Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?

An important decision in presence-only species distribution modeling is how to select background (or pseudo-absence) localities for model parameterization. The selection of such localities may influence model parameterization and thus, can influence the appropriateness and accuracy of the model prediction when extrapolating the species distribution across time and space. We used 12 species from the Australian Wet Tropics (AWT) to evaluate the relationship between the geographic extent from which pseudo-absences are taken and model performance, and shape and importance of predictor variables using the MAXENT modeling method. Model performance is lower when pseudo-absence points are taken from either a restricted or broad region with respect to species occurrence data than from an intermediate region. Furthermore, variable importance (i.e., contribution to the model) changed such that, models became increasingly simplified, dominated by just two variables, as the area from which pseudo-absence points were drawn increased. Our results suggest that it is important to consider the spatial extent from which pseudo-absence data are taken. We suggest species distribution modeling exercises should begin with exploratory analyses evaluating what extent might provide both the most accurate results and biologically meaningful fit between species occurrence and predictor variables. This is especially important when modeling across space or time—a growing application for species distributional modeling.     

The effect of species response form on species distribution model prediction and inference

Ecological theory and current evidence support the validity of various species response curves according to a variety of environmental gradients. Various methods have been developed for building species distribution models but it is not well known how these methods perform under various assumptions about the form of the underlying species response. It is also not well known how spatial correlation in species occurrence affects model performance. These effects were investigated by applying an environmental envelope method (BIOCLIM) and three regression-based methods: logistic regression (LR), generalized additive modelling (GAM), and classification and regression tree (CART) to simulated species occurrence data. Each simulated species was constructed as a sum of responses with varying weights. Three basic species response curves were assumed: Gaussian (bell-shaped), Beta (skew) and linear. The two non-linear responses conform to standard ecological niche theory. All three responses were applied in turn to three simulated environmental variables, each with varying degrees of spatial autocorrelation. GAM produced the most consistent model performance over all forms of simulated species response. BIOCLIM and CART were inclined to underrate the performance of variables with a linear response. BIOCLIM was less sensitive to data density. LR was susceptible to model misspecification. The use of a linear function in LR underestimated the performance of variables with non-linear species response and contributed to increased spatial autocorrelation in model residuals. Omission of important environmental variables with non-linear species response also contributed to increased spatial autocorrelation in model residuals. Adding a spatial autocovariate term to the LR model (autologistic model) reduced the spatial autocorrelation and improved model performance, but did not correct the misidentification of the dominant environmental determinant. This is to be expected since the autologistic approach was designed primarily for prediction and not for inference. Given that various forms of species response to environmental determinants arise commonly in nature: (1) higher order functions should always be tested when applying LR in modelling species distribution; (2) spatial autocorrelation in species distribution model residuals can indicate that environmental determinants with non-linear response are missing from the model; and (3) deficiencies in LR model performance due to model misspecification can be addressed by adding a spatial autocovariate to the model, but care should be taken when interpreting the coefficients of the model parameters.     

Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?

Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges because (i) they typically violate SDM's assumption that the organism is in equilibrium with its environment, and (ii) species absence data are often unavailable or believed to be too difficult to interpret. This often leads researchers to generate pseudo-absences for model training or utilize presence-only methods, and to confuse the distinction between predictions of potential vs. actual distribution. We examined the hypothesis that true-absence data, when accompanied by dispersal constraints, improve prediction accuracy and ecological understanding of iSDMs that aim to predict the actual distribution of biological invasions. We evaluated the impact of presence-only, true-absence and pseudo-absence data on model accuracy using an extensive dataset on the distribution of the invasive forest pathogen Phytophthora ramorum in California. Two traditional presence/absence models (generalized linear model and classification trees) and two alternative presence-only models (ecological niche factor analysis and maximum entropy) were developed based on 890 field plots of pathogen occurrence and several climatic, topographic, host vegetation and dispersal variables. The effects of all three possible types of occurrence data on model performance were evaluated with receiver operating characteristic (ROC) and omission/commission error rates. Results show that prediction of actual distribution was less accurate when we ignored true-absences and dispersal constraints. Presence-only models and models without dispersal information tended to over-predict the actual range of invasions. Models based on pseudo-absence data exhibited similar accuracies as presence-only models but produced spatially less feasible predictions. We suggest that true-absence data are a critical ingredient not only for accurate calibration but also for ecologically meaningful assessment of iSDMs that focus on predictions of actual distributions.     

