Phenotypic plasticity of native vs. invasive purple loosestrife: a two-state multivariate approach

The differences in phenotypic plasticity between invasive (North American) and native (German) provenances of the invasive plant Lythrum salicaria (purple loosestrife) were examined using a multivariate reaction norm approach testing two important attributes of reaction norms described by multivariate vectors of phenotypic change: the magnitude and direction of mean trait differences between environments. Data were collected for six life history traits from native and invasive plants using a split-plot design with experimentally manipulated water and nutrient levels. We found significant differences between native and invasive plants in multivariate phenotypic plasticity for comparisons between low and high water treatments within low nutrient levels, between low and high nutrient levels within high water treatments, and for comparisons that included both a water and nutrient level change. The significant genotype x environment (G x E) effects support the argument that invasiveness of purple loosestrife is closely associated with the interaction of high levels of soil nutrient and flooding water regime. Our results indicate that native and invasive plants take different strategies for growth and reproduction; native plants flowered earlier and allocated more to flower production, while invasive plants exhibited an extended period of vegetative growth before flowering to increase height and allocation to clonal reproduction, which may contribute to increased fitness and invasiveness in subsequent years.     

Reproductive plasticity,oviposition site selection,and maternal effects in fragmented landscapes

Traditionally, evolutionary ecology and conservation biology have primarily been concerned with how environmental changes affect population size and genetic diversity. Recently, however, there has been a growing realization that phenotypic plasticity can have important consequences for the probability of population persistence, population growth, and evolution during rapid environmental change. Habitat fragmentation due to human activities is dramatically changing the ecological conditions of life for many organisms. In this review, we use examples from the literature to demonstrate that habitat fragmentation has important consequences on oviposition site selection in insects, with carryover effects on offspring survival and, therefore, population dynamics. We argue that plasticity in oviposition site selection and maternal effects on offspring phenotypes may be an important, yet underexplored, mechanism by which environmental conditions have consequences across generations. Without considering the impact of habitat fragmentation on oviposition site selection, it will be difficult to assess the effect of fragmentation on offspring fitness, and ultimately to understand the impact of anthropogenic-induced environmental change on population viability.     

Evaluating the causal basis of ecological success within the scleractinia: an integral projection model approach

Many tropical corals have declined in abundance in the last few decades, and evaluating the causal basis of these losses is critical to understanding how coral reefs will change in response to ongoing environmental challenges. Motivated by the likelihood that marine environments will become increasingly unfavorable for coral growth as they warm and become more acidic (i.e., ocean acidification), it is reasonable to evaluate whether specific phenotypic traits of the coral holobiont are associated with ecological success (or failure) under varying environmental conditions including those that are adverse to survival. Initially, we asked whether it was possible to identify corals that are resistant or sensitive to such conditions by compiling quantitative measures of their phenotypic traits determined through empirical studies, but we found only weak phenotypic discrimination between ecological winners and losers, or among taxa. To reconcile this outcome with ecological evidence demonstrating that coral taxa are functionally unequal, we looked beyond the notion that phenotypic homogeneity arose through limitations of empirical data. Instead, we examined the validity of contemporary means of categorizing corals based on ecological success. As an alternative means to distinguish among functional groups of corals, we present a demographic approach using integral projection models (IPMs) that link organismal performance to demographic outcomes, such as the rates of population growth and responses to environmental stress. We describe how IPMs can be applied to corals so that future research can evaluate within a quantitative framework the extent to which changes in physiological performance influence the demographic underpinnings of ecological performance.     

