Estimation and simulation of foraging trips in land-based marine predators.

The behavior of colony-based marine predators is the focus of much research globally. Large telemetry and tracking data sets have been collected for this group of animals, and are accompanied by many empirical studies that seek to segment tracks in some useful way, as well as theoretical studies of optimal foraging strategies. However, relatively few studies have detailed statistical methods for inferring behaviors in central place foraging trips. In this paper we describe an approach based on hidden Markov models, which splits foraging trips into segments labeled as "outbound", "search", "forage", and "inbound". By structuring the hidden Markov model transition matrix appropriately, the model naturally handles the sequence of behaviors within a foraging trip. Additionally, by structuring the model in this way, we are able to develop realistic simulations from the fitted model. We demonstrate our approach on data from southern elephant seals (Mirounga leonina) tagged on Kerguelen Island in the Southern Ocean. We discuss the differences between our 4-state model and the widely used 2-state model, and the advantages and disadvantages of employing a more complex model.

Taking animal tracking to new depths: synthesizing horizontal--vertical movement relationships for four marine predators.

In animal ecology, a question of key interest for aquatic species is how changes in movement behavior are related in the horizontal and vertical dimensions when individuals forage. Alternative theoretical models and inconsistent empirical findings mean that this question remains unresolved. Here we tested expectations by incorporating the vertical dimension (dive information) when predicting switching between movement states ("resident" or "directed") within a state-space model. We integrated telemetry-based tracking and diving data available for four seal species (southern elephant, Weddell, antarctic fur, and crabeater) in East Antarctica. Where possible, we included dive variables derived from the relationships between (1) dive duration and depth (as a measure of effort), and (2) dive duration and the postdive surface interval (as a physiological measure of cost). Our results varied within and across species, but there was a general tendency for the probability of switching into "resident" state to be positively associated with shorter dive durations (for a given depth) and longer postdive surface intervals (for a given dive duration). Our results add to a growing body of literature suggesting that simplistic interpretations of optimal foraging theory based only on horizontal movements do not directly translate into the vertical dimension in dynamic marine environments. Analyses that incorporate at least two dimensions can test more sophisticated models of foraging behavior.

Integrative modelling of animal movement: incorporating in situ habitat and behavioural information for a migratory marine predator.

A fundamental goal in animal ecology is to quantify how environmental (and other) factors influence individual movement, as this is key to understanding responsiveness of populations to future change. However, quantitative interpretation of individual-based telemetry data is hampered by the complexity of, and error within, these multi-dimensional data. Here, we present an integrative hierarchical Bayesian state-space modelling approach where, for the first time, the mechanistic process model for the movement state of animals directly incorporates both environmental and other behavioural information, and observation and process model parameters are estimated within a single model. When applied to a migratory marine predator, the southern elephant seal (Mirounga leonina), we find the switch from directed to resident movement state was associated with colder water temperatures, relatively short dive bottom time and rapid descent rates. The approach presented here can have widespread utility for quantifying movement-behaviour (diving or other)-environment relationships across species and systems.

Linking movement and dive data to prey distribution models: new insights in foraging behaviour and potential pitfalls of movement analyses.

BACKGROUND: Animal movement data are regularly used to infer foraging behaviour and relationships to environmental characteristics, often to help identify critical habitat. To characterize foraging, movement models make a set of assumptions rooted in theory, for example, time spent foraging in an area increases with higher prey density. METHODS: We assessed the validity of these assumptions by associating horizontal movement and diving of satellite-telemetered ringed seals (Pusa hispida)-an opportunistic predator-in Hudson Bay, Canada, to modelled prey data and environmental proxies. RESULTS: Modelled prey biomass data performed better than their environmental proxies (e.g., sea surface temperature) for explaining seal movement; however movement was not related to foraging effort. Counter to theory, seals appeared to forage more in areas with relatively lower prey diversity and biomass, potentially due to reduced foraging efficiency in those areas. CONCLUSIONS: Our study highlights the need to validate movement analyses with prey data to effectively estimate the relationship between prey availability and foraging behaviour.

Environmental drivers of population-level variation in the migratory and diving ontogeny of an Arctic top predator.

The development of migratory strategies that enable juveniles to survive to sexual maturity is critical for species that exploit seasonal niches. For animals that forage via breath-hold diving, this requires a combination of both physiological and foraging skill development. Here, we assess how migratory and dive behaviour develop over the first year of life for a migratory Arctic top predator, the harp seal Pagophilus groenlandicus, tracked using animal-borne satellite relay data loggers. We reveal similarities in migratory movements and differences in diving behaviour between 38 juveniles tracked from the Greenland Sea and Northwest Atlantic breeding populations. In both regions, periods of resident and transitory behaviour during migration were associated with proxies for food availability: sea ice concentration and bathymetric depth. However, while ontogenetic development of dive behaviour was similar for both populations of juveniles over the first 25 days, after this time Greenland Sea animals performed shorter and shallower dives and were more closely associated with sea ice than Northwest Atlantic animals. Together, these results highlight the role of both intrinsic and extrinsic factors in shaping early life behaviour. Variation in the environmental conditions experienced during early life may shape how different populations respond to the rapid changes occurring in the Arctic ocean ecosystem.

A continuous-time state-space model for rapid quality control of argos locations from animal-borne tags.

BACKGROUND: State-space models are important tools for quality control and analysis of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system can aid dynamic ocean management of human activities by informing when animals enter wind farms, shipping lanes, and other intensive use zones. This capability also facilitates the use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations. METHODS: We formulate a continuous-time state-space model to filter the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of observations. Our model is deliberately simple to ensure speed and reliability for automated, near real-time quality control of Argos location data. We validate the model by fitting to Argos locations collected from 61 individuals across 7 marine vertebrates and compare model-estimated locations to contemporaneous GPS locations. We then test assumptions that Argos Kalman filter/smoother error ellipses are unbiased, and that Argos Kalman smoother location accuracy cannot be improved by subsequent state-space modelling. RESULTS: Estimation accuracy varied among species with Root Mean Squared Errors usually <5 km and these decreased with increasing data sampling rate and precision of Argos locations. Including a model parameter to inflate Argos error ellipse sizes in the north - south direction resulted in more accurate location estimates. Finally, in some cases the model appreciably improved the accuracy of the Argos Kalman smoother locations, which should not be possible if the smoother is using all available information. CONCLUSIONS: Our model provides quality-controlled locations from Argos Least-Squares or Kalman filter data with accuracy similar to or marginally better than Argos Kalman smoother data that are only available via fee-based reprocessing. Simplicity and ease of use make the model suitable both for automated quality control of near real-time Argos data and for manual use by researchers working with historical Argos data.

The retrospective analysis of Antarctic tracking data project.

The Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.

Sex-specific, seasonal foraging tactics of adult grey seals (Halichoerus grypus) revealed by state-space analysis.

In many large pelagic animals, observing behavior is limited to observation by radio or satellite telemetry. In many cases, discriminating different behaviors from telemetry data has been a key, but often elusive, goal. Here we use state-space models (SSMs) to fit a correlated random walk (CRW) model that switches between two unobserved behavioral states (nominally foraging and traveling) to 41 male and 43 female adult grey seal (Halichoerus grypus) satellite telemetry tracks. The SSM results reveal markedly different spatial behavior between the sexes, fitting well with sexual size dimorphism and known dietary differences, suggesting that the sexes deal with seasonal prey availability and reproductive costs differently. From these results we were also able to produce behaviorally informed habitat use maps, showing a complex and dynamic network of small, intensely used foraging areas. Our flexible SSM approach clearly demonstrates sex-related behavioral differences, fine scale spatial and temporal foraging patterns, and a clearer picture of grey seal ecology and role in the Scotian Shelf ecosystem.

Assessing threats to species at risk using stage-structured state-space models: mortality trends in skate populations.

Population models are needed to assess the threats to species at risk and to evaluate alternative management actions. Data to support modeling is limited for many species at risk, and commonly used approaches generally assume stationary vital rates, a questionable assumption given widespread ecosystem change. We describe a modeling approach that can be applied to time series of length composition data to estimate vital rates and test for changes in these rates. Our approach uses stage-structured population models fit within a Bayesian state-space model. This approach simultaneously allows for both process and observation uncertainty, and it facilitates incorporating prior information on population dynamics and on the monitoring process. We apply these models to populations of winter skate (Leucoraja ocellata) that have been designated as "endangered" or "threatened." These models indicate that natural mortality has decreased for juveniles and increased for adults in these populations. The declines observed in these populations had been attributed to unsustainable rates of bycatch in fisheries for other groundfishes; our analyses indicate that increased natural mortality of adults is also an important factor contributing to these declines. Adult natural mortality was positively related to grey seal (Halichoerus grypus) abundance, suggesting the hypothesis that increased adult mortality reflected increased predation by expanding grey seal herds. Population projections indicated that the threatened population would be expected to stabilize at a low level of abundance if all fishery removals were eliminated, but that the endangered population would likely continue to decline even in the absence of fishery removals. We note that time series of size distributions are available for most marine fish populations monitored by research surveys, and we suggest that a similar approach could be used to extract information from these time series in order to estimate mortality rates and changes in these rates.

Abundance estimates and habitat preferences of bottlenose dolphins reveal the importance of two gulfs in South Australia.

Informed conservation management of marine mammals requires an understanding of population size and habitat preferences. In Australia, such data are needed for the assessment and mitigation of anthropogenic impacts, including fisheries interactions, coastal zone developments, oil and gas exploration and mining activities. Here, we present large-scale estimates of abundance, density and habitat preferences of southern Australian bottlenose dolphins (Tursiops sp.) over an area of 42,438km2 within two gulfs of South Australia. Using double-observer platform aerial surveys over four strata and mark-recapture distance sampling analyses, we estimated 3,493 (CV = 0.21; 95%CI = 2,327-5,244) dolphins in summer/autumn, and 3,213 (CV = 0.20; 95%CI = 2,151-4,801) in winter/spring of 2011. Bottlenose dolphin abundance and density was higher in gulf waters across both seasons (0.09-0.24 dolphins/km2) compared to adjacent shelf waters (0.004-0.04 dolphins/km2). The high densities of bottlenose dolphins in the two gulfs highlight the importance of these gulfs as a habitat for the species. Habitat modelling associated bottlenose dolphins with shallow waters, flat seafloor topography, and higher sea surface temperatures (SSTs) in summer/autumn and lower SSTs in winter/spring. Spatial predictions showed high dolphin densities in northern and coastal gulf sections. Distributional data should inform management strategies, marine park planning and environmental assessments of potential anthropogenic threats to this protected species.

State-space models' dirty little secrets: even simple linear Gaussian models can have estimation problems.

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.

A novel approach to quantifying the spatiotemporal behavior of instrumented grey seals used to sample the environment.

BACKGROUND: Paired with satellite location telemetry, animal-borne instruments can collect spatiotemporal data describing the animal's movement and environment at a scale relevant to its behavior. Ecologists have developed methods for identifying the area(s) used by an animal (e.g., home range) and those used most intensely (utilization distribution) based on location data. However, few have extended these models beyond their traditional roles as descriptive 2D summaries of point data. Here we demonstrate how the home range method, T-LoCoH, can be expanded to quantify collective sampling coverage by multiple instrumented animals using grey seals (Halichoerus grypus) equipped with GPS tags and acoustic transceivers on the Scotian Shelf (Atlantic Canada) as a case study. At the individual level, we illustrate how time and space-use metrics quantifying individual sampling coverage may be used to determine the rate of acoustic transmissions received. RESULTS: Grey seals collectively sampled an area of 11,308 km (2) and intensely sampled an area of 31 km (2) from June-December. The largest area sampled was in July (2094.56 km (2)) and the smallest area sampled occurred in August (1259.80 km (2)), with changes in sampling coverage observed through time. CONCLUSIONS: T-LoCoH provides an effective means to quantify changes in collective sampling effort by multiple instrumented animals and to compare these changes across time. We also illustrate how time and space-use metrics of individual instrumented seal movement calculated using T-LoCoH can be used to account for differences in the amount of time a bioprobe (biological sampling platform) spends in an area.

Daily activity budgets reveal a quasi-flightless stage during non-breeding in Hawaiian albatrosses.

BACKGROUND: Animals adjust activity budgets as competing demands for limited time and energy shift across life history phases. For far-ranging migrants and especially pelagic seabirds, activity during breeding and migration are generally well studied but the "overwinter" phase of non-breeding has received less attention. Yet this is a critical time for recovery from breeding, plumage replacement and gaining energy stores for return migration and the next breeding attempt. We aimed to identify patterns in daily activity budgets (i.e. time in flight, floating on the water's surface and active foraging) and associated spatial distributions during overwinter for the laysan Phoebastria immutabilis and black-footed P. nigripes albatrosses using state-space models and generalized additive mixed-effects models (GAMMs). We applied these models to time-series of positional and immersion-state data from small light- and conductivity-based data loggers. RESULTS: During overwinter, both species exhibited a consistent 'quasi-flightless' stage beginning c. 30 days after initiating migration and lasting c. 40 days, characterized by frequent long bouts of floating, very little sustained flight, and infrequent active foraging. Minimal daily movements were made within localized areas during this time; individual laysan albatross concentrated into the northwest corner of the Pacific while black-footed albatross spread widely across the North Pacific Ocean basin. Activity gradually shifted toward increased time in flight and active foraging, less time floating, and greater daily travel distances until colony return c. 155 days after initial departure. CONCLUSIONS: Our results demonstrate that these species make parallel adjustments to activity budgets at a daily time-scale within the overwinter phase of non-breeding despite different at-sea distributions and phenologies. The 'quasi-flightless' stage likely reflects compromised flight from active wing moult while the subsequent increase in activity may occur as priorities shift toward mass gain for breeding. The novel application of a GAMM-based approach used in this study offers the possibility of identifying population-level patterns in shifting activity budgets over extended periods while allowing for individual-level variation in the timing of events. The information gained can also help to elucidate the whereabouts of areas important at different times across life history phases for far-ranging migrants.

Probability of detecting marine predator-prey and species interactions using novel hybrid acoustic transmitter-receiver tags.

Understanding the nature of inter-specific and conspecific interactions in the ocean is challenging because direct observation is usually impossible. The development of dual transmitter/receivers, Vemco Mobile Transceivers (VMT), and satellite-linked (e.g. GPS) tags provides a unique opportunity to better understand between and within species interactions in space and time. Quantifying the uncertainty associated with detecting a tagged animal, particularly under varying field conditions, is vital for making accurate biological inferences when using VMTs. We evaluated the detection efficiency of VMTs deployed on grey seals, Halichoerus grypus, off Sable Island (NS, Canada) in relation to environmental characteristics and seal behaviour using generalized linear models (GLM) to explore both post-processed detection data and summarized raw VMT data. When considering only post-processed detection data, only about half of expected detections were recorded at best even when two VMT-tagged seals were estimated to be within 50-200 m of one another. At a separation of 400 m, only about 15% of expected detections were recorded. In contrast, when incomplete transmissions from the summarized raw data were also considered, the ratio of complete transmission to complete and incomplete transmissions was about 70% for distances ranging from 50-1000 m, with a minimum of around 40% at 600 m and a maximum of about 85% at 50 m. Distance between seals, wind stress, and depth were the most important predictors of detection efficiency. Access to the raw VMT data allowed us to focus on the physical and environmental factors that limit a transceiver's ability to resolve a transmitter's identity.

