A multispecies test of source–sink indicators to prioritize habitat for declining populations

For species at risk of decline or extinction in source–sink systems, sources are an obvious target for habitat protection actions. However, the way in which source habitats are identified and prioritized can reduce the effectiveness of conservation actions. Although sources and sinks are conceptually defined using both demographic and movement criteria, simplifications are often required in systems with limited data. To assess the conservation outcomes of alternative source metrics and resulting prioritizations, we simulated population dynamics and extinction risk for 3 endangered species. Using empirically based habitat population models, we linked habitat maps with measured site‐ or habitat‐specific demographic conditions, movement abilities, and behaviors. We calculated source–sink metrics over a range of periods of data collection and prioritized consistently high‐output sources for conservation. We then tested whether prioritized patches identified the habitats that most affected persistence by removing them and measuring the population response. Conservation decisions based on different source–sink metrics and durations of data collection affected species persistence. Shorter time series obscured the ability of metrics to identify influential habitats, particularly in temporally variable and slowly declining populations. Data‐rich source–sink metrics that included both demography and movement information did not always identify the habitats with the greatest influence on extinction risk. In some declining populations, patch abundance better predicted influential habitats for short‐term regional persistence. Because source–sink metrics (i.e., births minus deaths; births and immigrations minus deaths and emigration) describe net population conditions and cancel out gross population counts, they may not adequately identify influential habitats in declining populations. For many nonequilibrium populations, new metrics that maintain the counts of individual births, deaths, and movement may provide additional insight into habitats that most influence persistence.     

A model for behavioral regulation of metapopulation dynamics

Habitat fragmentation can decrease local population persistence by reducing connectivity, which is a function of dispersal of individuals among habitat fragments. Dispersal is often treated as diffusion in population models, even though for many species it is a result of a series of behavioral decisions. We developed a metapopulation model to explore the potential importance of dispersal behaviors in driving metapopulation dynamics. We incorporated types of behavior that affect dispersal—colonization inhibiting, colonization enhancing, extinction inhibiting, extinction enhancing, rescue enhancing, rescue inhibiting—into Levins’ (1969) metapopulation model and projected occupancy rates for a variety of parameter values. Examples from the literature of behaviors associated with each of these parameters are provided. Our model simplifies into previously published metapopulation models that incorporate only a single behavior, and we present a density-dependent rescue function that leads to multiple non-zero equilibria. We found a variety of behavioral effects on metapopulations. Rescue enhancement fills patches faster than does colonization enhancement or extinction inhibition, and declines in patch occupancy are moderate with extinction enhancement, but colonization inhibition causes metapopulation extinction. We also found that with colonization and extinction inhibitions, equilibrium patch occupancy is inversely related to patch turnover rate. With density-dependent rescue, persistence depends not only on the strength of the strong rescue effect, but also on having a sufficient initial fraction of patches occupied; the stronger the rescue effect, the lower this fraction can be. This study suggests that dispersal behavior can have strong influences on metapopulation dynamics. It confirms the importance of understanding the relationship between landscape structure and dispersal behavior in understanding population persistence.     

A robust-design formulation of the incidence function model of metapopulation dynamics applied to two species of rails

The incidence function model (IFM) uses area and connectivity to predict metapopulation dynamics. However, false absences and missing data can lead to underestimates of the number of sites contributing to connectivity, resulting in overestimates of dispersal ability and turnovers (extinctions plus colonizations). We extend estimation methods for the IFM by using a hierarchical Bayesian model to account both for false absences due to imperfect detection and for missing data due to sites not surveyed in some years. We compare parameter estimates, measures of metapopulation dynamics, and forecasts using stochastic patch occupancy models (SPOMs) among three IFM models: (1) a Bayesian formulation assuming no false absences and omitting site-year combinations with missing data; (2) a hierarchical Bayesian formulation assuming no false absences but incorporating missing data; and (3) a hierarchical Bayesian formulation allowing for imperfect detection and incorporating missing data. We fit the models to multiyear data sets of occupancy for two bird species that differ in body size and presumed dispersal ability but inhabit the same network of sites: the small Black Rail (Laterallus jamaicensis) and the medium-sized Virginia Rail (Rallus limicola). Incorporating missing data affected colonization parameters and led to lower estimates of dispersal ability for the Black Rail. Detection rates were high for the Black Rail in most years but moderate for the Virginia Rail. Incorporating imperfect detection resulted in higher occupancy and lower turnover rates for both species, with largest effects for the Virginia Rail. Forecasts using SPOMs were sensitive to both missing data and false absences; persistence in models assuming no false absences was more optimistic than from robust models. Our results suggest that incorporating false absences and missing data into the IFM can improve (1) estimates of dispersal ability and the effect of connectivity on colonization, (2) the scaling of extinction risk with patch area, and (3) forecasts of occupancy and turnover rates.     