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.     

Modelling the effects of litter decomposition on tree diversity patterns

Current theories may not fully explain why latitudinal patterns of plant diversity differ between terrestrial and flooded ecosystems. Moreover, the co-occurrence of hyper diverse stands in lowland tierra firma (not inundated) forests and almost monospecific stands in mangroves and gallery riparian vegetation within the tropics remains enigmatic. Building on evidence from ecology and agriculture, we present a new model investigating the hypothesis that, besides the general positive feedback of plant growth by nutrients release, litter decomposition builds up an intra-specific negative feedback functionally linked with tree diversity. The model results were compared with extensive published data sets both across and within latitudinal zones. The model predicts correctly the biomass production and decomposition process, as well as the number of tree species, their relative abundance in all environmental conditions providing a novel, putative explanation also for the diversity variations observed within the tropics. The model demonstrates a possible mechanistic link between the carbon cycle and biodiversity patterns, which is interesting in the debate about advancing in the direction of a unifying ecosystem theory.     

Identifying key life-traits for the dynamics and gene flow in a weedy crop relative: Sensitivity analysis of the GeneSys simulation model for weed beet (Beta vulgaris ssp. vulgaris)

The benefits of genetically modified herbicide-tolerant (GMHT) sugar beet (Beta vulgaris) varieties stem from their presumed ability to improve weed control and reduce its cost, particularly targeting weed beet, a harmful annual weedy form of the genus Beta (i.e. B. vulgaris ssp. vulgaris) frequent in sugar beet fields. As weed beet is totally interfertile with sugar beet, it is thus likely to inherit the herbicide-tolerance transgene through pollen-mediated gene flow. Hence, the foreseeable advent of HT weed beet populations is a serious threat to the sustainability of GM sugar beet cropping systems. For studying and quantifying the long-term effects of cropping system components (crop succession and cultivation techniques) on weed beet population dynamics and gene flow, we developed a biophysical process-based model called GeneSys-Beet in a previous study. In the present paper, the model was employed to identify and rank the weed life-traits as function of their effect on weed beet densities and genotypes, using a global sensitivity analysis to model parameters. Monte Carlo simulations with simultaneous randomization of all life-trait parameters were carried out in three cropping systems contrasting for their risk for infestation by HT weed beets. Simulated weed plants and bolters (i.e. beet plants with flowering and seed-producing stems) were then analysed with regression models as a function of model parameters to rank processes and life-traits and quantify their effects. Key parameters were those determining the timing and success of growth, development, seed maturation and the physiological end of seed production. Timing parameters were usually more important than success parameters, showing for instance that optimal timing of weed management operations is more important than its exact efficacy. The ranking of life-traits though depended on the cropping system and, to a lesser extent, on the target variable (i.e. GM weeds vs. total weed population). For instance, post-emergence parameters were crucial in rotations with frequent sugar beet crops whereas pre-emergence parameters were most important when sugar beet was rare. In the rotations with frequent sugar beet and insufficient weed control, interactions between traits were small, indicating diverse populations with contrasted traits could prosper. Conversely, when sugar beet was rare and weed control optimal, traits had little impact individually, indicating that a small number of optimal combinations of traits would be successful. Based on the analysis of sugar beet parameters and genetic traits, advice for the future selection of sugar beet varieties was also given. In climatic conditions similar to those used here, the priority should be given to limiting the presence of hybrid seeds in seed lots rather than decreasing varietal sensitivity to vernalization.     

