The Experts below are selected from a list of 8022 Experts worldwide ranked by ideXlab platform
Andrew M Liebhold - One of the best experts on this subject based on the ideXlab platform.
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comparing generalized and customized spread models for nonnative Forest Pests
Ecological Applications, 2020Co-Authors: Emma J Hudgins, Andrew M Liebhold, Brian LeungAbstract:While generality is often desirable in ecology, customized models for individual species are thought to be more predictive by accounting for context specificity. However, fully customized models require more information for focal species. We focus on pest spread and ask: How much does predictive power differ between generalized and customized models? Further, we examine whether an intermediate "semi-generalized" model, combining elements of a general model with species-specific modifications, could yield predictive advantages. We compared predictive power of a generalized model applied to all Forest pest species (the generalized dispersal kernel or GDK) to customized spread models for three invasive Forest Pests (beech bark disease [Cryptococcus fagisuga], gypsy moth [Lymantria dispar], and hemlock woolly adelgid [Adelges tsugae]), for which time-series data exist. We generated semi-generalized dispersal kernel models (SDK) through GDK correction factors based on additional species-specific information. We found that customized models were more predictive than the GDK by an average of 17% for the three species examined, although the GDK still had strong predictive ability (57% spatial variation explained). However, by combining the GDK with simple corrections into the SDK model, we attained a mean of 91% of the spatial variation explained, compared to 74% for the customized models. This is, to our knowledge, the first comparison of general and species-specific ecological spread models' predictive abilities. Our strong predictive results suggest that general models can be effectively synthesized with context-specific information for single species to respond quickly to invasions. We provided SDK forecasts to 2030 for all 63 United States Pests in our data set.
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spatial patterns of discovery points and invasion hotspots of non native Forest Pests
Global Ecology and Biogeography, 2019Co-Authors: Samuel F Ward, Andrew M Liebhold, Songlin FeiAbstract:Aim: Establishments of non‐native Forest Pests (insects and pathogens) continue to increase worldwide with growing numbers of introductions and changes in invasion pathways. Quantifying spatio‐temporal patterns in establishment locations and subsequent invasion dynamics can provide insight into the underlying mechanisms driving invasions and assist biosecurity agencies with prioritizing areas for proactive surveillance and management. Location: United States of America. Time period: 1794–2018. Major taxa studied: Insecta, plant pathogens. Methods: Using locations of first discovery and county‐level occurrence data for 101 non‐native Pests across the contiguous USA, we (a) quantified spatial patterns in discovery points and county‐level species richness with spatial point process models and spatial hotspot analyses, respectively, and (b) identified potential proxies for propagule pressure (e.g., human population density) associated with these observed patterns. Results: Discovery points were highly aggregated in space and located in areas with high densities of ports and roads. Although concentrated in the north‐eastern USA, discovery points also occurred farther west and became less aggregated as time progressed. Invasion hotspots were more common in the north‐east. Geographic patterns of discovery points and hotspots varied substantially among pest origins (i.e., global region of Pests’ native ranges) and pest feeding guilds. Significant variation in invasion richness was attributed to the patterns of first discovery locations. Data and shapefiles comprising analyses are provided. Main conclusions: Use of spatial point pattern analyses provided a quantitative characterization of the central role of human activities in establishment of non‐native Pests. Moreover, the decreased aggregation of discovery points through time suggests that invasion pathways to certain areas in the USA have either been created or intensified by human activities. Overall, our results suggest that spatio‐temporal variability in the intensity of invasion pathways has resulted in marked geographic patterns of establishment and contributed to current macroscale patterns of pest invasion in the USA.
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predicting the spread of all invasive Forest Pests in the united states
Ecology Letters, 2017Co-Authors: Emma J Hudgins, Andrew M Liebhold, Brian Leung, Regan EarlyAbstract:We tested whether a general spread model could capture macroecological patterns across all damaging invasive Forest Pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all Pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of Forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility - well-studied predictors of establishment - should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread.