Effects of protected areas on survival of threatened gibbons in China

Establishing protected areas (PAs) is an essential strategy to reduce biodiversity loss. However, many PAs do not provide adequate protection due to poor funding, inadequate staffing and equipment, and ineffective management. As part of China's recent economic growth, the Chinese government has significantly increased investment in nature reserves over the past 20 years, providing a unique opportunity to evaluate whether PAs can protect threatened species effectively. We compiled data from published literature on populations of gibbons (Hylobatidae), a threatened taxon with cultural significance, that occurred in Chinese reserves after 1980. We evaluated the ability of these PAs to maintain gibbon habitat and populations by comparing forest cover and human disturbance between reserves and their surrounding areas and modeling the impact of reserve characteristics on gibbon population trends. We also assessed the perspective of reserve staff concerning PA management effectiveness through an online survey. Reserves effectively protected gibbon habitat by reducing forest loss and human disturbance; however, half the reserves lost their gibbon populations since being established. Gibbons were more likely to survive in reserves established more recently, at higher elevation, with less forest loss and lower human impact, and that have been relatively well studied. A larger initial population size in the 1980s was positively associated with gibbon persistence. Although staff of all reserves reported increased investment and improved management over the past 20–30 years, no relationship was found between management effectiveness and gibbon population trends. We suggest early and emphatic intervention is critical to stop population decline and prevent extinction.     

Population Persistence in Florida Torreya: Comparing Modeled Projections of a Declining Coniferous Tree

Abstract: The Florida torreya (   Torreya taxifolia ) is a coniferous tree endemic to a 35-km stretch of bluffs and ravines along the east side of the Apalachicola River in northern Florida and southern Georgia. This formerly locally abundant tree has declined as a result of disease during the 1950s and is on the U.S. endangered species list. With no seed production in the wild, this species is headed toward extinction. We conducted a survey on roughly 200 trees from 1988 to 1996 and used these data to estimate the likelihood of population persistence during the next several decades. We compared a stage-class transition matrix model ( RAMAS) and an individual-based stochastic model ( TORSIM) of growth and mortality to project future populations. Given the current lack of seed production in the wild, all models predict extinction. The question of concern is the imminence of this predicted extinction. Differing predicted times to extinction would suggest different immediate management recommendations. Both models predicted an over 90% likelihood of persistence during the next 50 years. Predictions differed in that the transition matrix model was less optimistic than the individual-based model regarding persistence. Model sensitivity analysis showed that the results were robust to significant decreases in growth and sprouting probabilities. Submodels identified different persistence likelihoods in different populations. Nonetheless, unless management of the population can facilitate maturation and seed production, extinction of this species in the wild is inevitable.     

Divergence in sink contributions to population persistence

Population sinks present unique conservation challenges. The loss of individuals in sinks can compromise persistence; but conversely, sinks can improve viability by improving connectivity and facilitating the recolonization of vacant sources. To assess the contribution of sinks to regional population persistence of declining populations, we simulated source–sink dynamics for 3 very different endangered species: Black‐capped Vireos (Vireo atricapilla) at Fort Hood, Texas, Ord's kangaroo rats (Dipodomys ordii) in Alberta, and Northern Spotted Owls (Strix occidentalis caurina) in the northwestern United States. We used empirical data from these case studies to parameterize spatially explicit individual‐based models. We then used the models to quantify population abundance and persistence with and without long‐term sinks. The contributions of sink habitats varied widely. Sinks were detrimental, particularly when they functioned as strong sinks with few emigrants in declining populations (e.g., Alberta's Ord's kangaroo rat) and benign in robust populations (e.g., Black‐capped Vireos) when Brown‐headed Cowbird (Molothrus ater) parasitism was controlled. Sinks, including ecological traps, were also crucial in delaying declines when there were few sources (e.g., in Black‐capped Vireo populations with no Cowbird control). Sink contributions were also nuanced. For example, sinks that supported large, variable populations were subject to greater extinction risk (e.g., Northern Spotted Owls). In each of our case studies, new context‐dependent sinks emerged, underscoring the dynamic nature of sources and sinks and the need for frequent re‐assessment. Our results imply that management actions based on assumptions that sink habitats are generally harmful or helpful risk undermining conservation efforts for declining populations.     

Natural Die-Offs of Large Mammals: Implications for Conservation

The viability of populations is a central concern of biological conservation. The occurrence of catastrophic die-offs may greatly reduce the long-term viability of populations. Theoretical extinction models and viability analyses require information on the frequency of die-offs and on the distribution of die-off severities. A review of literature identified 96 natural die-offs in large mammal populations, with a die-off being defined as a peak-to-trough decline in estimated population numbers of at least 25%. If such die-offs are common, population viability analyses that ignore them may be overly optimistic. The severities of the natural die-offs of large mammals presented here are not uniformly distributed. There is a relative overabundance of die-offs in the 70–90% range, and an underabundance of die-offs greater than 90%. This may indicate the presence of buffers against population extinction. The reported causes of large mammal die-offs were significantly related to trophic level: herbivore die-offs were more often attributed to starvation, while carnivore die-offs were more often attributed to disease. Populations subject to large-scale phenomena such as drought and severe winters may not be protected from die-offs by population subdivision. On the other hand, populations subject to catastrophic disease epidemics may be protected by subdivision, and threatened by corridors between conservation areas and by translocation efforts.     

A novel holistic framework for genetic‐based captive‐breeding and reintroduction programs

Research in reintroduction biology has provided a greater understanding of the often limited success of species reintroductions and highlighted the need for scientifically rigorous approaches in reintroduction programs. We examined the recent genetic‐based captive‐breeding and reintroduction literature to showcase the underuse of the genetic data gathered. We devised a framework that takes full advantage of the genetic data through assessment of the genetic makeup of populations before (past component of the framework), during (present component), and after (future component) captive‐breeding and reintroduction events to understand their conservation potential and maximize their success. We empirically applied our framework to two small fishes: Yarra pygmy perch (Nannoperca obscura) and southern pygmy perch (Nannoperca australis). Each of these species has a locally adapted and geographically isolated lineage that is endemic to the highly threatened lower Murray–Darling Basin in Australia. These two populations were rescued during Australia's recent decade‐long Millennium Drought, when their persistence became entirely dependent on captive‐breeding and subsequent reintroduction efforts. Using historical demographic analyses, we found differences and similarities between the species in the genetic impacts of past natural and anthropogenic events that occurred in situ, such as European settlement (past component). Subsequently, successful maintenance of genetic diversity in captivity—despite skewed brooder contribution to offspring—was achieved through carefully managed genetic‐based breeding (present component). Finally, genetic monitoring revealed the survival and recruitment of released captive‐bred offspring in the wild (future component). Our holistic framework often requires no additional data collection to that typically gathered in genetic‐based breeding programs, is applicable to a wide range of species, advances the genetic considerations of reintroduction programs, and is expected to improve with the use of next‐generation sequencing technology.     

