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opencc-zeroAug 2020View details →

Data from: Can the genomics of ecological speciation be predicted across the divergence continuum from host races to species? A case study in Rhagoletis

Studies assessing the predictability of evolution typically focus on short-term adaptation within populations or the repeatability of change among lineages. A missing consideration in speciation research is to determine whether natural selection predictably transforms standing genetic variation within populations into differences between species. Here, we test whether host-related selection on diapause timing anticipates genome-wide differentiation during ecological speciation by comparing ancestral hawthorn and newly formed apple-infesting host races of Rhagoletis pomonella to their sibling species R. mendax that attacks blueberries. The responses of 57,857 single nucleotide polymorphisms in a diapause study on the hawthorn race strongly predicted the direction and magnitude of genomic divergence among the three flies at a field site in Fennville, Michigan, USA. As anticipated, the apple race and R. mendax show parallel changes in the frequencies of putative inversions on three chromosomes associated with the earlier fruiting times of apples and blueberries compared to hawthorns. A diapause experiment on R. mendax revealed compensatory mutations throughout the genome accounting for the earlier eclosion of blueberry, but not apple flies. Thus, a degree of predictability, although not complete, exists in the genomics of diapause across the ecological speciation continuum in Rhagoletis. The generality of this result is placed in the context of other similar systems.

opencc-by-4.0Dec 2016View details →

Competitive growth experiments with a high-lipid Chlamydomonas reinhardtii mutant strain and its wild-type to predict industrial and ecological risks

Key microalgal species are currently being exploited as biomanufacturing platforms using mass cultivation systems. The opportunities to enhance productivity levels or produce non-native compounds are increasing as genetic manipulation and metabolic engineering tools are rapidly advancing. Regardless of the end product, there are both environmental and industrial risks associated to open pond cultivation of mutant microalgal strains. A mutant escape could be detrimental to local biodiversity and increase the risk of algal blooms. Similarly, if the cultivation pond is invaded by a wild-type microalgae or the mutant reverts to wild-type phenotypes, productivity could be impacted. To investigate these potential risks, a response surface methodology was applied to determine the competitive outcome of two Chlamydomonas reinhardtii strains, a wild-type (CC-124) and a high-lipid accumulating mutant (CC-4333), grown in mixotrophic conditions, with differing levels of nitrogen and initial wild-type to mutant ratios. Results of the growth experiments show that mutant cells have double the exponential growth rate of the wild-type in monoculture. However, due to a slower transition from lag phase to exponential phase, mutant cells are outcompeted by the wild-type in every co-culture treatment. This suggests that, under the conditions tested, outdoor cultivation of the C. reinhardtii cell wall-deficient mutant strains does not carry a significant environmental risk to its wild-type in an escape scenario. Furthermore, lipid results show the mutant strain accumulates over 200% more TAGs per cell, at 50 mg/L NH4Cl, compared to the wild-type, therefore, the fragility of the mutant strain could impact on overall industrial productivity.

opencc-zeroNov 2022View details →

Data and Scripts from: Bayesian prediction of multivariate ecology from phenotypic data yields novel insights into the diets of extant and extinct taxa

Morphology often reflects ecology, enabling the prediction of ecological roles for taxa that lack direct observations such as fossils. In comparative analyses, ecological traits, like diet, are often treated as categorical, which may aid prediction and simplify analyses but ignores the multivariate nature of ecological niches. Futhermore, methods for quantifying and predicting multivariate ecology remain rare. Here, we ranked the relative importance of 13 food items for a sample of 88 extant carnivoran mammals, and then used Bayesian multilevel modeling to assess whether those rankings could be predicted from dental morphology and body size. Traditional diet categories fail to capture the true multivariate nature of carnivoran diets, but Bayesian regression models derived from living taxa have good predictive accuracy for importance ranks. Using our models to predict the importance of individual food items, the multivariate dietary niche, and the nearest extant analogs for a set of data-deficient extant and extinct carnivoran species confirms long-standing ideas for some taxa, but yields new insights about the fundamental dietary niches of others. Our approach provides a promising alternative to traditional dietary classifications. Importantly, this approach need not be limited to diet, but serves as a general framework for predicting multivariate ecology from phenotypic traits.

opencc-zeroOct 2022View details →

Evolutionary effects of nitrogen are not easily predicted from ecological responses