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historical accumulation of nonindigenous Forest Pests in the continental united states
BioScience, 2010Co-Authors: Juliann E Aukema, Deborah G. Mccullough, Betsy Von Holle, Andrew M Liebhold, Kerry O Britton, Susan J FrankelAbstract:Nonindigenous Forest insects and pathogens affect a range of ecosystems, industries, and property owners in the United States. Evaluating temporal patterns in the accumulation of these nonindigenous Forest Pests can inform regulatory and policy decisions. We compiled a comprehensive species list to assess the accumulation rates of nonindigenous Forest insects and pathogens established in the United States. More than 450 nonindigenous insects and at least 16 pathogens have colonized Forest and urban trees since European settlement. Approximately 2.5 established nonindigenous Forest insects per year were detected in the United States between 1860 and 2006. At least 14% of these insects and all 16 pathogens have caused notable damage to trees. Although sap feeders and foliage feeders dominated the comprehensive list, phloem- and wood-boring insects and foliage feeders were often more damaging than expected. Detections of insects that feed on phloem or wood have increased markedly in recent years.
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mapping host species abundance of three major exotic Forest Pests
Res. Pap. NE-726. Newtown Square PA: U.S. Department of Agriculture Forest Service Northeastern Research Station. 11 p., 2005Co-Authors: Randall S Morin, Andrew M Liebhold, Eugene R Luzader, Andrew J Lister, Kurt W Gottschalk, Daniel TwardusAbstract:Periodically over the last century, Forests of the Eastern United States devastated by invasive Pests. We used existing data to predict the geographical extent of future damage from beech bark disease (BBD), hemlock woolly adelgid (HWA), and gypsy moth. The distributions of host species of these alien Pests were mapped in 1-km2 cells by interpolating host basal area/ha from 93,611 Forest-inventory plots in 37 states. The interpolated surfaces were adjusted for Forest density (percent land cover) by multiplying values by an estimate of percent Forest cover derived from existing land-cover maps (30-m2 cells). According to our estimates, BBD currently occupies only about 27 percent of its potential range in land area, but has invaded more than 54 percent in total host density. HWA occupies nearly 26 percent of its potential range in land area, and about one-quarter in total host density. Gypsy moth occupies only 23 percent of its potential range in the Eastern United States, and only 26 percent in total host density.
Michael J. Wingfield - One of the best experts on this subject based on the ideXlab platform.
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urban trees bridge heads for Forest pest invasions and sentinels for early detection
Biological Invasions, 2017Co-Authors: Trudy Paap, Michael J. Wingfield, T BurgessAbstract:Urban trees have been increasingly appreciated for the many benefits they provide. As concentrated hubs of human-mediated movement, the urban landscape is, however, often the first point of contact for exotic Pests including insects and plant pathogens. Consequently, urban trees can be important for accidentally introduced Forest Pests to become established and potentially invasive. Reductions in biodiversity and the potential for stressful conditions arising from anthropogenic disturbances can predispose these trees to pest attack, further increasing the likelihood of exotic Forest Pests becoming established and increasing in density. Once established in urban environments, dispersal of introduced Pests can proceed to natural Forest landscapes or planted Forests. In addition to permanent long-term damage to natural ecosystems, the consequences of these invasions include costly attempts at eradication and post establishment management strategies. We discuss a range of ecological, economic and social impacts arising from these incursions and the importance of global biosecurity is highlighted as a crucially important barrier to pest invasions. Finally, we suggest that urban trees may be viewed as ‘sentinel plantings’. In particular, botanical gardens and arboreta frequently house large collections of exotic plantings, providing a unique opportunity to help predict and prevent the invasion of new Pests, and where introduced Pests with the capacity to cause serious impacts in Forest environments could potentially be detected during the initial stages of establishment. Such early detection offers the only realistic prospect of eradication, thereby reducing damaging ecological impacts and long term management costs.
