Biology subjects

Helmus, M. R.

Publications and source records attributed to Helmus, M. R..

14 recordsLinked to original sources

bioRxiv2026

Mapping long-distance jump dispersal risk by leveraging transport infrastructure data and sampling bias correction: a case study with the invasive spotted lanternfly (Lycorma delicatula)

Long-distance jump dispersal accelerates invasive species spread. Analysis of past jumps can identify invasion pathways and point to locations at risk of future colonization, but spatial bias in survey records obscures patterns. To inform surveillance for the spreading invasive grape pest Lycorma delicatula (Hemiptera: Fulgoridae), we gathered 82,890 agency records of established invasive populations from the United States. We used a clustering algorithm to identify 207 jump dispersal sites, and we developed a bias-aware comparison dataset by filtering records to identify proactive search effort at locations not yet known to hold L. delicatula. We measured points' proximity to a co-produced list of 22 property types encompassing categories with high vehicle traffic, railroads, and related contexts that may transport L. delicatula. Bootstrapping analysis showed that proactive surveys were concentrated near hypothesized influential property types, confirming substantial sampling bias. With this bias accounted for, historical jump dispersal sites were closer than expected to 15 property types, particularly distribution centers, truck rentals, flea markets, and importers. We also compared the lengths of road and rail around these points, finding that jump sites were strongly associated with elevated rail density, whereas models showed limited support for roads as jump sites. Finally, we used the high-risk features to project risk of future jumps across the eastern U.S. using ensemble random forests. Predicted high-risk areas were northeast Illinois, southeast Michigan, and central Ohio. This framework is generalizable, allowing various pathways to be assessed and jump dispersal risk to be projected based on spatially biased surveillance data.

ecology↗

bioRxiv2026

Comparing pest survey methods through detection probability: seasonal and abundance-dependent detection of spotted lanternfly (Lycorma delicatula, Hemiptera: Fulgoridae)

BACKGROUND: Invasive species management demands accurate information on the distribution of targeted pests, but surveys have imperfect detection. Understanding the factors influencing detection probability can guide improved management planning. For the invasive spotted lanternfly (Lycorma delicatula), several sampling methods have been used. We evaluated three widely applied methods: 5-minute timed visual search, BugBarrier sticky band traps, and modified circle traps. These methods were used to quantify abundance in 5 x 20 m plots spanning the core to margins of five outlying satellite populations in Pennsylvania U.S.A. Methods were assessed every two weeks over the growing season for two years. RESULTS: Using a hierarchical Bayesian model, we found seasonal variation in all methods' detection probabilities, with timed visual search increasing in sensitivity over the course of the season and both tree-based traps showing a U-shaped pattern, with lowest detection probability around midseason. For timed visual search in plots used by ten L. delicatula individuals, the estimated probability of detecting at least one individual ranged from 10% to 53%. For tree-based traps, detection was higher on larger trees and on Ailanthus altissima, a preferred hostplant. For traps installed on A. altissima with diameter at breast height of 20 cm in a plot with the same L. delicatula density (N=10), estimated mean detection probability ranged from 33% to 99% for BugBarrier and from 28% to 84% for circle traps. CONCLUSION: Informed with estimated detection probabilities, managers can compare alternative survey methods and design strategic management plans that properly incorporate realistic survey sensitivity.

ecology↗

bioRxiv2025

Leveraging spatial scale and temporal variation to optimize estimates of invasive spread rates

Estimating the extent and speed of an invasive species spread is crucial for optimizing surveys and management, but this estimation is challenging due to the scale-dependent nature of spread. For instance, when discretizing occurrence data to grids to estimate the extent of invaded ranges, larger cells can decrease boundary precision, while smaller cells can increase the risk of missing invaded areas. Moreover, on shorter timescales such as year-to-year comparisons, spread rates can exhibit lags, accelerations, and slowdowns. We present a multiscale spread optimization methodology developed for the spotted lanternfly (Lycorma delicatula), a pest impacting grapes that is spreading westward across the continental United States. We analyzed a dataset of >900,000 occurrence records covering spread from this pests initial detection in eastern Pennsylvania in 2014 to its invasion front in Chicago, IL, in 2023. First, we delineated the annual U.S. invasion front using square grids with varying cell sizes and -convex hulls with different boundary resolutions. For each method and scale, we regressed invaded range area against year using both simple linear and logistic nonlinear models. Coarser spatial scales yielded faster estimated spread rates, and logistic models outperformed linear regressions, indicating a lag, acceleration, and slowdown in annual spread rate. Next, to determine the spatial scale that best captured the invasion front boundary, we used cross-validation, optimizing the F{beta} metric, which balances recall and precision. Emphasizing recall generally favored coarser spatial scales, and - convex hulls outperformed grid-based methods in delineating invasion fronts. Finally, L. delicatula has dispersed long distances from its primary epicenter, establishing satellite populations. We delineated each satellite population each year since its inception using optimized -hull values and measured their year-to-year boundary expansion. Like the primary epicenter, these satellite populations showed accelerating expansion, at least until merging with the primary invasion. Overall, the expansion rate of the primary invasion has slowed since 2017, decreasing from a maximum of 21 km/year, possibly due in part to control efforts, although the exact cause remains unresolved. Considering spatial scale and temporal variation can optimize the analysis of invasive spread and motivate early interventions to manage nascent epicenters before their spread accelerates.