Anthropogenic nitrogen (N) addition might alter the evolutionary trajectories of plant populations, in part because it alters the abiotic and biotic environment by increasing aboveground primary productivity, light asymmetry, and herbivory intensity, and reducing plant species diversity. Such evolutionary impacts could be caused by N altering patterns of natural selection (i.e., trait-fitness relationships) and the opportunity for selection (i.e., variance in relative fitness). Because at the community level N addition favors species with light acquisition strategies (e.g., tall species), we predict that N would also increase selection favoring those same traits. We also hypothesize that N could alter the opportunity for selection via its effects on mean fitness and/or competitive asymmetries.To investigate these evolutionary consequences of N, we quantified the strength of selection and the opportunity for selection in replicated populations of the annual grass Setaria faberi Herrm. (giant foxtail) growing in a long-term N addition experiment. We also correlated our measures of selection and opportunity for selection with light asymmetry, diversity, and herbivory intensity to identify the proximate causes of any N effects on evolutionary processes. N addition increased aboveground productivity, light asymmetry, and reduced species diversity. Contrary to expectations, N addition did not strengthen selection for trait values associated with higher light acquisition such as greater height and specific leaf area (SLA); rather, it strengthened selection favoring lower SLA. Increased light asymmetry was associated with stronger selection for lower SLA and lower species diversity was associated with stronger selection for greater height and lower SLA, suggesting a role for these factors in driving N-mediated selection. The opportunity for selection was not influenced by N addition (despite increased mean fitness) but was negatively associated with species diversity. Our results indicate that anthropogenic N enrichment can affect evolutionary processes, but that evolutionary changes in plant traits within populations are unlikely to parallel the shifts in plant traits observed at the community level.

opencc-by-4.0Nov 2023View details →

Results and code associated with «Predictability of ecological and evolutionary dynamics in a changing world»

Below you'll find results and code associated with the following article (*): Bozzuto, C, Ives, AR (2024): Predictability of ecological and evolutionary dynamics in a changing world. Proceedings of the Royal Society B, 291: 20240980. https://doi.org/10.1098/rspb.2024.0980 ABSTRACT: Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship. (*) previously a preprint on bioRxiv: https://doi.org/10.1101/2023.11.01.565089

opencc-zeroApr 2024View details →

Comparative ecological analysis and predictive modeling of tick-borne pathogens

Tick-borne diseases constitute the predominant vector-borne health threat in North America. Recent observations have noted a significant expansion in the range of the black-legged tick (Ixodes scapularis Say, Acari: Ixodidae), alongside a rise in the incidence of diseases caused by its vectored pathogens: Borrelia burgdorferi (Spirochaetales: Spirochaetaceae), Babesia microti (Piroplasmida: Babesiidae), and Anaplasma phagocytophilium (Rickettsiales: Anaplasmataceae), the causative agents of Lyme disease, babesiosis, and anaplasmosis, respectively. Prior research identified environmental features that influence the ecological dynamics of I. scapularis and B. burgdorferi that can be used to predict the distribution and abundance of these organisms, and thus Lyme disease risk. In contrast, there is a paucity of research into the environmental determinants of B. microti and A. phagocytophilium. Here we use over a decade of surveillance data to model the impact of environmental features on the infection prevalence of these increasingly common human pathogens in ticks across New York State (NYS). Our findings reveal a consistent northward and westward expansion of B. microti in NYS from 2009 to 2019, while the range of A. phagocytophilum varied at fine spatial scales. We constructed biogeographic models using data from over 1000 site-year visits and encompassing more than 250 environmental variables to accurately forecast infection prevalence for each pathogen to future years that were not included in model training. Several environmental features were identified to have divergent effects on the pathogens, revealing potential ecological differences governing their distribution and abundance. These validated biogeographic models are immediately useful for disease prevention efforts.

opencc-by-4.0Dec 2021View details →

Figure 5 in Establishment of an expansion-predicting model for invasive alien cerambycid beetle Aromia bungii based on a virtual ecology approach

Figure 5. Map of predicted occurrence units for the whole of Saitama Prefecture using both the river density model and river single model. The degree of shading reflects the theoretical invasion number predicted by each simulation model.

opencc-by-4.0Dec 2021View details →

Figure 4 in Establishment of an expansion-predicting model for invasive alien cerambycid beetle Aromia bungii based on a virtual ecology approach

Figure 4. (a) Map of occurrence records for A. bungii through 2019. (b–g) Predicted occurrence units based on our models for each habitat variable. The degree of shading reflects the theoretical invasion number predicted by each model.

opencc-by-4.0Dec 2021View details →

Figure 2 in Establishment of an expansion-predicting model for invasive alien cerambycid beetle Aromia bungii based on a virtual ecology approach

Figure 2. Basic structure of the cellular automata model. (A) Two values are associated with each cell: 1) the cell ID "x," a unique ID for each cell, and 2) the expansion probability "ex" indicating four directional vectors into adjacent cells (described below). (B) Values e1, e2, e3, and e4 indicate the probability of dispersion using the path to the top, left, bottom, and right cells, respectively. If the dispersion path value is 1, the insect population in this cell can expand to the adjacent cell.

opencc-by-4.0Dec 2020View details →

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A in What are the best modern analogs for ancient South American mammal communities? Evidence from ecological diversity analysis (EDA)

FIGURE 6. Classification Tree results and predictions for the five fossil localities. A) Results and predictions for CT1, vegetative cover. B) Results and predictions for CT2, biogeographic realm. Abbreviations: LV, La Venta; QH, Quebrada Honda; RU, Rümikon; SC, Santa Cruz; TG, Tinguiririca.

opencc-by-4.0Feb 2018View details →

Data and scripts for Predictable Ecological Response to Rising CO2 of a Community of Marine Phytoplankton