Predicting how defaunation-induced changes in seed predation and dispersal will affect tropical tree populations

The loss of large animals due to overhunting and habitat loss potentially affects tropical tree populations and carbon cycling. Trees reliant on large-bodied seed dispersers are thought to be particularly negatively affected by defaunation. But besides seed dispersal, defaunation can also increase or decrease seed predation. It remains unclear how these different defaunation effects on early life stages ultimately affect tree population dynamics. We reviewed the literature on how tropical animal loss affects different plant life stages, and we conducted a meta-analysis of how defaunation affects seed predation. We used this information to parameterize models that altered matrix projection models from a suite of tree species to simulate defaunation-caused changes in seed dispersal and predation. We assessed how applying these defaunation effects affected population growth rates. On average, population-level effects of defaunation were negligible, suggesting that defaunation may not cause the massive reductions in forest carbon storage that have been predicted. In contrast to previous hypotheses, we did not detect an effect of seed size on changes in seed predation rates. The change in seed predation did not differ significantly between exclosure experiments and observational studies, although the results of observational studies were far more variable. Although defaunation surely affects certain tree taxa, species that benefit or are harmed by it and net changes in forest carbon storage cannot currently be predicted based on available data. Further research on how factors such as seed predation vary across tree species and defaunation scenarios is necessary for understanding cascading changes in species composition and diversity.     

Invasive Microstegium populations consistently outperform native range populations across diverse environments

Plant species introduced into novel ranges may become invasive due to evolutionary change, phenotypic plasticity, or other biotic or abiotic mechanisms. Evolution of introduced populations could be the result of founder effects, drift, hybridization, or adaptation to local conditions, which could enhance the invasiveness of introduced species. However, understanding whether the success of invading populations is due to genetic differences between native and introduced populations may be obscured by origin x environment interactions. That is, studies conducted under a limited set of environmental conditions may show inconsistent results if native or introduced populations are differentially adapted to specific conditions. We tested for genetic differences between native and introduced populations, and for origin x environment interactions, between native (China) and introduced (U.S.) populations of the invasive annual grass Microstegium vimineum (stiltgrass) across 22 common gardens spanning a wide range of habitats and environmental conditions. On average, introduced populations produced 46% greater biomass and had 7.4% greater survival, and outperformed native range populations in every common garden. However, we found no evidence that introduced Microstegium exhibited greater phenotypic plasticity than native populations. Biomass of Microstegium was positively correlated with light and resident community richness and biomass across the common gardens. However, these relationships were equivalent for native and introduced populations, suggesting that the greater mean performance of introduced populations is not due to unequal responses to specific environmental parameters. Our data on performance of invasive and native populations suggest that post-introduction evolutionary changes may have enhanced the invasive potential of this species. Further, the ability of Microstegium to survive and grow across the wide variety of environmental conditions demonstrates that few habitats are immune to invasion.     

Adaptive introgression as a resource for management and genetic conservation in a changing climate

Current rates of climate change require organisms to respond through migration, phenotypic plasticity, or genetic changes via adaptation. We focused on questions regarding species’ and populations’ ability to respond to climate change through adaptation. Specifically, the role adaptive introgression, movement of genetic material from the genome of 1 species into the genome of another through repeated interbreeding, may play in increasing species’ ability to respond to a changing climate. Such interspecific gene flow may mediate extinction risk or consequences of limited adaptive potential that result from standing genetic variation and mutation alone, enabling a quicker demographic recovery in response to changing environments. Despite the near dismissal of the potential benefits of hybridization by conservation practitioners, we examined a number of case studies across different taxa that suggest gene flow between sympatric or parapatric sister species or within species that exhibit strong ecotypic differentiation may represent an underutilized management option to conserve evolutionary potential in a changing environment. This will be particularly true where advanced‐generation hybrids exhibit adaptive traits outside the parental phenotypic range, a phenomenon known as transgressive segregation. The ideas presented in this essay are meant to provoke discussion regarding how we maintain evolutionary potential, the conservation value of natural hybrid zones, and consideration of their important role in adaptation to climate.     

