of Twite Carduelis flavirostris wintering on the coast of East Anglia has declined dramatically over recent decades; there is evidence linking this decline with habitat loss but a causal role for climate change is unclear. These examples illustrate that climate change could be having population-level impacts now, but also show that it is dangerous to become too narrowly focused on single issues affecting coastal birds. Making predictions about how populations might respond to future climate change depends on an adequate understanding of important ecological processes at an appropriate spatial scale. We illustrate this with recent work conducted on the Icelandic population of Black-tailed Godwits Limosa limosa islandica that shows large-scale regulatory processes. Most predictive models to date have focused on local populations (single estuary or a group of neighbouring estuaries). We discuss the role such models might play in risk assessment, and the need for them to be linked to larger-scale ecological processes. We argue that future work needs to focus on spatial scale issues and on linking physical models of coastal environments with important ecological processes.