Optimizing dispersal study design by Monte Carlo simulation

Dispersal of Lycorma delicatula (Hemiptera: Fulgoridae) Nymphs Through Contiguous, Deciduous Forest

Spotted lanternfly (Lycorma delicatula) is a recently introduced pest in the United States, where it threatens the wine, timber, and ornamentals industries. Knowledge of the dispersal ability of L. delicatula is key to developing effective management strategies for this invasive pest. We conducted a mark, release, re-sight study, marking nymphs with fluorescent powders and observing dispersal distances from a central release point at three time points over 7 d following release. To examine how dispersal patterns changed over the course of nymphal development, we repeated this process for each of L. delicatula's four instars. All releases were conducted in contiguous, deciduous forest, which is a widespread habitat type within L. delicatula's invaded range and a habitat where this pest may have negative ecological and economic impacts. We found that nymphs displayed clear directionality in their movement following release, apparently preferring to move uphill on the modest 6° grade at our release site. Most nymphs remained near the release location, while some moved tens of meters. The maximum displacement we observed was 65 m from the release point, 10 d after release. Nymphs were re-sighted singly and in small groups on a variety of trees, shrubs, and understory vegetation. All four instars had similar dispersal distances over time, though third instar nymphs moved farthest on average, with estimated median displacement of 16.9 m 7 d after release. Further studies are needed to provide additional information on what factors influence spotted lanternfly dispersal.

Advancing an interdisciplinary framework to study seed dispersal ecology

Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant's life history and environmental variability that ultimately influences a population's ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity.

The total dispersal kernel: a review and future directions

The distribution and abundance of plants across the world depends in part on their ability to move, which is commonly characterized by a dispersal kernel. For seeds, the total dispersal kernel (TDK) describes the combined influence of all primary, secondary and higher-order dispersal vectors on the overall dispersal kernel for a plant individual, population, species or community. Understanding the role of each vector within the TDK, and their combined influence on the TDK, is critically important for being able to predict plant responses to a changing biotic or abiotic environment. In addition, fully characterizing the TDK by including all vectors may affect predictions of population spread. Here, we review existing research on the TDK and discuss advances in empirical, conceptual modelling and statistical approaches that will facilitate broader application. The concept is simple, but few examples of well-characterized TDKs exist. We find that significant empirical challenges exist, as many studies do not account for all dispersal vectors (e.g. gravity, higher-order dispersal vectors), inadequately measure or estimate long-distance dispersal resulting from multiple vectors and/or neglect spatial heterogeneity and context dependence. Existing mathematical and conceptual modelling approaches and statistical methods allow fitting individual dispersal kernels and combining them to form a TDK; these will perform best if robust prior information is available. We recommend a modelling cycle to parameterize TDKs, where empirical data inform models, which in turn inform additional data collection. Finally, we recommend that the TDK concept be extended to account for not only where seeds land, but also how that location affects the likelihood of establishing and producing a reproductive adult, i.e. the total effective dispersal kernel.

Detecting crucial dispersal pathways using a virtual ecology approach: A case study of the mirid bug Stenotus rubrovittatus

Detecting dispersal pathways is important both for understanding species range expansion and for managing nuisance species. However, direct detection is difficult. Here, we propose detecting these crucial pathways using a virtual ecology approach, simulating species dynamics using models, and virtual observations. As a case study, we developed a dispersal model based on cellular automata for the pest insect Stenotus rubrovittatus and simulated its expansion. We tested models for species expansion based on four landscape parameters as candidate pathways; these are river density, road density, area of paddy fields, and area of abandoned farmland, and validated their accuracy. We found that both road density and abandoned area models had prediction accuracy. The simulation requires simple data only to have predictive power, allowing for fast modeling and swift establishment of management plans.

Measuring short distance dispersal of Alliaria petiolata and determining potential long distance dispersal mechanisms

Introduction

Alliaria petiolata, an herbaceous plant, has invaded woodlands in North America. Its ecology has been thoroughly studied, but an overlooked aspect of its biology is seed dispersal distances and mechanisms. We measured seed dispersal distances in the field and tested if epizoochory is a potential mechanism for long-distance seed dispersal.