Emma J Hudgins - One of the best experts on this subject based on the ideXlab platform.
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comparing generalized and customized spread models for nonnative Forest Pests
Ecological Applications, 2020Co-Authors: Emma J Hudgins, Andrew M Liebhold, Brian LeungAbstract:While generality is often desirable in ecology, customized models for individual species are thought to be more predictive by accounting for context specificity. However, fully customized models require more information for focal species. We focus on pest spread and ask: How much does predictive power differ between generalized and customized models? Further, we examine whether an intermediate "semi-generalized" model, combining elements of a general model with species-specific modifications, could yield predictive advantages. We compared predictive power of a generalized model applied to all Forest pest species (the generalized dispersal kernel or GDK) to customized spread models for three invasive Forest Pests (beech bark disease [Cryptococcus fagisuga], gypsy moth [Lymantria dispar], and hemlock woolly adelgid [Adelges tsugae]), for which time-series data exist. We generated semi-generalized dispersal kernel models (SDK) through GDK correction factors based on additional species-specific information. We found that customized models were more predictive than the GDK by an average of 17% for the three species examined, although the GDK still had strong predictive ability (57% spatial variation explained). However, by combining the GDK with simple corrections into the SDK model, we attained a mean of 91% of the spatial variation explained, compared to 74% for the customized models. This is, to our knowledge, the first comparison of general and species-specific ecological spread models' predictive abilities. Our strong predictive results suggest that general models can be effectively synthesized with context-specific information for single species to respond quickly to invasions. We provided SDK forecasts to 2030 for all 63 United States Pests in our data set.
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predicting the spread of all invasive Forest Pests in the united states
Ecology Letters, 2017Co-Authors: Emma J Hudgins, Andrew M Liebhold, Brian Leung, Regan EarlyAbstract:We tested whether a general spread model could capture macroecological patterns across all damaging invasive Forest Pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all Pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of Forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility - well-studied predictors of establishment - should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread.
Dagmar Haase - One of the best experts on this subject based on the ideXlab platform.
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of bugs and men how Forest Pests and their management strategies are perceived by visitors of an urban Forest
Urban Forestry & Urban Greening, 2019Co-Authors: Martin Gutsch, Neele Larondelle, Dagmar HaaseAbstract:Abstract Larger Forest patches in urban areas are highly valuable recreation sites that provide the urban population with various ecosystem services. Yet they are highly vulnerable to biological Pests, especially in the light of climate change. The growing need to intervene against Forest Pests needs to be clearly but carefully communicated to the urban Forest visitors in order to minimize conflicts. In this paper, a survey with 554 complete responses, conducted in the Forest district of the “Teufelssee” in south-east Berlin, Germany, sheds first light on visitors’ perceptions of biological Pests and their management. Results of Chi square statistics and a series of Logit models indicate a clear predisposition against pesticide or biocide interventions, while at the same time, showing remarkable positive tendencies towards mechanical interventions or measures taken on the individual-tree level. There are positive correlations between the age and the knowledge about Pests (Kendall-Tau-b τB = 0.165) and between the age and the knowledge about pest regulation (τB = 0.182). Positive correlations also exist between level of education and pest knowledge (τB = 0.1) and knowledge about their regulation (τB = 0.08), respectively. Elderly respondents tend to vote for faster interventions. Overall, a large majority of the respondents would be willing to participate in a volunteer mapping of Pests while visiting the Forest. The results of this study can be used to inform urban Forest management to modify and optimize their communication and information policies concerning Pests and substantiated interventions.
Regan Early - One of the best experts on this subject based on the ideXlab platform.
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predicting the spread of all invasive Forest Pests in the united states
Ecology Letters, 2017Co-Authors: Emma J Hudgins, Andrew M Liebhold, Brian Leung, Regan EarlyAbstract:We tested whether a general spread model could capture macroecological patterns across all damaging invasive Forest Pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all Pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of Forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility - well-studied predictors of establishment - should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread.