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The subject of investigating causation in ecology has been widely discussed in recent years, especially by advocates of a structural causal model (SCM) approach. Some of these advocates have criticized the use of predictive models and model selection for drawing inferences about causation. We argue that the comparison of model-based predictions with observations is a key step in hypothetico-deductive (H-D) science and remains a valid approach for assessing causation. We draw a distinction between two approaches to inference based on predictive modeling. The first approach is not guided by causal hypotheses and focuses on the relationship between a (typically) single response variable and a potentially large number of covariates. We agree that this approach does not yield useful inferences about causation and is primarily useful for hypothesis generation. The second approach follows a H-D framework and is guided by specific hypotheses about causal relationships. We believe that this has been, and continues to be, a useful approach to causal inference. Here, we first define different kinds of causation, arguing that a "probability-raisers-of-processes" definition is especially appropriate for many ecological systems. We outline different scientific "designs" for generating the observations used to investigate causation. We briefly outline some relevant components of the SCM and H-D approaches to investigating causation, emphasizing a H-D approach that focuses on modeling causal effects on vital rate (e.g., rates of survival, recruitment, local extinction, colonization) parameters underlying system dynamics. We consider criticisms of predictive modeling leveled by some SCM proponents and provide two example analyses of ecological systems that use predictive modeling and avoid these criticisms. We conclude that predictive models have been, and can continue to be, useful for providing inferences about causation., (© 2025 The Ecological Society of America. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Although long-distance migratory songbirds are widely believed to be at risk from warming temperature trends, species capable of attempting more than one brood in a breeding season could benefit from extended breeding seasons in warmer springs. To evaluate local and global factors affecting population dynamics of the black-throated blue warbler (Setophaga caerulescens), a double-brooded long-distance migrant, we used Pradel models to analyze 25 years of mark-recapture data collected in New Hampshire, USA. We assessed the effects of spring temperature (local weather) and the El Niño Southern Oscillation index (a global climate cycle), as well as predator abundance, insect biomass, and local conspecific density on population growth in the subsequent year. Local and global climatic conditions affected warbler populations in different ways. We found that warbler population growth was lower following El Niño years (which have been linked to poor survival in the wintering grounds and low fledging weights in the breeding grounds) than La Niña years. At a local scale, populations increased following years with warm springs and abundant late-season food, but were unaffected by spring temperature following years when food was scarce. These results indicate that the warming temperature trends might have a positive effect on recruitment and population growth of black-throated blue warblers if food abundance is sustained in breeding areas. In contrast, potential intensification of future El Niño events could negatively impact vital rates and populations of this species., (© 2015 John Wiley & Sons Ltd.)

Forest degradation is arguably the greatest threat to biodiversity, ecosystem services, and rural livelihoods. Therefore, increasing understanding of how organisms respond to degradation is essential for management and conservation planning. We were motivated by the need for rapid and practical analytical tools to assess the influence of management and degradation on biodiversity and system state in areas subject to rapid environmental change. We compared bird community composition and size in managed (ejido, i.e., communally owned lands) and unmanaged (national park) forests in the Sierra Tarahumara region, Mexico, using multispecies occupancy models and data from a 2-year breeding bird survey. Unmanaged sites had on average higher species occupancy and richness than managed sites. Most species were present in low numbers as indicated by lower values of detection and occupancy associated with logging-induced degradation. Less than 10% of species had occupancy probabilities >0.5, and degradation had no positive effects on occupancy. The estimated metacommunity size of 125 exceeded previous estimates for the region, and sites with mature trees and uneven-aged forest stand characteristics contained the highest species richness. Higher estimation uncertainty and decreases in richness and occupancy for all species, including habitat generalists, were associated with degraded young, even-aged stands. Our findings show that multispecies occupancy methods provide tractable measures of biodiversity and system state and valuable decision support for landholders and managers. These techniques can be used to rapidly address gaps in biodiversity information, threats to biodiversity, and vulnerabilities of species of interest on a landscape level, even in degraded or fast-changing environments. Moreover, such tools may be particularly relevant in the assessment of species richness and distribution in a wide array of habitats., (© 2014 Society for Conservation Biology.)

