Invasion and eradication of a competitively superior species in heterogeneous landscapes

The effect of heterogeneous environments upon the dynamics of invasion and the eradication or control of invasive species is poorly understood, although it is a major challenge for biodiversity conservation. Here, we first investigate how the probability and time for invasion are affected by spatial heterogeneity. Then, we study the effect of control program strategies (e.g. species specificity, spatial scale of action, detection and eradication efficiency) on the success and time of eradication. We find that heterogeneity increases both the invasion probability and the time to invasion. Heterogeneity also reduces the probability of eradication but does not change the time taken for successful eradication. We confirm that early detection of invasive species reduces the time until eradication, but we also demonstrate that this is true only if the local control action is sufficiently efficient. The criterion of removal efficiency is even more important for an eradication program than simply ensuring control effort when the invasive species is not abundant.     

Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach

Ticks act as vectors of pathogens that can be harmful to animals and/or humans. Epidemiological models can be useful tools to investigate the potential effects of control strategies on diseases such as tick-borne diseases. The modelling of tick population dynamics is a prerequisite to simulating tick-borne diseases and the corresponding spread of the pathogen. We have developed a dynamic model to simulate changes in tick density at different stages (egg, larva, nymph and adult) under the influence of temperature. We have focused on the tick Ixodes ricinus, which is widespread in Europe. The main processes governing the biological cycles of ticks were taken into account: egg laying, hatching, development, host (small, mainly rodents, or large, like deer and cattle, mammals) questing, feeding and mortality. This model was first applied to a homogeneous habitat, where simulations showed the ability of the model to reproduce the general patterns of tick population dynamics. We considered thereafter a multi-habitat model, where three different habitats (woodland, ecotone and meadow) were connected through host migration. Based on this second application, it appears that migration from woodland, via the ecotone, is necessary to sustain the presence of ticks in the meadow. Woodland can therefore be considered as a source of ticks for the meadow, which in turn can be regarded as a sink. The influence of woodland on surrounding tick densities increases in line with the area of this habitat before reaching a plateau. A sensitivity analysis to parameter values was carried out and demonstrated that demographic parameters (sex ratio, development, mortality during feeding and questing, host finding) played a crucial role in the determination of questing nymph densities. This type of modelling approach provides insight into the influence of spatial heterogeneity on tick population dynamics.     

The influence of host diversity and composition on epidemiological patterns at multiple spatial scales

Spatial patterns of pathogen prevalence are determined by ecological processes acting across multiple spatial scales. Host-pathogen interactions are influenced by community composition, landscape structure, and environmental factors. Explaining prevalence patterns requires an understanding of how local determinants of infection, such as community composition, are mediated by landscape characteristics and regional-scale environmental drivers. Here we investigate the role of local community interactions and the effects of landscape structure on the dynamics of barley and cereal yellow dwarf viruses (B/CYDV) in the open meadows of the Cascade Mountains of Oregon. B/CYDV is an aphid-transmitted, generalist pathogen of over 100 wild and cultivated grass species. We used variance components analysis and model selection techniques to partition the sources of variation in B/CYDV prevalence and to determine which abiotic and biotic factors influence host-pathogen interactions in a Cascades meadowsystem. B/CYDV prevalence in Cascades meadows varied by host species identity, with a significantly higher proportion of infected Festuca idahoensis individuals than Elymus glaucus or Bromus carinatus. Although there was significant variation in prevalence among host species and among meadows in the same meadow complex, there was no evidence of any significant variation in prevalence among different meadow complexes at a larger spatial scale. Variation in prevalence among meadows was primarily associated with the local community context (host identity, the relative abundance of different host species, and host species richness) and the physical landscape attributes of the meadow. These results highlight the importance of local host community composition, mediated by landscape characteristics such as meadow aspect, as a determinant of the spatial pattern of infection of a multi-host pathogen.     