Episodic death across species of desert shrubs

Extreme events shape population and community trajectories. We report episodic mortality across common species of thousands of long-lived perennials individually tagged and monitored for 20 years in the Colorado Desert of California following severe regional drought. Demographic records from 1984 to 2004 show 15 years of virtual stasis in populations of adult shrubs and cacti, punctuated by a 55-100% die-off of six of the seven most common perennial species. In this episode, adults that experienced reduced growth in a lesser drought during 1984-1989 failed to survive the drought of 2002. The significance of this event is potentially profound because population dynamics of long-lived plants can be far more strongly affected by deaths of adults, which in deserts potentially live for centuries, than by seedling births or deaths. Differential mortality and rates of recovery during and after extreme climatic events quite likely determine the species composition of plant and associated animal communities for at least decades. The die-off recorded in this closely monitored community provides a unique window into the mechanics of this process of species decline and replacement.     

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

Area-based assessment of extinction risk

Underpinning the International Union for Conservation of Nature (IUCN) Red List is the assessment of extinction risk as determined by the size and degree of loss of populations. The IUCN system lists a species as Critically Endangered, Endangered, or Vulnerable if its population size declines 80%, 50%, or 30% within a given time frame. However, effective implementation of the system faces substantial challenges and uncertainty because geographic scale data on population size and long-term dynamics are scarce. I develop a model to quantify extinction risk using a measure based on a species' distribution, a much more readily obtained quantity. The model calculates the loss of the area of occupancy that is equivalent to the loss of a given proportion of a population. It is a very simple yet general model that has no free parameters and is independent of scale. The model predicted well the distributions of 302 tree species at a local scale and the distributions of 348 species of North American land birds. This area-based model provides a solution to the long-standing problem for IUCN assessments of lack of data on population sizes, and thus it will contribute to facilitating the quantification of extinction risk worldwide.     

Accuracy of Short‐Term Demographic Data in Projecting Long‐Term Fate of Populations

Short‐term surveys are useful in conservation of species if they can be used to reliably predict the long‐term fate of populations. However, statistical evaluations of reliability are rare. We studied how well short‐term demographic data (1999–2002) of tartar catchfly (Silene tatarica), a perennial riparian plant, projected the fate and growth of 23 populations of this species up to the year 2010. Surveyed populations occurred along a river with natural flood dynamics and along a regulated river. Riparian plant populations are affected by flooding, which maintains unvegetated shores, while forest succession proceeds in areas with little flooding. Flooding is less severe along the regulated river, and vegetation overgrowth reduces abundance of tartar catchfly on unvegetated shores. We built matrix models to calculate population growth rates and estimated times to population extinction in natural and in regulated rivers, 13 and 10 populations, respectively. Models predicted population survival well (model predictions matched observed survival in 91% of populations) and accurately predicted abundance increases and decreases in 65% of populations. The observed and projected population growth rates differed significantly in all but 3 populations. In most cases, the model overestimated population growth. Model predictions did not improve when data from more years were used (1999–2006). In the regulated river, the poorest model predictions occurred in areas where cover of other plant species changed the fastest. Although vegetation cover increased in most populations, it decreased in 4 populations along the natural river. Our results highlight the need to combine disturbance and succession dynamics in demographic models and the importance of habitat management for species survival along regulated rivers. Precisión de Datos Demográficos de Corto Plazo en la Proyección del Destino de Poblaciones a Largo Plazo     

Planning for ex situ conservation in the face of uncertainty

Ex situ conservation strategies for threatened species often require long‐term commitment and financial investment to achieve management objectives. We present a framework that considers the decision to adopt ex situ management for a target species as the end point of several linked decisions. We used a decision tree to intuitively represent the logical sequence of decision making. The first decision is to identify the specific management actions most likely to achieve the fundamental objectives of the recovery plan, with or without the use of ex‐situ populations. Once this decision has been made, one decides whether to establish an ex situ population, accounting for the probability of success in the initial phase of the recovery plan, for example, the probability of successful breeding in captivity. Approaching these decisions in the reverse order (attempting to establish an ex situ population before its purpose is clearly defined) can lead to a poor allocation of resources, because it may restrict the range of available decisions in the second stage. We applied our decision framework to the recovery program for the threatened spotted tree frog (Litoria spenceri) of southeastern Australia. Across a range of possible management actions, only those including ex situ management were expected to provide >50% probability of the species’ persistence, but these actions cost more than use of in situ alternatives only. The expected benefits of ex situ actions were predicted to be offset by additional uncertainty and stochasticity associated with establishing and maintaining ex situ populations. Naïvely implementing ex situ conservation strategies can lead to inefficient management. Our framework may help managers explicitly evaluate objectives, management options, and the probability of success prior to establishing a captive colony of any given species.     