Nesting migratory geese are among the dominant herbivores in (sub) arctic environments, which have undergone unprecedented increases in temperatures and plant growing days over the last three decades. Within these regions, the Hudson Bay Lowlands are home to an overabundant breeding population of lesser snow geese that has dramatically damaged the ecosystem, with cascading effects at multiple trophic levels. In some areas the overabundance of geese has led to a drastic reduction in available forage. In addition, warming of this region has widened the gap between goose migration timing and plant green-up, and this 'mismatch' between goose and plant phenologies could in turn affect gosling development. The dual effects of climate change and habitat quality on gosling body condition and juvenile survival are not known, but are critical for predicting population growth and related degradation of (sub) arctic ecosystems. To address these issues, we used information on female goslings marked and measured between 1978 and 2005 (4125 individuals). Goslings that developed within and near the traditional center of the breeding colony experienced the effects of long-term habitat degradation: body condition and juvenile survival declined over time. In newly colonized areas, however, we observed the opposite pattern (increase in body condition and juvenile survival). In addition, warmer than average winters and summers resulted in lower gosling body condition and first-year survival. Too few plant 'growing days' in the spring relative to hatch led to similar results. Our assessment indicates that geese are recovering from habitat degradation by moving to newly colonized locales. However, a warmer climate could negatively affect snow goose populations in the long-run, but it will depend on which seasons warm the fastest. These antagonistic mechanisms will require further study to help predict snow goose population dynamics and manage the trophic cascade they induce., (© 2012 Blackwell Publishing Ltd.)

Population control through harvest has the potential to reduce the abundance of nuisance and invasive species. However, demographic structure and density-dependent processes can confound removal efforts and lead to undesirable consequences, such as overcompensation (an increase in abundance in response to harvest) and instability (population cycling or chaos). Recent empirical studies have demonstrated the potential for increased mortality (such as that caused by harvest) to lead to overcompensation and instability in plant, insect, and fish populations. We developed a general population model with juvenile and adult stages to help determine the conditions under which control harvest efforts can produce unintended outcomes. Analytical and simulation analyses of the model demonstrated that the potential for overcompensation as a result of harvest was significant for species with high fecundity, even when annual stage-specific survivorship values were fairly low. Population instability as a result of harvest occurred less frequently and was only possible with harvest strategies that targeted adults when both fecundity and adult survivorship were high. We considered these results in conjunction with current literature on nuisance and invasive species to propose general guidelines for assessing the risks associated with control harvest based on life history characteristics of target populations. Our results suggest that species with high per capita fecundity (over discrete breeding periods), short juvenile stages, and fairly constant survivorship rates are most likely to respond undesirably to harvest. It is difficult to determine the extent to which overcompensation and instability could occur during real-world removal efforts, and more empirical removal studies should be undertaken to evaluate population-level responses to control harvests. Nevertheless, our results identify key issues that have been seldom acknowledged and are potentially generic across taxa.

Investigations of disease dynamics in wild animal populations often use estimated prevalence or incidence as a measure of true disease frequency. Such indices, almost always based solely on raw counts of infected and uninfected individuals, are often used as the basis for analysis of temporal and spatial dynamics of diseases. Generally, such studies do not account for potential differences in observer detection probabilities of host individuals stratified by biotic and/or abiotic factors. We demonstrate the potential effects of heterogeneity in state-specific detection probabilities on estimated disease prevalence using mark-recapture data from previous work in a House Finch (Carpodacus mexicanus) and Mycoplasma gallisepticum system. In this system, detection probabilities of uninfected finches were generally higher than infected individuals. We show that the magnitude and seasonal pattern of variation in estimated prevalence, corrected for differences in detection probabilities, differed markedly from uncorrected (apparent) prevalence. When the detection probability of uninfected individuals is higher than infected individuals (as in our study), apparent prevalence is negatively biased, and vice versa. In situations where state-specific detection probabilities strongly interact over time, we show that the magnitude and pattern of apparent prevalence can change dramatically; in such cases, observed variations in prevalence may be completely spurious artifacts of variation in detection probability, rather than changes in underlying disease dynamics. Accounting for differential detection probabilities in estimates of disease frequency removes a potentially confounding factor in studies seeking to identify biotic and/or abiotic drivers of disease dynamics. Given that detection probabilities of different groups of individuals are likely to change temporally and spatially in most field studies, our results underscore the importance of estimating and incorporating detection probabilities in estimated disease prevalence (specifically), and more generally, any ecological index used to estimate some parameter of interest. While a mark-recapture approach makes it possible to estimate detection probabilities, it is not always practical, especially at large scales. We discuss several alternative approaches and categorize the assumptions under which analysis of uncorrected prevalence may be acceptable.