A spatial-temporal optimization approach to watershed management: Acid mine drainage treatment in the Cheat River watershed, WV, USA

Most water management studies concentrate on the inter-temporal allocation problem or, more recently, spatial dynamics - but not both. While early spatial-temporal studies focused on the allocation of water quantity, this paper presents an approach to water quality analysis that incorporates both spatial and temporal dynamics in a watershed framework. The acid mine drainage (AMD) problem in the Cheat River watershed of West Virginia, USA, serves as a case study and provides an opportunity to test the modeling approach developed. The empirical models are written in General Algebraic Modeling System (GAMS) and solved using the CPLEX mixed integer programming package. The results suggest that available investments should be concentrated in heavily impaired stream segments. The model can be used to assess the economic implications of alternative watershed Total Maximum Daily Load (TMDL) implementation or other management strategies.     

Independent effects of fragmentation on forest songbirds: an organism-based approach.

The degree to which spatial patterns influence the dynamics and distribution of populations is a central question in ecology. This question is even more pressing in the context of rapid habitat loss and fragmentation, which threaten global biodiversity. However, the relative influence of habitat loss and landscape fragmentation, the spatial patterning of remaining habitat, remains unclear. If landscape pattern affects population size, managers may be able to design landscapes that mitigate habitat loss. We present the results of a mensurative experiment designed to test four habitat loss vs. fragmentation hypotheses. Unlike previous studies, we measured landscape structure using quantitative, spatially explicit habitat distribution models previously developed for two species: Blackburnian Warbler (Dendroica fusca) and Ovenbird (Seiurus aurocapilla). We used a stratified sampling design that reduced the confounding of habitat amount and fragmentation variables. Occurrence and reoccurrence of both species were strongly influenced by characteristics at scales greater than the individual territory, indicating little support for the random-sample hypothesis. However, the type and spatial extent of landscape influence differed. Both occurrence and reoccurrence of Blackburnian Warblers were influenced by the amount of poor-quality matrix at 300- and 2000-m spatial extents. The occurrence and reoccurrence of Ovenbirds depended on a landscape pattern variable, patch size, but only in cases when patches were isolated. These results support the hypothesis that landscape pattern is important for some species only when the amount of suitable habitat is low. Although theoretical models have predicted such an interaction between landscape fragmentation and composition, to our knowledge this is the first study to report empirical evidence of such nonlinear fragmentation effects. Defining landscapes quantitatively from an organism-based perspective may increase power to detect fragmentation effects, particularly in forest mosaics where boundaries between patches and matrix are ambiguous. Our results indicate that manipulating landscape pattern may reduce negative impacts of habitat loss for Ovenbird, but not Blackburnian Warbler. We emphasize that most variance in the occurrence of both species was explained by local scale or landscape composition variables rather than variables reflecting landscape pattern.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Native ecotypic variation and the role of host identity in the spread of an invasive herbivore, Cactoblastis cactorum

Environmental niche models (ENMs) have gained enormous popularity as tools to investigate potential changes in species distributions resulting from climate change and species introductions. Despite recognition that species interactions can influence the dynamics of invasion spread, most implementations of ENMs focus on abiotic factors as the sole predictors of potential range limits. Implicit in this approach is the assumption that biotic interactions are relatively unimportant, either because of scaling issues, or because fundamental and realized niches are equivalent in a species' native range. When species are introduced into exotic landscapes, changes in biotic interactions relative to the native range can lead to occupation of different regions of niche space and apparent shifts in physiological tolerances. We use an escaped biological control organism, Cactoblastis cactorum (Berg.), to assess the role of the environmental envelope as compared with patterns of host-herbivore associations based on collections made in the native range. Because all nonnative populations are derived from a single C. cactorum ecotype, we hypothesize that biotic interactions associated with this ecotype are driving the species' invasion dynamics. Environmental niche models constructed from known native populations perform poorly in predicting nonnative distributions of this species, except where there is an overlap in niche space. In contrast, genetic isolation in the native range is concordant with the observed pattern of host use, and strong host association has been noted in nonnative landscapes. Our results support the hypothesis that the apparent shift in niche space from the native to the exotic ranges results from a shift in biotic interactions, and demonstrate the importance of considering biotic interactions in assessing the risk of future spread for species whose native range is highly constrained by biotic interactions.     