Long-term drivers of persistence and colonization dynamics in spatially structured amphibian populations

Many organisms live in networks of local populations connected by dispersing individuals, called spatially structured populations (SSPs), where the long-term persistence of the entire network is determined by the balance between 2 processes acting at the scale of local populations: extinction and colonization. When multiple threats act on an SSP, a comparison of the different factors determining local extinctions and colonizations is essential to plan sound conservation actions. We assessed the drivers of long-term population dynamics of multiple amphibian species at the regional scale. We used dynamic occupancy models within a Bayesian framework to identify the factors determining persistence and colonization of local populations. Because connectivity among patches is fundamental to SSPs dynamics, we considered 2 measures of connectivity acting on each focal patch: incidence of the focal species and incidence of invasive crayfish. We used meta-analysis to summarize the effect of different drivers at the community level. Persistence and colonization of local populations were jointly determined by factors acting at different scales. Persistence probability was positively related to the area and the permanence of wetlands, whereas it was negatively related to occurrence of fish. Colonization probability was highest in semipermanent wetlands and in sites with a high incidence of the focal species in nearby sites, whereas it showed a negative relationship with the incidence of invasive crayfish in the landscape. By analyzing long-term data on amphibian population dynamics, we found a strong effect of some classic features commonly used in SSP studies, such as patch area and focal species incidence. The presence of an invasive non-native species at the landscape scale emerged as one of the strongest drivers of colonization dynamics, suggesting that studies on SSPs should consider different connectivity measures more frequently, such as the incidence of predators, especially when dealing with biological invasions.     

Metapopulation dynamics in the butterfly Hipparchia semele changed decades before occupancy declined in The Netherlands

The survival of many species in human-dominated, fragmented landscapes depends on metapopulation dynamics, i.e., on a dynamic equilibrium of extinctions and colonizations in patches of suitable habitat. To understand and predict distributional changes, knowledge of these dynamics can be essential, and for this, metapopulation studies are preferably based on long-time-series data from many sites. Alas, such data are very scarce. An alternative is to use opportunistic data (i.e., collected without applying standardized field methods), but these data suffer from large variations in field methods and search intensity between sites and years. Dynamic site-occupancy models offer a general approach to adjust for variable survey effort. These models extend classical metapopulation models to account for imperfect detection of species and yield estimates of the probabilities of occupancy, colonization, and survival of species at sites. By accounting for detection, they fully correct for among-year variability in search effort. As an illustration, we fitted a dynamic site-occupancy model to 60 years of presence-absence data (more precisely, detection-nondetection) of the heathland butterfly Hipparchia semele in The Netherlands. Detection records were obtained from a database containing volunteer-based data from 1950-2009, and nondetection records were deduced from database records of other butterfly species. Our model revealed that metapopulation dynamics of Hipparchia had changed decades before the species' distribution began to contract. Colonization probability had already started to decline from 1950 onward, but this was counterbalanced by an increase in the survival of existing populations, the result of which was a stable distribution. Only from 1990 onward was survival not sufficient to compensate for the further decrease of colonization, and occupancy started to decline. Hence, it appears that factors acting many decades ago triggered a change in the metapopulation dynamics of this species, which ultimately led to a severe decline in occupancy that only became apparent much later. Our study emphasizes the importance of knowledge of changes in survival and colonization of species in modern landscapes over a very long time scale. It also demonstrates the power of site-occupancy modeling to obtain important population dynamics information from databases containing opportunistic sighting records.     

