A case study of bats and white‐nose syndrome demonstrating how to model population viability with evolutionary effects

Ecological factors generally affect population viability on rapid time scales. Traditional population viability analyses (PVA) therefore focus on alleviating ecological pressures, discounting potential evolutionary impacts on individual phenotypes. Recent studies of evolutionary rescue (ER) focus on cases in which severe, environmentally induced population bottlenecks trigger a rapid evolutionary response that can potentially reverse demographic threats. ER models have focused on shifting genetics and resulting population recovery, but no one has explored how to incorporate those findings into PVA. We integrated ER into PVA to identify the critical decision interval for evolutionary rescue (DIER) under which targeted conservation action should be applied to buffer populations undergoing ER against extinction from stochastic events and to determine the most appropriate vital rate to target to promote population recovery. We applied this model to little brown bats (Myotis lucifugus) affected by white‐nose syndrome (WNS), a fungal disease causing massive declines in several North American bat populations. Under the ER scenario, the model predicted that the DIER period for little brown bats was within 11 years of initial WNS emergence, after which they stabilized at a positive growth rate (λ = 1.05). By comparing our model results with population trajectories of multiple infected hibernacula across the WNS range, we concluded that ER is a potential explanation of observed little brown bat population trajectories across multiple hibernacula within the affected range. Our approach provides a tool that can be used by all managers to provide testable hypotheses regarding the occurrence of ER in declining populations, suggest empirical studies to better parameterize the population genetics and conservation‐relevant vital rates, and identify the DIER period during which management strategies will be most effective for species conservation.     

Variation in plasma levels of insulin-like growth factor-I (IGF-I) in lingcod: relationships among season,size, and gonadal steroids

The physiological response of a fish to its environment is mediated through the endocrine axis controlling growth. Therefore, growth-regulating hormone levels can serve as ecologically relevant indicators of fish growth rate. We quantified variation in plasma insulin-like growth factor-I (IGF-I) to evaluate its potential as an indicator of growth in lingcod, an economically and ecologically important bottomfish species in the northeast Pacific. An information-theoretic model selection approach was used to test the hypothesis that variation in lingcod IGF-I is related to season, body size, and gonadal steroid concentration. Season and a length × season interaction were the most important predictors of plasma IGF-I among the variables we evaluated, suggesting that season and body size should be explicitly accounted for when interpreting endocrine patterns in wild fish populations. This is among the few studies that have measured and interpreted patterns of IGF-I in wild fish and the first to describe seasonal endocrine profiles in lingcod.     

A novel application of Approximate Bayesian Computation for detecting male reproductive advantages due to mating order

Studies of the effects of mating order on fertilization success, classically analyzed as the proportional paternity of the second male, have advanced our understanding of the relative influences of postcopulatory male–male competition and female choice on sexual selection. However, results from these studies are often difficult to analyze because (1) distributions of offspring per dam rarely follow a normal distribution and (2) proportional paternities are never normally distributed. Previous studies partially account for these limitations by using nonparametric statistics. However, behavioral studies are often plagued by relatively small sample sizes and require a more powerful analytical approach. Here, we develop a new analytical framework for studying fertilization bias. Our Approximate Bayesian Computational (ABC) model overcomes many of the limitations of currently employed methods. We apply our model to analyze the effects of male mating order on paternity success in the brown anole lizard, Anolis sagrei. Using our ABC simulation, we find a marked first-male advantage: first males sired approximately 80 % of the offspring in our study. Next, based on re-analysis of four previously published datasets, we show that traditional statistical methods often over- or underestimate biases related to mating order. Moreover, by comparing our model to more traditional statistical tests, we show that the ABC method is robust to relatively small samples sizes and should therefore be useful for studying mating-order effects in a variety of systems. Our model is implemented as an R package, ABCp2, and is freely available for use.     