Spatial heterogeneity influences native and nonnative plant species richness

Spatial heterogeneity may have differential effects on the distribution of native and nonnative plant species richness. We examined the effects of spatial heterogeneity on native and nonnative plant species richness distributions in the central part of Rocky Mountain National Park, Colorado, USA. Spatial heterogeneity around vegetation plots was characterized using landscape metrics, environmental/topographic variables (slope, aspect, elevation, and distance from stream or river), and soil variables (nitrogen, clay, and sand). The landscape metrics represented five components of landscape heterogeneity and were measured at four spatial extents (within varying radii of 120, 240, 480, and 960 m) using the FRAGSTATS landscape pattern analysis program. Akaike's Information Criterion adjusted for small sample size (AICc) was used to select the best models from a set of multiple linear regression models developed for native and nonnative plant species richness at four spatial extents and three levels of ecological hierarchy (i.e., landscape, land cover, and community). Both native and nonnative plant species richness were positively correlated with edge density, Simpson's diversity index and interspersion/juxtaposition index, and were negatively correlated with mean patch size. The amount of variation explained at four spatial extents and three hierarchical levels ranged from 30% to 70%. At the landscape level, the best models explained 43% of the variation in native plant species richness and 70% of the variation in nonnative plant species richness (240-m extent). In general, the amount of variation explained was always higher for nonnative plant species richness, and the inclusion of landscape metrics always significantly improved the models. The best models explained 66% of the variation in nonnative plant species richness for both the conifer land cover type and lodgepole pine community. The relative influence of the components of spatial heterogeneity differed for native and nonnative plant species richness and varied with the spatial extent of analysis and levels of ecological hierarchy. The study offers an approach to quantify spatial heterogeneity to improve models of plant biodiversity. The results demonstrate that ecologists must recognize the importance of spatial heterogeneity in managing native and nonnative plant species.     

Interplay between proteases and protease inhibitors in the sea fan—Aspergillus pathosystem

Environmental conditions greatly impact the dynamics of host–pathogen relationships, affecting outbreaks and emergence of new diseases. In corals, epizootics have been a main contributor to the decline of reef ecosystems and rising sea surface temperatures associated with climate change are thought to exacerbate virulence of pathogens and/or compromise the immune responses of coral hosts. Among pathogens strategies, protease secretion is a common virulence factor that promotes colonization of the host. As such, protease inhibitors play an invaluable role to the host for protection against pathogen invasion. This study describes changes in activity of proteases secreted by the fungal pathogen, Aspergillus sydowii, and protease inhibitors of Gorgonia ventalina under ambient and elevated temperatures and health conditions (disease and healthy). G. ventalina colonies were collected from Florida Keys, Florida (24° 34.138N, 81° 22.905W) or La Parguera, Puerto Rico (17° 56.091N, 67° 02.577W) in 2007 and 2012, respectively. At elevated temperatures, protease activity was significantly higher than at ambient temperatures in A. sydowii. Temperature stress did not induce a change in protease inhibitor activity, but in healthy G. ventalina colonies, inhibitor activity against proteases was higher than in diseased individuals. Healthy colonies appear capable of resisting proteolytic activity, but diseased individuals are still likely affected by pathogen infections. These data suggest that rising sea surface temperatures due to climate change may increase levels of virulence (protease activity) of A. sydowii, while immunity (protease inhibitor) of G. ventalina may not be affected.     