Methods

Dispersal distances were measured by placing seed traps in a sector design around three seed point sources, which consisted of 15 second-year plants transplanted within a 0.25 m radius circle. Traps were placed at intervals ranging from 0.25–3.25 m from the point source. Traps remained in the field until a majority of seeds were dispersed. Eight probability density functions were fitted to seed trap counts via maximum likelihood. Epizoochory was tested as a potential seed dispersal mechanism for A. petiolata through a combination of field and laboratory experiments. To test if small mammals transport A. petiolata seeds in their fur, experimental blocks were placed around dense A. petiolata patches. Each block contained a mammal inclusion treatment (MIT) and control. The MIT consisted of a wood-frame (31 × 61× 31 cm) covered in wire mesh, except for the two 31 × 31 cm ends, placed over a germination tray filled with potting soil. A pan filled with bait was placed in the center of the tray. The control frame (11 × 31 × 61 cm) was placed over a germination tray and completely covered in wire mesh to exclude animal activity. Treatments were in the field for peak seed dispersal. In March, trays were moved to a greenhouse and A. petiolata seedlings were counted and then compared between treatments. To determine if A. petiolata seeds attach to raccoon (Procyon lotor) and white-tailed deer (Odocoileus virginianus) fur, wet and dry seeds were dropped onto wet and dry fur. Furs were rotated 180 degrees and the seeds that remained attached were counted. To measure seed retention, seeds were dropped on furs and rotated as before, then the furs were agitated for one hour. The seeds retained in the fur were counted.

Results

For the seed dispersal experiment, the 2Dt function provided the best fit and was the most biologically meaningful. It predicted that seed density rapidly declined with distance from the point source. Mean dispersal distance was 0.52 m and 95% of seeds dispersed within 1.14 m. The epizoochory field experiment showed increased mammal activity and A. petiolata seedlings in germination trays of the MIT compared to control. Laboratory studies showed 3–26% of seeds were attached and retained by raccoon and deer fur. Retention significantly increased if either seed or fur were wet (57–98%).

Discussion

Without animal seed vectors, most seeds fall within a short distance of the seed source; however, long distance dispersal may be accomplished by epizoochory. Our data are consistent with A. petiolata’s widespread distribution and development of dense clusters of the species in invaded areas.

Transmission dynamics: critical questions and challenges

This article overviews the dynamics of disease transmission in one-host-one-parasite systems. Transmission is the result of interacting host and pathogen processes, encapsulated with the environment in a 'transmission triangle'. Multiple transmission modes and their epidemiological consequences are often not understood because the direct measurement of transmission is difficult. However, its different components can be analysed using nonlinear transmission functions, contact matrices and networks. A particular challenge is to develop such functions for spatially extended systems. This is illustrated for vector transmission where a 'perception kernel' approach is developed that incorporates vector behaviour in response to host spacing. A major challenge is understanding the relative merits of the large number of approaches to quantifying transmission. The evolution of transmission mode itself has been a rather neglected topic, but is important in the context of understanding disease emergence and genetic variation in pathogens. Disease impacts many biological processes such as community stability, the evolution of sex and speciation, yet the importance of different transmission modes in these processes is not understood. Broader approaches and ideas to disease transmission are important in the public health realm for combating newly emerging infections.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.

Long-distance wind-dispersal of spores in a fungal plant pathogen: estimation of anisotropic dispersal kernels from an extensive field experiment

Given its biological significance, determining the dispersal kernel (i.e., the distribution of dispersal distances) of spore-producing pathogens is essential. Here, we report two field experiments designed to measure disease gradients caused by sexually- and asexually-produced spores of the wind-dispersed banana plant fungus Mycosphaerella fijiensis. Gradients were measured during a single generation and over 272 traps installed up to 1000 m along eight directions radiating from a traceable source of inoculum composed of fungicide-resistant strains. We adjusted several kernels differing in the shape of their tail and tested for two types of anisotropy. Contrasting dispersal kernels were observed between the two types of spores. For sexual spores (ascospores), we characterized both a steep gradient in the first few metres in all directions and rare long-distance dispersal (LDD) events up to 1000 m from the source in two directions. A heavy-tailed kernel best fitted the disease gradient. Although ascospores distributed evenly in all directions, average dispersal distance was greater in two different directions without obvious correlation with wind patterns. For asexual spores (conidia), few dispersal events occurred outside of the source plot. A gradient up to 12.5 m from the source was observed in one direction only. Accordingly, a thin-tailed kernel best fitted the disease gradient, and anisotropy in both density and distance was correlated with averaged daily wind gust. We discuss the validity of our results as well as their implications in terms of disease diffusion and management strategy.