ecology↗

bioRxiv2023

Quantifying population resistance to climatic variability: The invasive spotted lanternfly grape pest is buffered against temperature extremes in California

Temperature time series data are a composition of average trends and stochastic variability that together shape population dynamics. However, models of temperature-dependent species often overlook variability, focusing solely on growth rate under average conditions. When models omit variability, they can inaccurately predict the dynamics that underlie the establishment of invasive pests sensitive to temperature fluctuations. Here, we conduct a stochastic modeling study of spotted lanternfly (Lycorma delicatula), a univoltine grape pest, which has invaded grape growing regions of the eastern U.S. due to human transport leading to frequent establishment of populations in urban and suburban areas. As spotted lanternfly continues to be transported to new grape growing regions and climate change alters variability, it is vital to predict its establishment potential. Although it overwinters as diapausing eggs, experiments suggest that diapause is plastic and not necessary for survival. We developed a deterministic stage-age-structured partial differential equation model of diapausing and non-diapausing populations. We derived a new metric quantifying population resistance to climatic variability defined as the level of stochasticity that leads to negative growth compared to average conditions. We simulated growth rate and resistance to variability across a range of average temperature conditions and stochasticity. We then analyzed how variability and diapause interact with survival, fecundity, and development to affect population dynamics. Finally, we estimated establishment potential across all U.S. cities. Diapausing populations were typically more resistant than non-diapausing populations because diapause enhances overwintering egg survival during winter cold waves, while allowing accelerated development and increased fecundity during summer and fall heat waves. Establishment potential is especially underestimated in important grape growing regions of California if models of diapausing populations omit variability. By quantifying population resistance to climatic variability, we gain a fuller understanding of invasive species establishment in todays stochastic and changing climate.

ecology↗

bioRxiv2023

lydemapr: an R package to track the spread of the invasive Spotted Lanternfly (Lycorma delicatula, White 1845) (Hemiptera, Fulgoridae) in the United States

A crucial asset in the management of invasive species is the open-access sharing of data on the range of invaders and the progression of their spread. Such data should be current, comprehensive, consistent, and standardized, to support reproducible and comparable forecasting efforts among multiple researchers and managers. Here, we present the lydemapr R package containing spatiotemporal data and mapping functions to visualize the current spread of the spotted lanternfly (Lycorma delicatula, White 1841) in the Western Hemisphere. The spotted lanternfly is a forest and agricultural pest in the eastern Mid-Atlantic region of the U.S., where it was first discovered in 2014. As of 2022, it has been found in 12 states according to state and federal departments of agriculture. However, the lack of easily accessible, fine-scale data on its spread hampers research and management efforts. We obtained multiple memoranda-of-understanding from several agencies and citizen-science projects, gaining access to their internal data on spotted lanternfly point observations. We then cleaned, harmonized, anonymized, and combined the individual data sources into a single comprehensive dataset. The resulting dataset contains spatial data gridded at the 1 km2 resolution, with yearly information on the presence/absence of spotted lanternflies, establishment status, and population density across 658,392 observations. The lydemapr package will aid researchers, managers, and the public in their understanding, modeling, and managing of the spread of this invasive pest.

ecology↗

bioRxiv2023

Predicting and quantifying coexistence outcomes between resident and invading species using trait and abundance data

A major challenge in invasion ecology is determining which introduced species pose a threat to resident species through competitive displacement. Here, we provide a statistical framework rooted in coexistence theory to calculate coexistence outcomes - including competitive displacement - between resident and invading species. Advantageously, our framework uses readily available trait and abundance data rather than the demographic data traditionally used in coexistence theory applications which is often difficult to collect for most species. Our framework provides methods for predicting displacement that has yet to manifest in incipient invasions, and for quantifying displacement in ongoing invasions. We apply this framework to the native and introduced gecko species on Curacao and predict the displacement of all three native species by introduced species and quantify that the displacement of one native species is already underway. Our results affirm that trait and abundance data are suitable proxies to reasonably predict and quantify coexistence outcomes.

ecology↗

bioRxiv2023

The great acceleration of island saturation by species introductions in the Anthropocene has altered species-area relationships

The species-area relationship (SAR) is a fundamental pattern of island biogeography which is often curvilinear due to reduced accumulation of species on mid-sized island caused by island isolation and the lack of speciation present on larger islands. The curvature of SARs represents lower saturation of species on mid-sized islands and therefore accelerated species accumulation should linearize island SARs. In the Anthropocene, island species accumulation has accelerated from introduced species. We hypothesize three new patterns. First, the saturation of species for the most unsaturated islands should increase more from introduced species than other islands. Second, SARs should become more linear as islands accumulate more species. Third, introduced species should greatly accelerate the island saturation process. We assessed these patterns for the reptile and amphibian of the Caribbean, a global hotspot of biodiversity. Mid-sized Caribbean islands are now more saturated causing a linearization of contemporary herpetofauna SARs resulting from a ca. 30 myr and 40 myr acceleration of island saturation for reptiles and amphibians, respectively. Thus, humans within the last few hundreds of years--starting with European colonization of the Americas--have greatly accelerated the natural process of island saturation by 30 million years within the Caribbean global biodiversity hotspot.

ecology↗

bioRxiv2022

Predicting host associations of the invasive spotted lanternfly on trees across the USA

Global impacts of invasive insect pests cost billions of dollars annually, but the impact of any individual pest species depends on the strength of associations with economically important plant hosts. Estimating host associations for a pest requires surveillance field surveys that observe pest association on plant species within an invaded area. However, field surveys often miss rare hosts and cannot observe associations with plants found outside the invaded range. Associations for these plants instead are estimated with experimental assays such as controlled feeding trials, which are time consuming and for which few candidate hosts can be tested logistically. For emerging generalist pests, these methods are unable to rapidly produce estimates for the hundreds of potential suitable hosts that the pest will encounter as it spreads within newly invaded regions. In such cases, association data from these existing methods can be statistically leveraged to impute unknown associations. Here we use phylogenetic imputation to estimate potential host associations in an emergent generalist forest pest in the U.S., the spotted lanternfly (Lycorma delicatula; SLF). Phylogenetic imputation works when closely related plants have similar association strengths, termed phylogenetic signal in host association, which is common in phytophagous insects. We first aggregated known SLF host associations from published studies. Existing research has estimated association strengths for 144 species across both the invaded and native range of SLF. These known associations exhibited phylogenetic signal. We then developed two protocols that combined known host association data and fit phylogenetic imputation models based on hidden state prediction algorithms to estimate association strength for 569 candidate tree species found across the continental U.S. Of candidate species considered, 255 are predicted to have strong associations with SLF in the U.S. and can be found in several clades including Juglandaceae, Rutaceae, Salicaceae, and Sapindaceae. Uninvaded regions with the highest numbers of these strongly associated species include midwestern and west coast states such as Illinois and California. Survey efforts for SLF should be focused on these regions and predicted species, which should also be prioritized in experimental assays. Phylogenetic imputation scales up existing host association data, and the protocols we present here can be readily adapted to inform surveillance and management efforts for other invasive generalist plant pests.

ecology↗

bioRxiv2022

Detecting stabilizing, directional, and disruptive patterns of anthropogenic species loss with general models of nonrandom extinction

The selective landscape that gave rise to Earths species has shifted in the Anthropocene. Humans have accelerated extinction pressures, making efforts to detect general non-random patterns of extinction increasingly important. Much research has focused on detecting which traits make some species more likely to go extinct, such as large body size and slow reproductive rate in animals, limited dispersal in vascular plants, and narrow habitat requirements in cacti. However, general models for such non-random extinction are lacking. Here, we adapt the three general models of natural selection to classify non-random extinction as directional, disruptive, or stabilizing extinction. We develop a quantitative method for testing which general extinction model best describes observed data and apply it to the Caribbean lizard genus Leiocephalus as a case study. We surveyed the literature for recorded last occurrence for extinct and threat status for extant species. Eight species have gone extinct and ten are predicted to go extinct soon. Past extinctions in Leiocephalus showed directional extinction of large bodied species, while future-predicted extinctions exhibited a more complex extinction model similar to both random and stabilizing extinction with respect to body size. Similarly, future-predicted extinctions exhibited stabilizing extinction with respect to limb and tail lengths. Lizards with either very long or very short appendages are most likely to go extinct in the future. This shift from directional to stabilizing extinction for Leiocephalus is consistent with hunting, introduced predators, and habitat loss that first increased extinction pressure on the largest species and then extinction pressure on species that deviate from an adaptive peak centered on a generalist ground-lizard body plan. As adaptive optima shift in the Anthropocene, general models of non-random extinction are essential to developing a mature strategy for future successful conservation efforts.

ecology↗

bioRxiv2022

Multiscale assessment of oviposition habitat associations and implications for management in the spotted lanternfly (Lycorma delicatula), an emerging invasive pest

O_LIControl of incipient invaders--established invasive species in the early stages of spreading-- can be inhibited by incomplete knowledge of the species habitat use. By identifying consistent habitat associations for incipient invaders early, control efforts can be more effective. Yet, because habitat associations are the result of multiscale processes, approaches are needed for integrating data collected across scales to identify them. C_LIO_LIWe employed a hierarchical, multiscale approach to identify oviposition habitat associations in the spotted lanternfly (Lycorma delicatula) an incipient invasive species of high concern in the United States. We targeted the oviposition habitat spatial scales most likely to be used by lanternflies and the spatial scales of explanatory environmental variables most easily used by managers to locate egg masses to control. We explored whether habitat associations exist for oviposition habitat use and how well habitat use is explained by the duration sites have been invaded. Finally, because habitat associations are likely driven by fitness, we determined if the use of any habitat types were associated with higher fitness as measured by the number of eggs per egg mass (i.e., fecundity). C_LIO_LISpotted lanternflies exhibited oviposition habitat associations at the landscape, site, and tree scales. Overall, lanternflies oviposited more frequently at sites and on trees with low canopy cover in the surrounding landscape, on trees from the Acer genus, and in the crowns of larger trees beyond the reach of managers without special equipment. The duration a site had been invaded had opposing effects at the site and tree scales which indicates the need for scale-dependent management approaches. C_LIO_LIDespite the consistent habitat associations identified, no environmental variables explained variation in lanternfly fecundity, indicating more work is needed to identify environmental drivers of spotted lanternfly fitness. C_LIO_LISynthesis and applications. Our results indicate a multiscale approach is needed for spotted lanternfly control with unique strategies for locating egg masses at sites and on trees that vary in invasion duration. Additionally, our results suggest that multiscale investigations of habitat associations would likely inform the control of other invasive species as well. C_LI

ecology↗

bioRxiv2022

Elevated human footprint on islands promotes both introduction and extinction probability of insular reptiles at opposite ends of geographic, evolutionary and ecological continua

Species ranges are changing in the Anthropocene, the ranges of introduced species are expanding, while extinction-prone species are contracting. Introductions and extinctions are both caused by how species respond to human impacts, but it is unknown why the ranges of some species expand and some contract. Here, we test that this opposite response of human impact is due to introduced and extinction-prone species falling at opposite ends of geographic, evolutionary, or ecological trait continua. We constructed a database of native range maps, traits, phylogenetic relationships, and the introduction and extinction-prone status of squamate reptiles with ranges native to the Western Hemisphere. Across >3,000 snake and lizard species (88% of known native squamates), 142 had been introduced elsewhere and 483 were extinction-prone (i.e., extinct, vulnerable, threatened). To explain variation in status, we first tested if the same human-impacted regions in the Americas contained the native ranges of species of either status. Second, we tested for phylogenetic signal in species status. Finally, we tested the explanatory power of multiple trait continua. The native ranges of introduced and extinction-prone reptiles were clustered in island regions with high human impact vs. mainland regions with lower human impact. Phylogenetic signal was weak for status, but introduced and extinction-prone species were clustered in different clades. All geographic and ecological traits that explained both statuses supported the opposite ends hypothesis. Introduced species had larger, edgier ranges, while extinction-prone species had smaller, simpler ranges. Introduced species were mostly herbivorous/omnivorous, while extinction-prone species were mostly carnivorous. Introduced species produced larger clutches, while extinction-prone species were smaller in body size. In the Anthropocene, the naive ranges of introduced and extinction-prone species are in the same human-impacted regions where trait continua, having opposite effects, determine whether species ranges expand or contract in the continuing face of global change.