Temperature-associated population diversity in salmon confers benefits to mobile consumers

Habitat heterogeneity can generate intraspecific diversity through local adaptation of populations. While it is becoming increasingly clear that population diversity can increase stability in species abundance, less is known about how population diversity can benefit consumers that can integrate across population diversity in their prey. Here we demonstrate cascading effects of thermal heterogeneity on trout-salmon interactions in streams where rainbow trout rely heavily on the seasonal availability of anadromous salmon eggs. Water temperature in an Alaskan stream varied spatially from 5 degrees C to 17.5 degrees C, and spawning sockeye salmon showed population differentiation associated with this thermal heterogeneity. Individuals that spawned early in cool regions of the 5 km long stream were genetically differentiated from those spawning in warmer regions later in the season. Sockeye salmon spawning generates a pulsed resource subsidy that supports the majority of seasonal growth in stream-dwelling rainbow trout. The spatial and temporal structuring of sockeye salmon spawn timing in our focal stream extended the duration of the pulsed subsidy compared to a thermally homogeneous stream with a single population of salmon. Further, rainbow trout adopted movement strategies that exploited the multiple pulses of egg subsidies in the thermally heterogeneous stream. Fish that moved to track the resource pulse grew at rates about 2.5 times higher than those that remained stationary or trout in the reference stream with a single seasonal pulse of eggs. Our results demonstrate that habitat heterogeneity can have important effects on the population diversity of dominant species, and in turn, influence their value to species that prey upon them. Therefore, habitat homogenization may have farther-reaching ecological effects than previously considered.     

Dynamics and management of infectious disease in colonizing populations

The introduction of chronic, infectious diseases by colonizing populations (invasive or reintroduced) is a serious hazard in conservation biology, threatening the original host and other spillover species. Most research on spatial invasion of diseases has pertained to established host populations, either at steady state or fluctuating through time. Within a colonizing population, however, the spread of disease may be influenced by the expansion process of the population itself. Here we explore the simultaneous expansion of a colonizing population and a chronic, nonlethal disease introduced with it, describing basic patterns in homogeneous and structured landscapes and discussing implications for disease management. We describe expected outcomes of such introductions for three qualitatively distinct cases, depending on the relative velocities at which the population and epidemic expand. (1) If transmissibility is low the disease cannot be sustained, although it may first expand its range somewhat around the point of introduction. (2) If transmissibility is moderate but the wave-front velocity for the population, vp, is higher than that for the disease, vd, the disease wave front lags behind that of the population. (3) A highly transmissible disease, with vd > vp, will invade sufficiently rapidly to track the spread of the host. To test these elementary theoretical predictions, we simulated disease outbreaks in a spatially structured host population occupying a real landscape. We used a spatially explicit, individual-based model of Persian fallow deer (Dama mesopotamica) reintroduced in northern Israel, considering a hypothetical introduction of bovine tuberculosis. Basic patterns of disease expansion in this realistic setting were similar to our conceptual predictions for homogeneous landscapes. Landscape heterogeneity, however, induced the establishment of population activity centers and disease foci within them, leading to jagged wave fronts and causing local variation in the relative velocities at which the population and epidemic expanded. Based on predictions from simple theory and simulations of managed outbreaks, we suggest that the relative velocities at which the population and epidemic expand have important implications for the impact of different management strategies. Recognizing which of our three general cases best describes a particular outbreak will aid in planning an efficient strategy to contain the disease.     

Spatially mixed crops to control the stratified dispersal of airborne fungal diseases