Measuring copepod naupliar abundance in a subtropical bay using quantitative PCR

Copepod nauplii are important in plankton food web dynamics, but limited information is available about their ecology due to methodological challenges. Reported here is a new molecular method that was developed, optimized, and tested in laboratory and field samples that uses quantitative PCR (qPCR) to identify and estimate the abundance of nauplii of the planktonic copepod, Parvocalanus crassirostris. The overall approach included collection of bulk zooplankton samples in the field, size fractionation to create artificial cohorts of relatively few developmental stages, obtaining DNA copy number for each size fraction by qPCR amplification of a target gene region, and estimation of the number of animals in each fraction through application of known DNA copy number across developmental stage. Method validation studies found that our qPCR-based approach has comparable accuracy to microscope-based counts of early developmental stages. Naupliar abundance estimates obtained using the two methods on cultured populations were similar; the regression of qPCR estimates on microscope-based counts resulted in a nearly 1:1 ratio (slope = 1.09). The qPCR-based method is superior to traditional identification and quantification methods for nauplii due to its higher taxonomic resolution, sensitive detection over a range of DNA quantities, and relatively high throughput sample processing.     

Fractal characterization of three-dimensional zooplankton swimming trajectories

Several natural processes, such as swimming and flying, occur in a three-dimensional reference frame and thus describe three-dimensional trajectories. Analysing such tracks is no easy task. To this aim, here we propose a new technique, based on the box-counting approach, by which to estimate the three-dimensional fractal dimension (D_3D) of spatially-evolving routes. This technique has been preliminary tested on two sets of random walks (pure and correlated). Then, our approach has been utilised to characterise the swimming trajectories performed by the freshwater cladoceran Daphnia pulex under two light conditions.Morphologically different tracks attain statistically different D_3D values, smoother paths having lower values than more tortuous ones; therefore, our proposed methodology proves to be fruitful in direct comparisons. Moreover D_3D can highlight bizarre situations, in which differently convoluted tracks are characterised by the same degree of contortion.     

The link between social network density and rank-order consistency of aggressiveness in juvenile eels

The emergence of an animal’s personality is the result of interactions between genetics, environment and experience. It is known that individuals are able to modulate their behaviour according to the context or the social environment. Many studies have shown for example, that familiarity among conspecifics diminishes aggressiveness, although little is known about the underlying processes. Nevertheless, personality traits have long been determined while ignoring the social context, especially in lower vertebrates such as fish. In the present experiment, we hypothesize that group connections (network density) may be positively correlated to consistency of aggressiveness by avoiding over-aggressive acts in further encounters. To test this hypothesis, we used eels (Anguilla anguilla) as a model species and monitored both aggressiveness and sociability in 64 individuals over their first 7 months of growth from the glass eel stage. As expected, social fish were less aggressive than their non-social counterparts at all times, highlighting the existence of a behavioural syndrome in eels. Additionally, rank-order consistency of aggressiveness was higher in groups of fish with high social connectivity, compared to those in less-connected fish groups. While aggressiveness must be consistent to be considered a personality trait, our results suggest that both aggressiveness and its consistency are influenced by initial social context.     

Populations of the Sydney rock oyster, Saccostrea glomerata, vary in response to ocean acidification

Acidifying oceans are predicted to fundamentally alter marine ecosystems. Over the next century, acute studies suggest that the impacts of climate change on marine organisms and ecosystems may be catastrophic. To date, however, little is known about whether the response of marine organisms varies within a species and whether this provides a potential ??adaptive capacity??. Here, we show that selectively bred lines of the ecologically and economically important estuarine mollusc, the Sydney rock oyster Saccostrea glomerata, are more resilient to ocean acidification than the wild populations. When reared at elevated pCO₂, we found a 25% reduction in shell growth of the selectively bred population of the Sydney rock oyster, Saccostrea glomerata, compared to a 64% reduction in shell growth of wild populations. This study shows that there are significantly different sensitivities to ocean acidification even within the same species, providing preliminary evidence that selective breeding may be a solution for important aquaculture industries to overcome the future effects of ocean acidification.     