Natural and anthropogenic influences on the diversity structure of reef fish communities in the Tuamotu Archipelago (French Polynesia)

Despite the rapid rate of human-induced species losses, the relative influence of natural and anthropogenic factors on the functional diversity of species assemblages remains unknown for most ecosystems. A model was previously developed to predict the diversity structure of coral reef fish assemblages in 10 atolls of low human pressure and contrasting morphology of the Tuamotu Archipelago (French Polynesia). This existing model predicted smoothed histograms (spectra) of species richness according to size classes, diet classes and life-history classes of fish assemblages using a combination of environmental characteristics at different spatial scales. The present study applied the model to Tikehau, another atoll of the same archipelago where commercial fishing is practiced and where the same sampling strategy was reproduced. Significant differences appeared between predicted and observed species richness in several size, diet and life-history classes of fish assemblages in Tikehau. Two parameters which were not accounted for in the initial model, i.e. fishing pressure and atoll position within the archipelago, explained together 63% of variance in model residuals, >60% being explained by fishing pressure only. The respective effects of fishing and atoll position on the diversity of coral reef fish assemblages are discussed, with the potential of such modelling approach to assess the relative importance of factors affecting functional diversity within communities.     

Do great tits rely on inadvertent social information from blue tits? A habitat selection experiment

Sympatric species sharing requirements are competitors, but recent evidence suggests that heterospecifics may also be used as a source of information. The heterospecific habitat copying hypothesis proposes that individuals of one species might use information inadvertently produced by the breeding performance of individuals of other species to assess habitat quality whenever the two species share needs. In this study, we provide the first experimental test of this hypothesis by examining whether the manipulated reproductive success of blue tits (Cyanistes caeruleus) is used as heterospecific inadvertent social information (ISI) in breeding-habitat selection by sympatric great tits (Parus major). The reproductive success of blue tits was manipulated 1year at the scale of patches by transferring nestlings from decreased to increased patches. No evidence was found of great tits using the reproductive success of blue tits as a source of heterospecific ISI. However, dispersal decisions by adult great tits correlated with information on con- and heterospecific densities, which constitute other sources of ISI. As density and breeding performance are tightly intertwined forms of information, the difficulty in distinguishing between them might lead great tits to use heterospecific ISI more in the form of density than breeding performance when making dispersal decisions.     

A Comprehensive Approach to Identifying Monitoring Priorities of Small Landbirds on Military Installations

Military installations provide important native habitat for songbirds, including many species that have experienced population declines in recent decades. As part of the Land Condition Trend Analysis (LCTA) program to monitor animal populations on military lands, we surveyed small (<250 g) breeding landbirds on 60 permanent plots on the Fort Riley Military Installation in northeastern Kansas from 1991 to 2002. During this period, species richness averaged 39.0 species (SE 0.9)/year and mean species richness per plot ranged from 3.6 species (SE=0.2)/plot (1999) to 7.5 species (SE=0.3)/plot (1992). Turnover (the appearance and disappearance of species on all plots from one year to the next) ranged from 5 species (2000–2001) to 16 species (1992–1993) and was driven primarily by turnover of woodland species. We developed an index of relative difference (C) to evaluate relative trends of local populations and found that 25 species declined, 15 species increased, and 7 did not change. Based on migration assemblages, more resident species (6 of 10) and more short-distant migrants (9 of 12) decreased than long-distance migrants (10 vs. 11). Our analysis of major vegetation communities on plots showed few changes in the quantity of habitats (grassland vs. woodlands) during the study. Our results indicate that Fort Riley provides important habitats for many landbirds, particularly those that require grasslands for breeding. Several species exhibited local declines when compared to the regional Breeding Bird Survey routes. We offer an approach that evaluates population changes of small landbirds and provides objective inputs for conservation directives. These can be adopted easily for use on military installations (that use LCTA), parks, and wildlife refuges that have data from annual breeding bird surveys.     

Reasons for women's non-uptake of amniocentesis

More than 10 years after a chromosomal anomaly screening programme was set up in France for pregnant women of advanced age, amniocentesis is still a controversial issue. The reasons why eligible women did not utilize the test and whether or not the existence of social welfare coverage determined women's access to prenatal diagnosis were studied. A group of 291 women aged ⩾35 years who recently gave birth to normal liveborns was interviewed by telephone. Among those aged 38 years and over, who automatically qualified for social security coverage, 75 per cent had undergone amniocentesis as opposed to 23 per cent in the 35 to 37-year-old non-covered age group who did not qualify for social security coverage. In both groups, access to amniocentesis was found to depend on the physicians', women's and male partners' attitudes towards prenatal diagnosis and abortion. Among the younger group, the uptake depended mainly on socio-economic factors. Institutional policies should ensure greater equality of access while allowing for individual preferences.