Intraspecific crop diversification is thought to be a possible solution to the disease susceptibility of monocultured crops. We modelled the stratified dispersal of an airborne pathogen population in order to identify the spatial patterns of cultivar mixtures that could slow epidemic spread driven by dual dispersal mechanisms acting over both short and long distances. We developed a model to simulate the propagation of a fungal disease in a 2D field, including a reaction-diffusion model for short-distance disease dispersal, and a stochastic model for long-distance dispersal. The model was fitted to data for the spatio-temporal spread of faba bean rust (caused by Uromyces viciae-fabae) through a discontinuous field. The model was used to compare the effectiveness of eight different planting patterns of cultivar mixtures against a disease spread by short-distance and stratified dispersal. Our combined modelling approach provides a reasonably good fit with the observed data for the spread of faba bean rust. Similar predictive power could be expected for the management of resource-mediated invasions by other airborne fungi. If a disease spreads by short-distance dispersal, random mixtures can be used to slow the epidemic spread, since their spatial irregularity creates a natural barrier to the progression of a smooth epidemic wave. In the context of stratified dispersal, heterogeneous patterns should be used that include a minimum distance between susceptible units, which decreases the probability of infection by long-distance spore dispersal. We provide a simple framework for modelling the stratified dispersal of disease in a diversified crop. The model suggests that the spatial arrangement of components in cultivar mixtures has to accord with the dispersal characteristics of the pathogen in order to increase the efficiency of diversification strategies in agro-ecosystems and forestry. It can be applied in low input agriculture to manage pathogen invasion by intercropping and cultivar mixtures, and to design sustainable systems of land use.     

Inferring evolutionary signals from ecological data in a plant-pathogen metapopulation

We followed the dynamics of local epidemics in three populations of a natural plant-pathogen system for four sequential years. We characterize the overwintering process with spatial statistics and use a stochastic, spatially explicit, modeling approach with Bayesian parameter estimation to study the spread of the infection during the growing season. Our modeling approach allows us to infer coevolutionary signals from spatiotemporal data on pathogen prevalence. Most importantly, we are able to assess the distribution of resistant hosts within the distribution of all host plants. We show that resistant hosts occur in areas with high pathogen encounter rates, and that the occurrence of resistance correlates with overwintering probability of the pathogen. The estimates for essentially all model parameters are characterized by a large amount of variation over the years and the populations. While the variation in the fraction of resistant hosts and in the force of infection is to a large extent explained by the population, the other model parameters (two parameters describing the shape of the dispersal kernel) vary essentially in an unpredictable manner, suggesting that much of the variation may occur at very fine spatial and temporal scales.     

Spatial connectivity in a large river system: resolving the sources and fate of dissolved organic matter

Large rivers are generally heterogeneous and productive systems that receive important inputs of dissolved organic matter (DOM) from terrestrial and in situ sources. Thus, they are likely to play a significant role in the biogeochemical cycling of the DOM flowing to the oceans. The asymmetric spatial gradient driven by directional flow and environmental heterogeneity contributes to the fate of DOM flowing downstream. Yet, the relative effects of spatial connectivity and environmental heterogeneity on DOM dynamics are poorly understood. For example, since environmental variables show spatial heterogeneity, the variation explained by environmental and spatial variables may be redundant. We used the St. Lawrence River (SLR) as a representative large river to resolve the unique influences of environmental heterogeneity and spatial connectivity on DOM dynamics. We used three-dimensional fluorescence matrices combined with parallel factor analysis (PARAFAC) to characterize the DOM pool in the SLR. Seven fluorophores were modeled, of which two were identified to be of terrestrial origin and three from algal exudates. We measured a set of environmental variables that are known to drive the fate of DOM in aquatic systems. Additionally, we used asymmetric eigenvector map (AEM) modeling to take spatial connectivity into account. The combination of spatial and environmental models explained 85% of the DOM variation. We show that spatial connectivity is an important driver of DOM dynamics, as a large fraction of environmental heterogeneity was attributable to the asymmetric spatial gradient. Along the longitudinal axis, we noted a rapid increase in dissolved organic carbon (DOC), mostly controlled by terrestrial input of DOM originating from the tributaries. Variance partitioning demonstrated that freshly produced protein-like DOM was found to be the preferential substrate for heterotrophic bacteria undergoing rapid proliferation, while humic-like DOM was more correlated to the diffuse attenuation coefficient of UVA radiation.     

Using a common commensal bacterium in endangered Takahe as a model to explore pathogen dynamics in isolated wildlife populations

Predicting and preventing outbreaks of infectious disease in endangered wildlife is problematic without an understanding of the biotic and abiotic factors that influence pathogen transmission and the genetic variation of microorganisms within and between these highly modified host communities. We used a common commensal bacterium, Campylobacter spp., in endangered Takahe (Porphyrio hochstetteri) populations to develop a model with which to study pathogen dynamics in isolated wildlife populations connected through ongoing translocations. Takahe are endemic to New Zealand, where their total population is approximately 230 individuals. Takahe were translocated from a single remnant wild population to multiple offshore and mainland reserves. Several fragmented subpopulations are maintained and connected through regular translocations. We tested 118 Takahe from 8 locations for fecal Campylobacter spp. via culture and DNA extraction and used PCR for species assignment. Factors relating to population connectivity and host life history were explored using multivariate analytical methods to determine associations between host variables and bacterial prevalence. The apparent prevalence of Campylobacter spp. in Takahe was 99%, one of the highest reported in avian populations. Variation in prevalence was evident among Campylobacter species identified. C. sp. nova 1 (90%) colonized the majority of Takahe tested. Prevalence of C. jejuni (38%) and C. coli (24%) was different between Takahe subpopulations, and this difference was associated with factors related to population management, captivity, rearing environment, and the presence of agricultural practices in the location in which birds were sampled. Modeling results of Campylobacter spp. in Takahe metapopulations suggest that anthropogenic management of endangered species within altered environments may have unforeseen effects on microbial exposure, carriage, and disease risk. Translocation of wildlife between locations could have unpredictable consequences including the spread of novel microbes between isolated populations.     

A multi-agent simulation to assess the risk of malaria re-emergence in southern France

A multi-agent simulation (MAS) was developed to assess the risk of malaria re-emergence in the Camargue in southern France, a non-endemic area where mosquitoes of the genus Anopheles (Culicidae) live. The contact rate between people and potential malaria vectors, or the human biting rate, is one of the key factor to predict the risk of re-emergence of malaria, would the parasite be introduced in the region. Our model (called MALCAM) represents the different agents that could influence malaria transmission in the Camargue – people, mosquitoes, animal hosts and the landscape – in a spatially explicit environment. The model simulates spatial and temporal variations in human biting rate at the landscape scale. These variations depend on the distribution of people and potential vectors, their behaviour and their interactions. A land use/cover map was used as a cellular-spatial support for the movements of and interactions between mobile agents. The model was tested for its sensitivity to variations in parameter values, and for the agreement between field observations and model predictions. The MALCAM model provides a tool to better understand the interactions between the multiple agents of the disease transmission system, and the land use and land cover factors that control the spatial heterogeneity in these interactions. It allows testing hypotheses and scenarios related to disease dynamics by varying the value of exogenous biological, geographical, or human factors. This application of agent-based modelling to a human vector-borne disease can be adapted to different diseases and regions.     

Linking richness, community variability, and invasion resistance with patch size

The influence of community dynamics on the success or failure of an invasion is of considerable interest. What has not been explored is the influence of patch size on the outcomes of invasions for communities with the same species pool. Here we use an empirically validated spatial model of a marine epibenthic community to examine the effects of patch size on community variability, species richness, invasion, and the relationships between these variables. We found that the qualitative form of the relationship between community variability and species richness is determined by the size of the model patch. In small patches, variability decreases with species richness, but beyond a critical patch size, variability increases with increasing richness. This occurs because in large patches large, long-lived colonies attain sufficient size to minimize mortality and dominate the community, leading to decreased species richness and community variability. This mechanism cannot operate on smaller patches where the size of colonies is limited by the patch size and mortality is high irrespective of species identity. Further, invasion resistance is strongly correlated with community variability. Thus, the relationship between species richness and invasion resistance is also determined by patch size. These patterns are generated largely by an inverse relationship between colony size and mortality, and they depend on the spatial nature and patch size of the community. Our results suggest that a continuum of possible relationships can exist between species richness, community variability, invasion resistance, and area. These relationships are emergent behaviors generated by the individual properties of the particular component species of a community.     

State-specific detection probabilities and disease prevalence.

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.     