Population dynamics models based on cumulative density dependent feedback: A link to the logistic growth curve and a test for symmetry using aphid data

Density dependent feedback, based on cumulative population size, has been advocated to explain and mathematically characterize “boom and bust” population dynamics. Such feedback results in a bell-shaped population trajectory of the population density. Here, we note that this trajectory is mathematically described by the logistic probability density function. Consequently, the cumulative population follows a time trajectory that has the same shape as the cumulative logistic function. Thus, the Pearl–Verhulst logistic equation, widely used as a phenomenological model for density dependent population growth, can be interpreted as a model for cumulative rather than instantaneous population. We extend the cumulative density dependent differential equation model to allow skew in the bell-shaped population trajectory and present a simple statistical test for skewness. Model properties are exemplified by fitting population trajectories of the soybean aphid, Aphis glycines. The linkage between the mechanistic underpinnings of the logistic probability density function and cumulative distribution function models could open up new avenues for analyzing population data.     

Diameter growth models for mixed-species stands of Coastal British Columbia including thinning and fertilization effects

In this study, diameter growth models for three species growing in mixed-stands of Coastal British Columbia (BC), Canada, under a variety of silvicultural treatments were developed. The three species were: Douglas-fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western redcedar (Thuja plicata Donn). A Box and Lucas model (1959) was initially fitted to the diameter growth series for each tree, as this model is very flexible and was based on processes reflective of the metabolic processes governing tree growth. Next, a random coefficients modelling approach (i.e., parameter prediction approach) was used to modify the estimated parameters for each species using functions of tree size and stage of development, site productivity, and inter-tree competition variables, while accounting for temporal correlation within trees. Impacts of fertilization on diameter growth were estimated by including the time since fertilization as an additional variable. Since state variables that are changed as a result of thinning were already in the model, accurate results post-thinning were obtained with no changes to the model. For the combined effects of thinning and fertilization, a two-step additive approach was used, where the state variables were changed following thinning and the diameter increment was modified for fertilization using the time since fertilization variable. Results indicated that multiple treatments sustain a change in growth for a longer time period following treatment than thinning or fertilization alone.     

Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)

Several studies have proven the importance of field margins in sustaining biodiversity and other work has been done on the effect of field management on field margin flora. However few models have been built to predict the effects of field management on the flora. Our project addresses this need for a model capable of predicting the effect of cropping techniques and their timing on the flora of field margins. Primula vulgaris is a biodiversity indicator, characteristic of undisturbed flora and found in field margins and woodlands: its population has been declining for several years. We created a temporal matrix model of P. vulgaris populations on field margins, taking into account the effects of field, field margin and roadside management based on literature and expert knowledge. We then analysed its sensitivity to demographic parameters by comparing lambda (growth rate) sensitivity and elasticity. We compared the management parameter effect using the relative growth rate of the population after 6 years of simulation. Sensitivity analysis to biological parameters showed the importance of adult survival and seed production and germination. Results show that P. vulgaris is particularly sensitive to broad-spectrum herbicides and that other management techniques like early mowing, scything and scrub-killer (diluted broad-spectrum herbicide or specific herbicide) are less aggressive. Our simulations show that management of cash crops in Brittany is too aggressive for P. vulgaris populations and that 4-5 years of grassland in the adjacent field are necessary to maintain populations.     

Développement “printanier” de la diatomée Rhizosolenia delicatula près de Roscoff

Rhizosolenia delicatula (Cleve) is not very often quantitatively recorded, although frequently mentioned in plankton investigations in European waters. Recent studies at Roscoff (France) place it among the dominant species in the seasonal cycle. R. delicatula is present most of the year. It flowered in May/June every year from 1962 to 1966 at a rate of cell division in accordance with exponential growth. This bloom falls in with the main seasonal bloom of phytoplankton as cell numbers and chlorophyll a. Detailed study of the growth in 1966 shows that horizontal transport exists due to spring and neap tide alternations. Highest records of cell numbers coincide with highest tidal coefficients. By comparing environmental conditions each year at the time growth takes place, optimal growth conditions were defined as follows: temperature 12° to 13°C, salinity 35‰, light 0.07 to 0.09 cal.g/cm²/min. Phosphate is not a limiting factor. After exponential growth, the species seems to be controlled by grazing. R. delicatula has a definite place in both the hydrographical cycle and plancton succession. It is the first noticeable species of the summer diatom suecession. R. fragilissima precedes R. delicatula in the succession, but has no such successful development. These two species exhibit the highest cell surface/volume ratios. The annual regularity in the appearance and growth of R. delicatula suggests that this species, an autochtonous one, actively increases in numbers when optimal conditions, as defined, occur. This development, when microplancton diversity is lowest, is not linked with water transportation. As incident light and temperature increase, primary production (as expected) increases also. At the same time, the structure of the community is changing; the species diversity increases.     

A new index for measuring perpendicularity of animal movements in relation to patch boundaries

We introduce a new index for measuring perpendicularity of animal movements with respect to a boundary (e.g., a habitat patch edge), and provide a computer algorithm for its calculation. Our index, η, improves on an approach that measures perpendicularity with respect to a fixed boundary direction. This is because η accounts for moment-to-moment trajectories relative to nearest-neighbor boundary attributes at the scale of an animal's movement. Our algorithm prp calculates η efficiently and accurately with both synthetic data and large telemetry datasets. In addition, we have included routines in prp which account for scenarios inherently problematic to perpendicularity estimators.     

Parsnip webworms and host plants at home and abroad: trophic complexity in a geographic mosaic

Due to differences in the structure of communities in which interactions are embedded, the intensity of interactions between species may vary with location; thus, what results from differences in outcomes and in degree of specialization is a geographic mosaic, which provides the raw material for divergent coevolutionary trajectories. Where selection intensity is great, reciprocal responses are likely in so-called "hotspots"; in contrast, where selection pressures are relaxed, reciprocal responses in "coldspots" are far less likely to occur. There are few if any studies examining how a gradient of increasing trophic complexity might influence the probability of phenotype matching and, correspondingly, the "temperature" of the coevolutionary interaction. This study was conducted to compare outcomes of the interaction between wild parsnip (Pastinaca sativa) and parsnip webworm (Depressaria pastinacella) in its indigenous area, Europe, to its area of introduction, the midwestern United States. Specifically, we tested the hypothesis that increasing trophic complexity, represented by alternate host plants or the presence of natural enemies, reduces the selective impact of parsnip webworms and hence diminishes linkage between host plant chemistry and webworms that would be expected in coevolutionary hotspots. This comparison of a two-species interaction in its area of introduction and its area of indigeneity revealed common patterns that are more reflective of interaction temperature than of continental origin. Where webworms are rare, parsnips produce lower levels of xanthotoxin and bergapten in both the midwestern United States and Netherlands populations. However, the most striking result from this intercontinental comparison is that what is a ubiquitous two-species interaction in North America is in fact exceptional in Europe; webworms could more reliably be found infesting H. sphondylium even where P. sativa was available as well. This preference for H. sphondylium exists despite the comparatively high probability of parasitism associated with this host plant and may reflect the overall lower furanocoumarin content of H. sphondylium. The interaction of parsnip webworms and wild parsnips at home and away demonstrates clearly the potential for rapid contemporary evolution of chemical traits upon re-association with a coevolved enemy, a potential evolutionary outcome that should be considered in the design and implementation of future weed biological control programs.     