Inferring animal densities from tracking data using Markov chains.

The distributions and relative densities of species are keys to ecology. Large amounts of tracking data are being collected on a wide variety of animal species using several methods, especially electronic tags that record location. These tracking data are effectively used for many purposes, but generally provide biased measures of distribution, because the starts of the tracks are not randomly distributed among the locations used by the animals. We introduce a simple Markov-chain method that produces unbiased measures of relative density from tracking data. The density estimates can be over a geographical grid, and/or relative to environmental measures. The method assumes that the tracked animals are a random subset of the population in respect to how they move through the habitat cells, and that the movements of the animals among the habitat cells form a time-homogenous Markov chain. We illustrate the method using simulated data as well as real data on the movements of sperm whales. The simulations illustrate the bias introduced when the initial tracking locations are not randomly distributed, as well as the lack of bias when the Markov method is used. We believe that this method will be important in giving unbiased estimates of density from the growing corpus of animal tracking data.

Animal-borne acoustic transceivers reveal patterns of at-sea associations in an upper-trophic level predator.

Satellite telemetry data have substantially increased our understanding of habitat use and foraging behaviour of upper-trophic marine predators, but fall short of providing an understanding of their social behaviour. We sought to determine whether novel acoustic and archival GPS data could be used to examine at-sea associations among grey seals (Halichoerus grypus) during the fall foraging period. Fifteen grey seals from Sable Island, Canada were deployed with Vemco Mobile Transceivers and Satellite-GPS transmitters in October 2009, 13 of which were recaptured and units retrieved 79 ± 2.3 days later during the following breeding season, December 2009-January 2010. An association between two individuals was defined as a cluster of acoustic detections where the time between detections was <30 min. Bathymetry, travel rate, and behavioural state (slow and fast movement) were determined for each GPS archival point (3.7 ± 0.1 locations recorded per hour). Behavioural state was estimated using a hidden Markov model. All seals had been involved in associations with other instrumented seals while at sea, with a total of 1,872 acoustic detections recorded in 201 associations. The median number of detections per association was 3 (range: 1-151) and the median duration of an association was 0.17 h (range: <0.1-11.3 h). Linear mixed-effects models showed that associations occurred when seals were exhibiting slow movement (0.24 ± 0.01 ms(-1)) on shallow (53.4 ± 3.7 m) offshore banks where dominant prey is known to occur. These results suggest the occurrence of short-term associations among multiple individuals at foraging grounds and provide new insights into the foraging ecology of this upper-trophic marine predator.

Incorrect likelihood methods were used to infer scaling laws of marine predator search behaviour.

BACKGROUND: Ecologists are collecting extensive data concerning movements of animals in marine ecosystems. Such data need to be analysed with valid statistical methods to yield meaningful conclusions. PRINCIPAL FINDINGS: We demonstrate methodological issues in two recent studies that reached similar conclusions concerning movements of marine animals (Nature 451:1098; Science 332:1551). The first study analysed vertical movement data to conclude that diverse marine predators (Atlantic cod, basking sharks, bigeye tuna, leatherback turtles and Magellanic penguins) exhibited "Lévy-walk-like behaviour", close to a hypothesised optimal foraging strategy. By reproducing the original results for the bigeye tuna data, we show that the likelihood of tested models was calculated from residuals of regression fits (an incorrect method), rather than from the likelihood equations of the actual probability distributions being tested. This resulted in erroneous Akaike Information Criteria, and the testing of models that do not correspond to valid probability distributions. We demonstrate how this led to overwhelming support for a model that has no biological justification and that is statistically spurious because its probability density function goes negative. Re-analysis of the bigeye tuna data, using standard likelihood methods, overturns the original result and conclusion for that data set. The second study observed Lévy walk movement patterns by mussels. We demonstrate several issues concerning the likelihood calculations (including the aforementioned residuals issue). Re-analysis of the data rejects the original Lévy walk conclusion. CONCLUSIONS: We consequently question the claimed existence of scaling laws of the search behaviour of marine predators and mussels, since such conclusions were reached using incorrect methods. We discourage the suggested potential use of "Lévy-like walks" when modelling consequences of fishing and climate change, and caution that any resulting advice to managers of marine ecosystems would be problematic. For reproducibility and future work we provide R source code for all calculations.

Hierarchical state-space estimation of leatherback turtle navigation ability.

Remotely sensed tracking technology has revealed remarkable migration patterns that were previously unknown; however, models to optimally use such data have developed more slowly. Here, we present a hierarchical Bayes state-space framework that allows us to combine tracking data from a collection of animals and make inferences at both individual and broader levels. We formulate models that allow the navigation ability of animals to be estimated and demonstrate how information can be combined over many animals to allow improved estimation. We also show how formal hypothesis testing regarding navigation ability can easily be accomplished in this framework. Using Argos satellite tracking data from 14 leatherback turtles, 7 males and 7 females, during their southward migration from Nova Scotia, Canada, we find that the circle of confusion (the radius around an animal's location within which it is unable to determine its location precisely) is approximately 96 km. This estimate suggests that the turtles' navigation does not need to be highly accurate, especially if they are able to use more reliable cues as they near their destination. Moreover, for the 14 turtles examined, there is little evidence to suggest that male and female navigation abilities differ. Because of the minimal assumptions made about the movement process, our approach can be used to estimate and compare navigation ability for many migratory species that are able to carry electronic tracking devices.

Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles.

1. Biological and statistical complexity are features common to most ecological data that hinder our ability to extract meaningful patterns using conventional tools. Recent work on implementing modern statistical methods for analysis of such ecological data has focused primarily on population dynamics but other types of data, such as animal movement pathways obtained from satellite telemetry, can also benefit from the application of modern statistical tools. 2. We develop a robust hierarchical state-space approach for analysis of multiple satellite telemetry pathways obtained via the Argos system. State-space models are time-series methods that allow unobserved states and biological parameters to be estimated from data observed with error. We show that the approach can reveal important patterns in complex, noisy data where conventional methods cannot. 3. Using the largest Atlantic satellite telemetry data set for critically endangered leatherback turtles, we show that the diel pattern in travel rates of these turtles changes over different phases of their migratory cycle. While foraging in northern waters the turtles show similar travel rates during day and night, but on their southward migration to tropical waters travel rates are markedly faster during the day. These patterns are generally consistent with diving data, and may be related to changes in foraging behaviour. Interestingly, individuals that migrate southward to breed generally show higher daytime travel rates than individuals that migrate southward in a non-breeding year. 4. Our approach is extremely flexible and can be applied to many ecological analyses that use complex, sequential data.

The influence of matrix habitat on Aphthona flea beetle immigration to leafy spurge patches.

Variation in movement ability by insects among different non-habitat (matrix) types may have important implications for both metapopulation dynamics and weed biocontrol practices. We used a mark-recapture experiment to explore the effects of two different matrix habitats (grass vs shrub) on the ability of two species of Aphthona (Chrysomelidae: Coleoptera) flea beetle to immigrate to patches of the invasive weed, leafy spurge. Using generalized linear models, we compared effects of the matrix habitat types, species and sex on observed immigration probabilities. Our analyses demonstrated that one species (A. nigriscutis) had a much higher immigration probability when moving through a grass-dominated matrix than a shrub-dominated matrix whereas immigration probabilities for the second species (A. lacertosa) were similar in both matrix habitats but significantly lower overall than for A. nigriscutis. Furthermore, A. nigriscutis females were more likely to immigrate to spurge patches embedded in a grass matrix than in shrub, whereas the opposite occurred for males. Our results suggest that metapopulation dynamics may be strongly affected by the type(s) of matrix habitat present on a landscape. These effects also suggest that release strategies for weed biocontrol should be tailored according to the structure of the landscape into which releases are planned. In addition, even closely related species can have significantly different movement abilities which will also affect release strategies.