Losers in the ‘Rock-Paper-Scissors’ game: The role of non-hierarchical competition and chaos as biodiversity sustaining agents in aquatic systems

Processes occurring within small areas (patch-scale) that influence species richness and spatial heterogeneity of larger areas (landscape-scale) have long been an interest of ecologists. This research focused on the role of patch-scale deterministic chaos arising in phytoplankton assemblages characteristic of “Rock-Paper-Scissors” population dynamics (i.e., competitively non-hierarchical). We employed a simple 2-patch model configuration with lateral mixing and through-flow, and tested the robustness of species richness at the scale of the landscape and spatial heterogeneity. Three different assemblages were used that in a dimensionless box model configuration exhibited chaotic behavior. Our results showed that when a spatial dimension was added to the model configuration, and when all species were shared between patches (i.e., no invading populations), chaos-induced species richness and spatial heterogeneity were quickly reduced with the onset of mixing. While assemblages in each patch were comprised of exactly the same species, they differed in their proportional population densities due to differing stages of succession and the incidence of alternative assemblage structures. Even at very low mixing rates (0.001 d⁻¹), which produced low passive migration rates (0.1% of the total biomass per day), the incidence of high richness and heterogeneity decreased by ∼80%. Interestingly, this sensitivity was not the same for the three assemblages tested. Declines in species richness and spatial heterogeneity associated with mixing were greater in assemblages comprised of competitively dissimilar species (based on the area occupied in the resource-tradeoff space defined by the R* model). The underlying mechanisms may involve the degree to which nutrient dynamics are altered with the arrival of immigrants. Our findings suggest that in partially to well-mixed aquatic systems, the roles of patch-scale non-hierarchical competition and chaos as factors maintaining species richness and spatial heterogeneity may be limited. However, in aquatic systems that experience periods of very low mixing, or even disconnection, non-hierarchical competition and chaos might indeed contribute significantly to biodiversity.     

Extrinsic regime shifts drive abrupt changes in regeneration dynamics at upper treeline in the Rocky Mountains, U.S.A

Given the widespread and often dramatic influence of climate change on terrestrial ecosystems, it is increasingly common for abrupt threshold changes to occur, yet explicitly testing for climate and ecological regime shifts is lacking in climatically sensitive upper treeline ecotones. In this study, quantitative evidence based on empirical data is provided to support the key role of extrinsic, climate-induced thresholds in governing the spatial and temporal patterns of tree establishment in these high-elevation environments. Dendroecological techniques were used to reconstruct a 420-year history of regeneration dynamics within upper treeline ecotones along a latitudinal gradient (approximately 44-35 degrees N) in the Rocky Mountains. Correlation analysis was used to assess the possible influence of minimum and maximum temperature indices and cool-season (November-April) precipitation on regional age-structure data. Regime-shift analysis was used to detect thresholds in tree establishment during the entire period of record (1580-2000), temperature variables significantly Correlated with establishment during the 20th century, and cool-season precipitation. Tree establishment was significantly correlated with minimum temperature during the spring (March-May) and cool season. Regime-shift analysis identified an abrupt increase in regional tree establishment in 1950 (1950-1954 age class). Coincident with this period was a shift toward reduced cool-season precipitation. The alignment of these climate conditions apparently triggered an abrupt increase in establishment that was unprecedented during the period of record. Two main findings emerge from this research that underscore the critical role of climate in governing regeneration dynamics within upper treeline ecotones. (1) Regional climate variability is capable of exceeding bioclimatic thresholds, thereby initiating synchronous and abrupt changes in the spatial and temporal patterns of tree establishment at broad regional scales. (2) The importance of climate parameters exceeding critical threshold values and triggering a regime shift in tree establishment appears to be contingent on the alignment of favorable temperature and moisture regimes. This research suggests that threshold changes in the climate system can fundamentally alter regeneration dynamics within upper treeline ecotones and, through the use of regime-shift analysis, reveals important climate-vegetation linkages.