Proposing an information criterion for individual-based models developed in a pattern-oriented modelling framework

Individual-based models (IBMs) have been improved in quality and reliability in recent years with an approach called pattern-oriented modelling (POM). POM proposes guidelines to develop models reproducing multiple patterns observed on the field and to test systematically how well the IBMs reproduce them. POM studies used generally traditional methods of goodness of fit such as the sum of squares evaluation or ad hoc comparisons of fitting errors and variations. Model selection, however, can be a rigorous statistical approach based on information theory and information criteria such as the Akaike's information criterion (AIC) or the deviance information criterion (DIC). So far, it has not been tried to link POM to these rigorous techniques. The main problems to achieve that are: (a) the difficulty to have likelihood functions for IBMs’ parameters and (b) the possibility to obtain posterior distributions of IBMs’ parameters given the patterns to reproduce. In a first part, this paper answers problem (a) by proposing and explaining how to calculate a deviance measure (POMDEV) for models developed in a context of POM. And while answering the second problem, a second part of the paper proposes an information criterion for model selection in a POM context (the pattern-oriented modelling information criterion: POMIC). This criterion does not yet have the same theoretical foundation as, e.g., AIC, but uses formal analogies to the DIC. In a third part POMIC is tested with a modelling exercise. This exercise shows the potential of POMIC to use multiple patterns for selecting among multiple potential submodels and eventually select the most parsimonious and well fitting model version. We conclude that POMIC, although being a heuristically derived approach, can greatly improve the POM framework.     

Estimating dyad association probability under imperfect and heterogeneous detection

In animal behaviour studies, association indices estimate the proportion of time two individuals (i.e. a dyad) spend in association. In terms of dyads, all association indices can be interpreted as estimators of the probability that a dyad is associated. However, traditional indices rely on the assumptions that the probability to detect a particular individual (p) is either approximately one and/or homogeneous between associated and not associated individuals. Based on marked individuals we develop a likelihood based model to estimate the probability a dyad is associated (ψ) accounting for p < 1 and possibly varying between associated and not associated individuals. The proposed likelihood based model allows for both individual and dyadic missing observations. In addition, the model can easily be extended to incorporate covariate information for modeling p and ψ. A simulation study showed that the likelihood based model approach yield reasonably unbiased estimates, even for low and heterogeneous individual detection probabilities, while, in contrast, traditional indices showed moderate to strong biases. The application of the proposed approach is illustrated using a real data set collected from a population of Commerson's dolphin (Cephalorhynchus commersonii) in Patagonia Argentina. Finally, we discuss possible extensions of the proposed model and its applicability in animal behaviour and ecological studies.     

Post-evaluation of a water pollution control plan: methodology and case study

China has developed more than 20 water pollution control plans for river basins (RBWPs) since 1996. However, the implementation has generally lagged. This paper proposes a three-step, post-evaluation methodology to analyze the implementation result of a RBWP and its influential factors. First, a multi-attribute evaluation method based on an index system is established to score the enforcement results of a RBWP. Indicators measure how well a RBWP has achieved its objectives, which include water quality compliance, pollution load control, project construction, financial inputs, and related management requirements. Second, an interpretive structural model is used to detect the significant factors that affect RBWP implementation. This model can effectively analyze the cause-effect chain and hierarchical relationship among variables. Five groups of factors were identified, namely, plan preparation, water resource endowment, policy, institution, and management. Both qualitative and quantitative methods are employed in the third step to evaluate the extent to which these factors have influenced the execution result of a RBWP, including pre-post contrast, scenario analysis, and correlation analysis. This research then post-evaluated the implementation of the Huai River Basin water pollution control plans (H-RBWPs) over a period of 10 years as a case study. Results showed that the implementation of the H-RBWPs was unsatisfactory during 2001–2005, although it improved during 2006–2010. The poor execution of these plans was partially caused by the underestimation of regional economic development in combination with ineffective industrial structure adjustment policies. Therefore, this case study demonstrates the feasibility and flexibility of the proposed post-evaluation methodology.     