In early 1994, a novel strain of Mycoplasma gallisepticum (MG)--a poultry pathogen with a world-wide distribution--emerged in wild house finches and within 3 years had reached epidemic proportions across their eastern North American range. The ensuing epizootic resulted in a rapid decline of the host population coupled with considerable seasonal fluctuations in prevalence. To understand the dynamics of this disease system, a multi-disciplinary team composed of biologists, veterinarians, microbiologists and mathematical modelers set forth to determine factors driving and influenced by this host-pathogen system. On a broad geographic scale, volunteer observers ("citizen scientists") collected and reported data used for calculating both host abundance and disease prevalence. The scale at which this monitoring initiative was conducted is unprecedented and it has been an invaluable source of data for researchers at the Cornell Laboratory of Ornithology to track the spread and magnitude of disease both spatially and temporally. At a finer scale, localized and intensive field studies provided data used to quantify the effects of disease on host demographic parameters via capture-mark-recapture modeling, effects of host behavior on disease and vice-versa, and the biological and genetic profiles of birds with known phenotypic characteristics. To balance the field-based component of the study, experiments were conducted with finches held in captivity to describe and quantify the effects of experimental infections on hosts in both individual and social settings. The confluence of these various elements of the investigation provided the foundation for construction of a general compartmentalized epidemiological model of the dynamics of the house finch-MG system. This paper serves several purposes including (i) a basic review of the pathogen, host, and epidemic cycle; (ii) an explanation of our research strategy; (iii) a basic review of results from the diverse multi-disciplinary approaches employed; and (iv) pertinent questions relevant to this and other wildlife disease studies that require further investigation.

We investigated the influence of age on survival and breeding rates in a long-lived species Rissa tridactyla using models with individual random effects permitting variation and covariation in fitness components among individuals. Differences in survival or breeding probabilities among individuals are substantial, and there was positive covariation between survival and breeding probability; birds that were more likely to survive were also more likely to breed, given that they survived. The pattern of age-related variation in these rates detected at the individual level differed from that observed at the population level. Our results provided confirmation of what has been suggested by other investigators: within-cohort phenotypic selection can mask senescence. Although this phenomenon has been extensively studied in humans and captive animals, conclusive evidence of the discrepancy between population-level and individual-level patterns of age-related variation in life-history traits is extremely rare in wild animal populations. Evolutionary studies of the influence of age on life-history traits should use approaches differentiating population level from the genuine influence of age: only the latter is relevant to theories of life-history evolution. The development of models permitting access to individual variation in fitness is a promising advance for the study of senescence and evolutionary processes.

Pharyngeal swabs were collected from 298 lesser snow geese (Chen caerulescens caerulescens) at Banks Island (Northwest Territories. Canada) in the summer of 1994. Pasteurella multocida serotype 1 was isolated from an adult male bird and P. multocida serotype 3 was isolated from an adult female goose. Pathogenicity of the serotype 1 isolate was confirmed by inoculation in Pekin ducks (Anas platyrhynchos). The serotype 3 isolate was non-pathogenic in Pekin ducks. This is the first documented isolation of pathogenic P. multocida serotype 1 from apparently healthy wild snow geese.

The consequences of philopatric and dispersal behaviours under changing environmental conditions were examined using data from the colony of Lesser Snow Geese (Anser caerulescens caerulescens) breeding at La Pérouse Bay, Manitoba, Canada. In response to increased population size and decreased food abundance over time, increasing numbers of family groups have been dispersing from the traditional feeding areas. Goslings from dispersed broods were significantly heavier (7.3%), and had longer culmens (3.1%), head lengths (2.6%) and marginally longer tarsi (1.9%) on average than goslings that remained within La Pérouse Bay itself. These differences were consistent in each of 5 years. There was no evidence that the larger size of dispersed goslings was due to either a tendency for larger adults to disperse to alternative sites, or increased mortality of smaller goslings among dispersed broods. The most likely cause for the larger size of goslings from dispersed broods was the significantly greater per capita availability of the preferred salt-marsh forage species at non-traditional brood-rearing areas. The larger goslings in non-traditional feeding areas showed significantly higher firstyear survival, suggesting that the use of deteriorating traditional feeding areas may currently be maladaptive in this population.