ecology↗

bioRxiv2021

Paninvasion severity assessment of a US grape pest to disrupt the global wine market

Economic impacts from plant pests are often felt at the regional scale, yet some impacts expand to the global scale through the alignment of a pests invasion potentials. Such globally invasive species (i.e., paninvasives) are like the human pathogens that cause pandemics. Like pandemics, assessing paninvasion risk for an emerging regional pest is key for stakeholders to take early actions that avoid market disruption. Here, we develop the paninvasion severity assessment framework and use it to assess a rapidly spreading regional U.S. grape pest, the spotted lanternfly planthopper (Lycorma delicatula; SLF), to spread and disrupt the global wine market. We found that SLF invasion potentials are aligned globally because important viticultural regions with suitable environments for SLF establishment also heavily trade with invaded U.S. states. If the U.S. acts as an invasive bridgehead, Italy, France, Spain, and other important wine exporters are likely to experience the next SLF introductions. Risk to the global wine market is high unless stakeholders work to reduce SLF invasion potentials in the U.S. and globally.

ecology↗

bioRxiv2020

phyr: An R package for phylogenetic species-distribution modelling in ecological communities

O_LIModel-based approaches are increasingly popular in ecological studies. A good example of this trend is the use of joint species distribution models to ask questions about ecological communities. However, most current applications of model-based methods do not include phylogenies despite the well-known importance of phylogenetic relationships in shaping species distributions and community composition. In part, this is due to lack of accessible tools allowing ecologists to fit phylogenetic species distribution models easily. C_LIO_LITo fill this gap, the R package phyr (pronounced fire) implements a suite of metrics, comparative methods and mixed models that use phylogenies to understand and predict community composition and other ecological and evolutionary phenomena. The phyr workhorse functions are implemented in C++ making all calculations and model estimations fast. C_LIO_LIphyr can fit a variety of models such as phylogenetic joint-species distribution models, spatiotemporal-phylogenetic autocorrelation models, and phylogenetic trait-based bipartite network models. phyr also estimates phylogenetically independent trait correlations with measurement error to test for adaptive syndromes and performs fast calculations of common alpha and beta phylogenetic diversity metrics. All phyr methods are united under Brownian motion or Ornstein-Uhlenbeck models of evolution and phylogenetic terms are modelled as phylogenetic covariance matrices. C_LIO_LIThe functions and model formula syntax we propose in phyr serves as a simple and unified framework that ignites the use of phylogenies to address a variety of ecological questions. C_LI

ecology↗

bioRxiv2018

Benefits And Limitations Of Three-Dimensional Printing Technology For Ecological Research

BackgroundEcological research often involves sampling and manipulating non-model organisms that reside in heterogeneous environments. As such, ecologists often adapt techniques and ideas from industry and other scientific fields to design and build equipment, tools, and experimental contraptions custom-made for the ecological systems under study. Three-dimensional (3D) printing provides a way to rapidly produce identical and novel objects that could be used in ecological studies, yet ecologists have been slow to adopt this new technology. Here, we provide ecologists with an introduction to 3D printing.\n\nResultsFirst, we give an overview of the ecological research areas in which 3D printing is predicted to be the most impactful and review current studies that have already used 3D printed objects. We then outline a methodological workflow for integrating 3D printing into an ecological research program and give a detailed example of a successful implementation of our 3D printing workflow for 3D printed models of the brown anole, Anolis sagrei, for a field predation study. After testing two print media in the field, we show that the models printed from the less expensive and more sustainable material (blend of 70% plastic and 30% recycled wood fiber) were just as durable and had equal predator attack rates as the more expensive material (100% virgin plastic).\n\nConclusionsOverall, 3D printing can provide time and cost savings to ecologists, and with recent advances in less toxic, biodegradable, and recyclable print materials, ecologists can choose to minimize social and environmental impacts associated with 3D printing. The main hurdles for implementing 3D printing - availability of resources like printers, scanners, and software, as well as reaching proficiency in using 3D image software - may be easier to overcome at institutions with digital imaging centers run by knowledgeable staff. As with any new technology, the benefits of 3D printing are specific to a particular project, and ecologists must consider the investments of developing usable 3D materials for research versus other methods of generating those materials.

ecology↗