Rising atmospheric CO2 and ocean acidification are fundamentally altering conditions for life of all marine organisms, including phytoplankton. Differences in CO2 related physiology between major phytoplankton taxa lead to differences in their ability to take up and utilise CO2. These differences may cause predictable shifts in the composition of marine phytoplankton communities in response to rising atmospheric CO2. We report an experiment in which 7 species of marine phytoplankton, belonging to 4 major taxonomic groups (cyanobacteria, chlorophytes, diatoms and coccolithophores) were grown at both ambient (500 µatm) and future (1000 µatm) CO2 levels. These phytoplankton were grown as individual species, as cultures of pairs of species and as a community assemblage of all seven species in two culture regimes (high-nitrogen batch cultures and lower-nitrogen semi-continuous cultures, though not under nitrogen limitation).  All phytoplankton species tested in this study increased their growth rates under elevated CO2 independent of the culture regime. We also find that, despite species-specific variation in growth response to high CO2, the identity of major taxonomic groups provides a good prediction of changes in population growth and competitive ability under high CO2. The CO2-induced growth response is a good predictor of CO2-induced changes in competition (R2>0.93) and community composition (R2>0.73). This study suggests that it may be possible to infer how marine phytoplankton communities respond to rising CO2 levels from the knowledge of the physiology of major taxonomic groups, but that these predictions may require further characterisation of these traits across a diversity of growth conditions. These findings must be validated in the context of limitation by other nutrients. Also, in natural communities of phytoplankton, numerous other factors that may all respond to changes in CO2, including nitrogen fixation, grazing and variation in the limiting resource will likely complicate this prediction.

opencc-by-4.0Apr 2022View details →

Fig. 4. Predicted lines from a in Ecological drivers of helminth infection patterns in the Virunga Massif mountain gorilla population

Fig. 4. Predicted lines from a generalized linear mixed model for significant effects of (a) the second principal component (PC2), (b) interaction between the first principal component (PC1) and MCP = area of 500-m buffered minimum convex polygon of detected nest sites per gorilla group, (see Minimum convex polygon calculation and Statistical analyses for details) and (c) interaction between monitoring (habituation) status and MCP on tapeworm infection (egg counts per gram in fecal sample). Principal components were computed from 10 correlated environmental variables (see Material and methods for details).

opencc-by-4.0Apr 2022View details →

Fig. 3. Predicted lines from a in Ecological drivers of helminth infection patterns in the Virunga Massif mountain gorilla population

Fig. 3. Predicted lines from a generalized linear mixed model for significant effects of (a) the first (PC1) and (b) second principal component (PC2), (c) Density = mean relative density of gorillas per MCP and (d) MCP = area of 500-m buffered minimum convex polygon of detected nest sites per gorilla group, (see Minimum convex polygon calculation and Statistical analyses for details) on strongylid infection (egg counts per gram in fecal sample). Principal components were computed from 10 correlated environmental variables (see Material and methods for details).

FIGURE 3 in Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts

FIGURE 3 Variation in HeV AUC from flying foxes. (A) The forest plot displays annual estimates and 95% confidence intervals ordered by latitude and year; points are scaled by the inverse sampling variance. The horizontal axis uses a modulus transformation to accommodate wide upper bounds of some confidence intervals. (B) Fitted values and 95% confidence intervals for the top GAM, with raw data (scaled by inverse sampling variance) and modelled means coloured by roost type. Transparency denotes AUC derived from truncated time series (≤20 weeks)

FIGURE 2 Fitted HeV urine pool prevalence and 95 in Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts

FIGURE 2 Fitted HeV urine pool prevalence and 95% confidence intervals from the most parsimonious GAMM with week, seasonal interactions with roost type and previous food shortages, and an adjustment for relative abundance of Pteropus alecto. Weekly data are overlaid, coloured by roost type, and sized by corresponding P. alecto relative abundance. Thin lines show the fitted curves from the random factor smooth including each roost per year

FIGURE 1 in Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts

FIGURE 1 Spatiotemporal variation in HeV shedding for the nine Australian flying fox roosts sampled from 2012 through 2014. Curve height indicates the weekly proportion of HeV-positive urine pools, with roosts shown in order of latitude and coloured by roost type. Ticks show sampling time points. Dark grey shading indicates regional acute food shortage events, and dashed lines with light grey shading indicate the Austral winter (i.e. June through August)

FIGURE 4 in Ecological conditions predict the intensity of Hendra virus excretion over space and time from bat reservoir hosts

FIGURE 4 Spatiotemporal variation in regional HeV spillover events during the flying fox surveillance period (2012–2014) and its relationship with HeV AUC. (a) Maps display the annual distributions of spillovers (coloured by year) in relation to the nine analysed roosts. (b) Modelled relationships between AUC and spillover counts are shown with fitted values and 95% confidence intervals from GAMs for 50, 100, 200, 300, 400 and 500 km buffers of each roost. Raw data are overlaid and scaled by the inverse of the sampling variance for AUC