Interacting Effects of Phenotypic Plasticity and Evolution on Population Persistence in a Changing Climate

Abstract: Climate change affects individual organisms by altering development, physiology, behavior, and fitness, and populations by altering genetic and phenotypic composition, vital rates, and dynamics. We sought to clarify how selection, phenotypic plasticity, and demography are linked in the context of climate change. On the basis of theory and results of recent empirical studies of plants and animals, we believe the ecological and evolutionary issues relevant to population persistence as climate changes are the rate, type, magnitude, and spatial pattern of climate‐induced abiotic and biotic change; generation time and life history of the organism; extent and type of phenotypic plasticity; amount and distribution of adaptive genetic variation across space and time; dispersal potential; and size and connectivity of subpopulations. An understanding of limits to plasticity and evolutionary potential across traits, populations, and species and feedbacks between adaptive and demographic responses is lacking. Integrated knowledge of coupled ecological and evolutionary mechanisms will increase understanding of the resilience and probabilities of persistence of populations and species.     

Live algae as a vector candidate for hydrophobic polychlorinated biphenyls translocation to bivalve filter feeders for laboratory toxicity test

Live algae carrying hydrophobic xenobiotics can be an effective vector candidate for the chemical translocation to filter feeders in the laboratory toxicity test, but information on their application is lacking. Time-course uptake and elimination of polychlorinated biphenyls (PCBs) (0, 50, 100, and 500 ng g(-1) by two key algal foods, Isochrysis galbana and Tetraselmis suecica, were measured. Both of the algae achieved maximum concentration in an hourafter PCBs exposure regardless the chemical concentrations in our time-course measurements (0, 1, 5, 10, 24, 48 and 72 hrs). Once achieved the maximum concentration, the algae shortly exhibited elimination or eliminating tendency depending on the chemical concentrations. Algae exposed to the chemical for 1 and 24 hrs (hereafter 1 and 24 hr vectors, respectively) were then evaluated as a chemical translocation vector by feeding test to larval and spat Crassostrea gigas. In the feeding test the 24 hr vector, which contained lower chemicals than the 1-hr vector, appeared to be more damaging the early lives of the oyster. This was particularly significant for vectors of higher PCBs (p<0.05), probably due to algal reduction in food value by the prolonged chemical stress. These findings imply that 1 hr exposure is long enough for a generation of algal vector for laboratory toxicity test, minimizing data error resulted from reduction in food value by longer chemical stress.     

Plant-trait-based modeling assessment of ecosystem-service sensitivity to land-use change

Evidence is accumulating that the continued provision of essential ecosystem services is vulnerable to land-use change. Yet, we lack a strong scientific basis for this vulnerability as the processes that drive ecosystem-service delivery often remain unclear. In this paper, we use plant traits to assess ecosystem-service sensitivity to land-use change in subalpine grasslands. We use a trait-based plant classification (plant functional types, PFTs) in a landscape modeling platform to model community dynamics under contrasting but internally consistent land-use change scenarios. We then use predictive models of relevant ecosystem attributes, based on quantitative plant traits, to make projections of ecosystem-service delivery. We show that plant traits and PFTs are effective predictors of relevant ecosystem attributes for a range of ecosystem services including provisioning (fodder), cultural (land stewardship), regulating (landslide and avalanche risk), and supporting services (plant diversity). By analyzing the relative effects of the physical environment and land use on relevant ecosystem attributes, we also show that these ecosystem services are most sensitive to changes in grassland management, supporting current agri-environmental policies aimed at maintaining mowing of subalpine grasslands in Europe.     

Effects of Changes in Biodiversity on Ecosystem Function in Tropical Forests

Changing land use in the tropics has resulted in vast areas of damaged and degraded lands where biodiversity has been reduced. The majority of research on biodiversity has been focused on population and community dynamics and has rarely considered the ecosystem processes that are intimately related. We present a framework for examining the effects of changes in biodiversity on ecosystem function in natural, managed, and damaged tropical forests. Using a whole-ecosystem approach, the framework identifies key nutrient and energy cycling processes and critical junctures or pathways, termed interfaces, where resources are concentrated and transferred between the biotic and abiotic components of the ecosystem. Processes occurring at these interfaces, and the organisms or attributes participating in these processes, exert a strong influence on ecosystem structure. We use examples from Puerto Rico, Southern China, Dominica, and Nicaragua to illustrate how the functional diversity framework can be applied to critically examine the effects of changes in biodiversity on ecosystem function, and the relative success or failure of rehabilitation strategies. The few available data suggest that functional diversity, and not just species richness, is important in maintaining the integrity of nutrient and energy fluxes. High species richness, however, may increase ecosystem resiliency following disturbance by increasing the number of alternative pathways for the flow of resources. We suggest ways in which the framework of functional diversity can be used to design research to examine the effects of changes in biodiversity on ecosystem processes and in the design and evaluation of ecosystem management and land rehabilitation projects in the tropics.     

Associations of forest bird species richness with housing and landscape patterns across the USA.

In the United States, housing density has substantially increased in and adjacent to forests. Our goal in this study was to identify how housing density and human populations are associated with avian diversity. We compared these associations to those between landscape pattern and avian diversity, and we examined how these associations vary across the conterminous forested United States. Using data from the North American Breeding Bird Survey, the U.S. Census, and the National Land Cover Database, we focused on forest and woodland bird communities and conducted our analysis at multiple levels of model specificity, first using a coarse-thematic resolution (basic models), then using a larger number of fine-thematic resolution variables (refined models). We found that housing development was associated with forest bird species richness in all forested ecoregions of the conterminous United States. However, there were important differences among ecoregions. In the basic models, housing density accounted for < 5% of variance in avian species richness. In refined models, 85% of models included housing density and/or residential land cover as significant variables. The strongest guild response was demonstrated in the Adirondack-New England ecoregion, where 29% of variation in richness of the permanent resident guild was associated with housing density. Model improvements due to regional stratification were most pronounced for cavity nesters and short-distance migrants, suggesting that these guilds may be especially sensitive to regional processes. The varying patterns of association between avian richness and attributes associated with landscape structure suggested that landscape context was an important mediating factor affecting how biodiversity responds to landscape changes. Our analysis suggested that simple, broadly applicable, land use recommendations cannot be derived from our results. Rather, anticipating future avian response to land use intensification (or reversion to native vegetation) has to be conditioned on the current landscape context and the species group of interest. Our results show that housing density and residential land cover were significant predictors of forest bird species richness, and their prediction strengths are likely to increase as development continues.     

Accounting for multiple testing in the analysis of spatio-temporal environmental data

The statistical analysis of environmental data from remote sensing and Earth system simulations often entails the analysis of gridded spatio-temporal data, with a hypothesis test being performed for each grid cell. When the whole image or a set of grid cells are analyzed for a global effect, the problem of multiple testing arises. When no global effect is present, we expect $$ \alpha $$% of all grid cells to be false positives, and spatially autocorrelated data can give rise to clustered spurious rejections that can be misleading in an analysis of spatial patterns. In this work, we review standard solutions for the multiple testing problem and apply them to spatio-temporal environmental data. These solutions are independent of the test statistic, and any test statistic can be used (e.g., tests for trends or change points in time series). Additionally, we introduce permutation methods and show that they have more statistical power. Real-world data are used to provide examples of the analysis, and the performance of each method is assessed in a simulation study. Unlike other simulation studies, our study compares the statistical power of the presented methods in a comprehensive simulation study. In conclusion, we present several statistically rigorous methods for analyzing spatio-temporal environmental data and controlling the false positives. These methods allow the use of any test statistic in a wide range of applications in environmental sciences and remote sensing.     

The interaction between seaweed farming as an alternative occupation and fisher numbers in the central Philippines

Alternative occupations are frequently promoted as a means to reduce the number of people exploiting declining fisheries. However, there is little evidence that alternative occupations reduce fisher numbers. Seaweed farming is frequently promoted as a lucrative alternative occupation for artisanal fishers in Southeast Asia. We examined how the introduction of seaweed farming has affected village-level changes in the number of fishers on Danajon Bank, central Philippines, where unsustainable fishing has led to declining fishery yields. To determine how fisher numbers had changed since seaweed farming started, we interviewed the heads of household from 300 households in 10 villages to examine their perceptions of how fisher numbers had changed in their village and the reasons they associated with these changes. We then asked key informants (people with detailed knowledge of village members) to estimate fisher numbers in these villages before seaweed farming began and at the time of the survey. We compared the results of how fisher numbers had changed in each village with the wealth, education, seaweed farm sizes, and other attributes of households in these villages, which we collected through interviews, and with village-level factors such as distance to markets. We also asked people why they either continued to engage in or ceased fishing. In four villages, respondents thought seaweed farming and low fish catches had reduced fisher numbers, at least temporarily. In one of these villages, there was a recent return to fishing due to declines in the price of seaweed and increased theft of seaweed. In another four villages, fisher numbers increased as human population increased, despite the widespread uptake of seaweed farming. Seaweed farming failed for technical reasons in two other villages. Our results suggest seaweed farming has reduced fisher numbers in some villages, a result that may be correlated with socioeconomic status, but the heterogeneity of outcomes is consistent with suggestions that alternative occupations are not a substitute for more direct forms of resource management.     

Using the negative binomial distribution to model overdispersion in ecological count data

A Poisson process is a commonly used starting point for modeling stochastic variation of ecological count data around a theoretical expectation. However, data typically show more variation than implied by the Poisson distribution. Such overdispersion is often accounted for by using models with different assumptions about how the variance changes with the expectation. The choice of these assumptions can naturally have apparent consequences for statistical inference. We propose a parameterization of the negative binomial distribution, where two overdispersion parameters are introduced to allow for various quadratic mean-variance relationships, including the ones assumed in the most commonly used approaches. Using bird migration as an example, we present hypothetical scenarios on how overdispersion can arise due to sampling, flocking behavior or aggregation, environmental variability, or combinations of these factors. For all considered scenarios, mean-variance relationships can be appropriately described by the negative binomial distribution with two overdispersion parameters. To illustrate, we apply the model to empirical migration data with a high level of overdispersion, gaining clearly different model fits with different assumptions about mean-variance relationships. The proposed framework can be a useful approximation for modeling marginal distributions of independent count data in likelihood-based analyses.     

Minimizing the cost of translocation failure with decision‐tree models that predict species’ behavioral response in translocation sites

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision‐tree models for species’ translocation, we used data on the short‐term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision‐tree algorithms (decision tree, decision‐tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. Minimizar el Costo del Fracaso de la Reubicación con Modelos de Árboles de Decisión que Predigan la Respuesta Conductual de la Especie en los Sitios de Reubicación     

Ecological opportunity and phenotypic plasticity interact to promote character displacement and species coexistence

We investigated the roles of resource availability and phenotypic plasticity in promoting ecological character displacement (i.e., trait evolution stemming from resource competition between species). Because ecological character displacement generates new populations that differ in resource use, this process should only occur when exploitable resources are available. We tested this hypothesis in two species of spadefoot toads (Spea bombifrons and S. multiplicata) whose tadpoles use phenotypic plasticity to develop into either an omnivore morph, which specializes on detritus, or a physically distinctive carnivore morph, which specializes on shrimp. Both species grow best on shrimp, but when reared together, S. bombifrons outcompetes S. multiplicata for shrimp and S. multiplicata outcompetes S. bombifrons for detritus. We found that when each species occurred alone in the field, they produced similar proportions of omnivores and carnivores. When the two species occurred together, however, they underwent ecological character displacement in larval development, with S. multiplicata producing mostly omnivores, and S. bombifrons producing mostly carnivores. We combined observations of natural populations with experiments to evaluate whether such character displacement was only possible when both shrimp and detritus were relatively abundant. Mixed-species ponds contained abundant detritus and shrimp, in contrast with nearby pure-species ponds, which were deficient in one resource. Experiments revealed that S. multiplicata competed poorly when detritus was rare and that S. bombifrons competed poorly when shrimp was rare. In nature, when one of these two resources was scarce, one species was missing, perhaps through competitive exclusion by the species that was the superior competitor for the remaining resource. Thus, ecological character displacement and, therefore, coexistence of close competitors, was only possible when diverse resources were available. Finally, even if exploitable resources are available, character displacement is not guaranteed to transpire if species cannot utilize such resources expeditiously. Phenotypic plasticity provides a general and important mechanism for facilitating resource partitioning. Thus, by facilitating shifts in resource use, phenotypic plasticity and ecological opportunity may often interact to promote divergence and coexistence of competitors.     

Methods to summarize change among land categories across time intervals

Time-series maps have become more detailed in terms of numbers of categories and time points. Our paper proposes methods for raster datasets where detailed analysis of all categorical transitions would be initially overwhelming. We create two measurements: Incidents and States. The former is the number of times a pixel’s category changes across time intervals; the latter is the number of categories that a pixel represents across time points. The combinations of Incidents and States summarize change trajectories. We also describe categorical transitions in terms of annual flow matrices, which quantify the additional information generated by intermediate time points within the temporal extent. Our approach summarizes change at the pixel and landscape levels in ways that communicate where and how categories transition over time. These methods are useful to detect hotspots of change and to consider whether the apparent changes are real or due to map error.     

Quantifying ecological thresholds from response surfaces

Ecological thresholds are abrupt changes of ecological state. While an ecological threshold is a widely accepted concept, most empirical methods detect them in time or across geographic space. Although useful, these approaches do not quantify the direct drivers of threshold response. Causal understanding of thresholds detected empirically requires their investigation in a multi-factor domain containing the direct drivers (often referred to as state space). Here, we present an approach to quantify thresholds from response surfaces modeled empirically in state space. We present two indices of shape attributes measured from response surfaces. The response surfaces are built using a regression method in state space. The indices are threshold strength (T) and diagonality (D). We use 48 simulated response surfaces of different shapes to test the efficacy of the indices in 3D. Our results show that T is sensitive to the steepness of the transition from one state to the next, with various forms of abrupt, centralized thresholds yielding the highest values among the simulated surfaces. D represents the orientation of the response surface or the simultaneous influence of more than one predictor in eliciting the response gradient. Strongly diagonal surfaces have the most diagonal surface area demonstrated by sharply undulating diagonal surfaces. Given that the success of T and D requires a regression method to accurately capture any shape of complex data structure, we also test the accuracy of empirical regression methods known to be tractable with complex data. We test classification and regression trees (CART), Random Forest, and non-parametric multiplicative regression (NPMR) for binary and continuous responses. We use the 48 simulated response surfaces to test the methods, and we find that prediction accuracy depends on both the T and D of the simulated data for each method. We choose the most accurate method among those we test for capturing any shape of response surface from real data, NPMR. Finally, we use NPMR to build response surfaces and quantify T and D from real ecological data sets. We demonstrate how measuring threshold strength and diagonality from multi-factor response surfaces can advance ecology.     

Empirical evaluation of neutral theory

We describe a general framework for testing neutral theory. We summarize similarities and differences between ten different versions of neutral theory. Two central predictions of neutral theory are that species abundance distributions will follow a zero-sum multinomial distribution and that community composition will change over space due to dispersal limitation. We review all published empirical tests of neutral theory. With the exception of one type of test, all tests fail to support neutral theory. We identify and perform several new tests. Specifically, we develop a set of best practices for testing the fit of the zero-sum multinomial (ZSM) vs. a lognormal null hypothesis and apply this to a data set, concluding that the lognormal outperforms neutral theory on robust tests. We explore whether a priori parameterization of neutral theory is possible, and we conclude that it is not. We show that non-curve-fitting predictions readily derived from neutral theory are easily falsifiable. In toto, there is a current overwhelming weight of evidence against neutral theory. We suggest some next steps for neutral theory.