Dispersal and the design of effective management strategies for plant invasions: matching scales for success

Dispersal of propagules makes invasions a fundamentally spatial phenomenon, and to be effective, management actions to control or eradicate invasive species must take this spatial structure into account. While there is a vibrant literature linking detailed dispersal measurements to the rate of invasive spread, and a separate literature focused on incorporating management into invasive models in order to improve the control of weeds, there are relatively fewer manuscripts incorporating state-of-the-art dispersal modeling and management modeling together to provide on-ground recommendations for structuring effective management. In this paper, we perform a generalized analysis of a spatially explicit, individual-based simulation model of invasion management with empirically determined dispersal processes, illustrated with the example of Miconia calvescens in the Australian Wet Tropics rain forest, to explore how matching the spatial scale of management to the spatial scale of the dispersal processes underpinning invasion influences the success of management. We find that management strategies designed to maximize the number of weeds removed from the management region, either in the first year of management or over longer periods, provide a poor estimate of the spatial scale of management that maximizes the probability of eradication. We show that achieving a goal of certainty of eradication requires exceeding a minimal spatial scale of management and total management resourcing. We generalize these results to examine how the spatial scale of dispersal drives the spatial scale of effective management strategies. These results show that to be effective, management of dispersal-driven invasions must occur at spatial scales determined by the scale of dispersal processes, and resourced accordingly. It illustrates how those scales might be calculated for a specific case for which detailed dispersal data are available and generalizes the result to highlight how dispersal scale drives the scale of effective management. The results highlight the importance of understanding the ecological drivers of invasion to structure effective management.

Fish dispersal in fragmented landscapes: a modeling framework for quantifying the permeability of structural barriers

Dispersal is a key determinant of the spatial distribution and abundance of populations, but human-made fragmentation can create barriers that hinder dispersal and reduce population viability. This study presents a modeling framework based on dispersal kernels (modified Laplace distributions) that describe stream fish dispersal in the presence of obstacles to passage. We used mark-recapture trials to quantify summer dispersal of brook trout (Salvelinus fontinalis) in four streams crossed by a highway. The analysis identified population heterogeneity in dispersal behavior, as revealed by the presence of a dominant sedentary component (48-72% of all individuals) characterized by short mean dispersal distance (<10 m), and a secondary mobile component characterized by longer mean dispersal distance (56-1086 m). We did not detect evidence of barrier effects on dispersal through highway crossings. Simulation of various plausible scenarios indicated that detectability of barrier effects was strongly dependent on features of sampling design, such as spatial configuration of the sampling area, barrier extent, and sample size. The proposed modeling framework extends conventional dispersal kernels by incorporating structural barriers. A major strength of the approach is that ecological process (dispersal model) and sampling design (observation model) are incorporated simultaneously into the analysis. This feature can facilitate the use of prior knowledge to improve sampling efficiency of mark-recapture trials in movement studies. Model-based estimation of barrier permeability and its associated uncertainty provides a rigorous approach for quantifying the effect of barriers on stream fish dispersal and assessing population dynamics of stream fish in fragmented landscapes.