Population Viability Analysis of Spring Chinook Salmon in the South Umpqua River, Oregon

Run sizes of spring chinook salmon in the South Umpqua River in Oregon have declined dramatically since the early part of this century. Habitat degradation is thought to be an important factor contributing to the decline of this stock, and qualitative assessment suggests the stock is at moderate risk of extinction. We use data from this and similar stocks to develop an age-structured, density-dependent model of the population dynamics that incorporates both demographic and environmental stochasticity. Under the assumption of no further habitat destruction, the population is predicted to have a greater than 95% probability of persistence for 200 years. However, sensitivity analysis for the density-dependence estimated from historical run-return data shows that substantially lower predicted viabilities are also statistically consistent with the data. A model that simulates continued habitat degradation results in almost certain extinction within 100 years.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

Setting population targets for mammals using body mass as a predictor of population persistence

Conservation planning and biodiversity assessments need quantitative targets to optimize planning options and assess the adequacy of current species protection. However, targets aiming at persistence require population‐specific data, which limit their use in favor of fixed and nonspecific targets, likely leading to unequal distribution of conservation efforts among species. We devised a method to derive equitable population targets; that is, quantitative targets of population size that ensure equal probabilities of persistence across a set of species and that can be easily inferred from species‐specific traits. In our method, we used models of population dynamics across a range of life‐history traits related to species’ body mass to estimate minimum viable population targets. We applied our method to a range of body masses of mammals, from 2 g to 3825 kg. The minimum viable population targets decreased asymptotically with increasing body mass and were on the same order of magnitude as minimum viable population estimates from species‐ and context‐specific studies. Our approach provides a compromise between pragmatic, nonspecific population targets and detailed context‐specific estimates of population viability for which only limited data are available. It enables a first estimation of species‐specific population targets based on a readily available trait and thus allows setting equitable targets for population persistence in large‐scale and multispecies conservation assessments and planning.     

Evidence of large-scale source-sink dynamics and long-distance dispersal among Wood Thrush populations

Source-sink dynamics are commonly thought to occur among Wood Thrush (Hylocichla mustelina) and other songbird populations, allowing for the persistence of populations with negative growth rates ("sinks") through immigration from populations with positive growth rates ("sources"). Knowledge of source-sink dynamics is important for management and conservation because the removal of source habitat should result in the extinction of dependent sinks. However, since research has focused on identifying individual sources/sink populations, not source-sink pairs, we cannot predict these effects or the scale over which they occur. We posit that, when dispersal occurs from a source to a sink year after year, there will be a one-year time-lagged correlation in abundance between the two populations. This should occur for populations separated by distances over which juveniles disperse. Using the North American Breeding Bird Survey data, we tested for such time-lagged correlations between paired Wood Thrush populations from 10 to 200 km apart. Populations were linked with a one-year time lag over distances from 60 to 80 km, indicating that dispersal and source-sink dynamics may occur over these long distances. There was also a declining trend in forest cover from sources to sinks. Conservation and management strategies should therefore be designed at large scales, with consideration for source-sink dynamics and forest cover.     

Estimating the status of nearshore rockfish (Sebastes spp.) populations with length frequency data.

Ecologists often point to excessive truncation of a population's size-structure as a deleterious effect of exploitation, yet the effect of this truncation on population persistence is seldom quantified. While persistence of marine populations requires maintenance of a sufficient level of lifetime reproduction, fishing reduces lifetime reproduction by increasing the total mortality rate, preventing individuals from growing old, large, and highly fecund. We employ a new method of estimating changes in lifetime egg production (LEP) using two samples of the size structure, one in the past and one current, to assess persistence of five species of nearshore rockfish (Sebastes spp.) in California and Oregon, U.S.A. Using length frequency data from catch in the recreational fishery, we estimate that since 1980, four of the five rockfish species considered have experienced declines in LEP to levels that suggest that persistence is impaired. When changes in LEP were estimated for subsets of the data corresponding to neighboring geographical regions, differences in LEP levels were apparent in the neighboring regions, implying that the effects of fishing mortality are not evenly distributed over space. We conclude by discussing the use of this estimation approach to assess the status of other species in data-poor situations.