A Framework for Assessing Supply‐Side Wildlife Conservation

Market‐based, supply‐side interventions such as domestication, cultivation, and wildlife farming have been proposed as legal substitutes for wild‐collected plants and animals in the marketplace. Based on the literature, we devised a list of the conditions under which supply‐side interventions may yield positive conservation outcomes. We applied it to the trade of the orchid Rhynchostylis gigantea, a protected ornamental plant. We conducted a survey of R. gigantea at Jatujak Market in Bangkok, Thailand. Farmed (legal) and wild (illegal, protected) specimens of R. gigantea were sold side‐by‐side at market. These results suggest farmed specimens are not being substituted for wild plants in the marketplace. For any given set of physical plant characteristics (size, condition, flowers), the origin of the plants (wild vs. farmed) did not affect price. For all price classes, farmed plants were of superior quality to wild‐collected plants on the basis of most physical variables. These results suggest wild and farmed specimens represent parallel markets and may not be substitutable goods. Our results with R. gigantea highlight a range of explanations for why supply‐side interventions may lack effectiveness, for example, consumer preferences for wild‐collected products and low financial incentives for farming. Our results suggest that market‐based conservation strategies may not be effective by themselves and may be best utilized as supplements to regulation and education. This approach represents a broad, multidisciplinary evaluation of supply‐side interventions that can be applied to other plant and animal species. Un Marco de Referencia para Evaluar la Oferta de la Conservación de Vida Silvestre     

PyLUR: Efficient software for land use regression modeling the spatial distribution of air pollutants using GDAL/OGR library in Python

• PyLUR comprises four modules for developing and applying a LUR model. • It considers both conventional and novel potential predictor variables. • GDAL/OGR libraries are used to do spatial analysis in the modeling and prediction. • Developed on Python platform, PyLUR is rather efficient in data processing. Land use regression (LUR) models have been widely used in air pollution modeling. This regression-based approach estimates the ambient pollutant concentrations at un-sampled points of interest by considering the relationship between ambient concentrations and several predictor variables selected from the surrounding environment. Although conceptually quite simple, its successful implementation requires detailed knowledge of the area, expertise in GIS, statistics, and programming skills, which makes this modeling approach relatively inaccessible to novice users. In this contribution, we present a LUR modeling and pollution-mapping software named PyLUR. It uses GDAL/OGR libraries based on the Python platform and can build a LUR model and generate pollutant concentration maps efficiently. This self-developed software comprises four modules: a potential predictor variable generation module, a regression modeling module, a model validation module, and a prediction and mapping module. The performance of the newly developed PyLUR is compared to an existing LUR modeling software called RLUR (with similar functions implemented on R language platform) in terms of model accuracy, processing efficiency and software stability. The results show that PyLUR out-performs RLUR for modeling in the Bradford and Auckland case studies examined. Furthermore, PyLUR is much more efficient in data processing and it has a capability to handle detailed GIS input data.     

Dynamics of insect resistance in Bt-corn

The development of genetically modified Bt-corn, incorporating various toxin genes from Bacillus thuringiensis that act as a chemical defense against insect pests, such as the European Corn Borer, provides farmers with a new pest management option. However, the emergence of insect resistance is a threat to the continued use of Bt-corn. The United States Environment Protection Agency (US EPA) has developed planting strategies, for preventing insect resistance by planting a mixture of Bt- and non-Bt-corn. Decisions about the exact proportion of Bt- and non-Bt-corn are based on complex spatially explicit mathematical models using detailed biological assumptions about the population genetics and life history of the European Corn Borer. We develop an alternative simpler model for the spread of resistance based on the logistic growth model, which we believe has utility in situations where it is impossible or impractical to estimate the different life history and genetics parameters required by more detailed models. We use our model to investigate the US EPA’s planting rules for Bt-corn and find that short-term economic behavior is likely to lead to these rules not being followed. Our results add weight to existing work on this problem. We also investigate the economics of planting Bt-corn in markets where consumers do and do not differentiate between the modes of production for the corn. We find that Bt-corn appears to be economic in markets that do not differentiate and uneconomic in markets where consumers do differentiate.