Integrating spread dynamics and economics of timber production to manage Chinese tallow invasions in southern U.S. forestlands

Economic costs associated with the invasion of nonnative species are of global concern. We estimated expected costs of Chinese tallow (Triadica sebifera (L.) Small) invasions related to timber production in southern U.S. forestlands under different management strategies. Expected costs were confined to the value of timber production losses plus costs for search and control. We simulated management strategies including (1) no control (NC), and control beginning as soon as the percentage of invaded forest land exceeded (2) 60 (Low Control), (3) 25 (Medium Control), or (4) 0 (High Control) using a spatially-explicit, stochastic, bioeconomic model. With NC, simulated invasions spread northward and westward into Arkansas and along the Gulf of Mexico to occupy ≈1.2 million hectares within 20 years, with associated expected total costs increasing exponentially to ≈$300 million. With LC, MC, and HC, invaded areas reached ≈275, 34, and 2 thousand hectares after 20 years, respectively, with associated expected costs reaching ≈$400, $230, and $200 million. Complete eradication would not be cost-effective; the minimum expected total cost was achieved when control began as soon as the percentage of invaded land exceeded 5%. These results suggest the importance of early detection and control of Chinese tallow, and emphasize the importance of integrating spread dynamics and economics to manage invasive species.

The importance of tree size and fecundity for wind dispersal of big-leaf mahogany

Seed dispersal by wind is a critical yet poorly understood process in tropical forest trees. How tree size and fecundity affect this process at the population level remains largely unknown because of insufficient replication across adults. We measured seed dispersal by the endangered neotropical timber species big-leaf mahogany (Swietenia macrophylla King, Meliaceae) in the Brazilian Amazon at 25 relatively isolated trees using multiple 1-m wide belt transects extended 100 m downwind. Tree diameter and fecundity correlated positively with increased seed shadow extent; but in combination large, high fecundity trees contributed disproportionately to longer-distance dispersal events (>60 m). Among three empirical models fitted to seed density vs. distance in one dimension, the Student-t (2Dt) generally fit best (compared to the negative exponential and inverse power). When seedfall downwind was modelled in two dimensions using a normalised sample, it peaked furthest downwind (c. 25 m) for large, high-fecundity trees; with the inverse Gaussian and Weibull functions providing comparable fits that were slightly better than the lognormal. Although most seeds fell within 30 m of parent trees, relatively few juveniles were found within this distance, resulting in juvenile-to-seed ratios peaking at c. 35–45 m. Using the 2Dt model fits to predict seed densities downwind, coupled with known fecundity data for 2000–2009, we evaluated potential Swietenia regeneration near adults (≤30 m dispersal) and beyond 30 m. Mean seed arrival into canopy gaps >30 m downwind was more than 3× greater for large, high fecundity trees than small, high-fecundity trees. Tree seed production did not necessarily scale up proportionately with diameter, and was not consistent across years, and this resulting intraspecific variation can have important consequences for local patterns of dispersal in forests. Our results have important implications for management and conservation of big-leaf mahogany populations, and may apply to other threatened wind-dispersed Meliaceae trees.

Evaluating nested clade phylogeographic analysis under models of restricted gene flow

Nested clade phylogeographic analysis (NCPA) is a widely used method that aims to identify past demographic events that have shaped the history of a population. In an earlier study, NCPA has been fully automated, allowing it to be tested with simulated data sets generated under a null model in which samples simulated from a panmictic population are geographically distributed. It was noted that NCPA was prone to inferring false positives, corroborating earlier findings. The present study aims to evaluate both single-locus and multilocus NCPA under the scenario of restricted gene flow among spatially distributed populations. We have developed a new program, ANeCA-ML, which implements multilocus NCPA. Data were simulated under 3 models of gene flow: a stepping stone model, an island model, and a stepping stone model with some long-distance dispersal. Results indicate that single-locus NCPA tends to give a high frequency of false positives, but, unlike the random-mating scenario presented previously, inferences are not limited to restricted gene flow with isolation by distance or contiguous range expansion. The proportion of single-locus data sets that contained false inferences was 76% for the panmictic case, 87% for the stepping stone model, 79% for the stepping stone model with long-distance dispersal, and more than 99% for the island model. The frequency of inferences is inversely related to the amount of gene flow between demes. We performed multilocus NCPA by grouping the simulated loci into data sets of 5 loci. The false-positive rate was reduced in multilocus NCPA for some inferences but remained high for others. The proportion of multilocus data sets that contained false inferences was 17% for the panmictic case, 30% for the stepping stone model, 4% for the stepping stone model with long-distance dispersal, and 54% for the island model. Multilocus NCPA reduces the false-positive rate by restricting the sensitivity of the method but does not appear to increase the accuracy of the approach. Three classical tests-the analysis of molecular variance method, Fu's Fs, and the Mantel test-show that there is information in the data that gives rise to explicable results using these standard approaches. In conclusion, for the scenarios that we have examined, our simulation study suggests that the NCPA method is unreliable and its inferences may be misleading. We suggest that the NCPA method should not be used without objective simulation-based testing by independent researchers.

Dispersal Patterns, Dispersal Mechanisms, and Invasion Wave Speeds for Invasive Thistles

Understanding and predicting population spread rates is an important problem in basic and applied ecology. In this article, we link estimates of invasion wave speeds to species traits and environmental conditions. We present detailed field studies of wind dispersal and compare nonparametric (i.e., data-based) and mechanistic (fluid dynamics model-based) dispersal kernel and spread rate estimates for two important invasive weeds, Carduus nutans and Carduus acanthoides. A high-effort trapping design revealed highly leptokurtic dispersal distributions, with seeds caught up to 96 m from the source, far further than mean dispersal distances (approx. 2 m). Nonparametric wave speed estimates are highly sensitive to sampling effort. Mechanistic estimates are insensitive to sampling because they are obtained from independent data and more useful because they are based on the dispersal mechanism. Over a wide range of realistic conditions, mechanistic spread rate estimates were most sensitive to high winds and low seed settling velocities. The combination of integrodifference equations and mechanistic dispersal models is a powerful tool for estimating invasion spread rates and for linking these estimates to characteristics of the species and the environment.

Measuring and modeling dispersal of adult zooplankton

Habitat fragmentation poses an inherent problem for metacommunity dynamics, as dispersal among communities is hindered by increasing isolation and the loss of patches. Wetlands are one such system that have undergone excessive destruction and fragmentation in recent years. Zooplankton within these communities have historically been considered frequent and widespread dispersers, but direct, quantitative measures of zooplankton dispersal are rare. In this study, I performed two experiments to quantify zooplankton dispersal and to identify the primary dispersal vectors. I first set up an array of traps at 10, 30, 60, 120 and 180 m around an isolated pond to collect dispersing individuals. Nearly 1,500 adult zooplankton were captured in traps up to 180 m from the pond, with approximately 60% of dispersers being captured in traps at 10 m from the pond. A second experiment using open and animal-excluded traps suggested that large animals were the primary dispersal vector for these zooplankton. Using a subset of these data, I fit four models to describe the shape and magnitude of adult cladoceran dispersal at this site. All models showed the majority of cladocerans were deposited very close to the source pond, with three models suggesting that the trapping area encompassed 67% or more of the dispersal distances. These results suggest that adult zooplankton movement among ponds may be significant in areas where aquatic habitats are plentiful. Yet, in recent years climate change and anthropogenic disturbances have reduced the number and size of aquatic habitats in many regions of the world, likely curtailing effective transport of individuals in many cases. As a result, fragmented zooplankton metacommunities may experience increased dispersal limitation, stronger priority effects, higher levels of inbreeding and selection against traits engendering high dispersability.

Environmental variability and the initiation of dispersal: turbulence strongly increases seed release

Dispersal is a critical process in ecology. It is an important biological driver of, for example, invasions, metapopulation dynamics, spatial pattern formation and pathogen movement. Much is known about the effect of environmental variability, including turbulence, on dispersal of diaspores. Here, we document experimentally the strong but under-explored influence of turbulence on the initiation of dispersal. Flower heads of two thistle species (Carduus nutans and Carduus acanthoides) with ripe seeds were exposed to series of laminar and turbulent air flows of increasing velocity in a wind tunnel. Seed release increased with wind speeds for both laminar and turbulent flows for both species. However, far more seeds were released, at significantly lower wind speeds, during turbulent flows. These results strongly suggest a need for more quantitative studies of abscission in the field, as well as dispersal models that incorporate variability in the diaspore release phase.