Interplay between contamination and the risk of invasive species or genetically modified organisms at population and landscape scales.Wayne G. Landis, Audrey M. Colnar, Ananda Seebach and Laura J. Sellens, Institute of Environmental Toxicology, Huxley College of the Environment, Western Washington University, Bellingham WA , USA

In many ways the factors governing the establishment of invasive species and genetically modified organisms (GMOs) are closely related topics. The introduction and establishment of invasive species or genetically modified organisms appears to be dependent upon the characteristics of the individuals, the life history strategies of the invasive, the pattern of habitats in the landscape and other stressors in the environment. Modeling by Deines, Chen and Landis (2005) has demonstrated that contaminants can influence the likelihood of introduction by affecting competitors, changing rates of migration to other habitats or altering the fitness of the invasive. Changes in the arrangement and size of habitat patches via indirect effects can have as large an effect as any direct effect when the number of and location of beachheads are changed. In the case of GMO bentgrass for herbicide resistance, the introduction of the specific herbicide can alter the selection landscape, allowing hybrids a selective advantage and increasing the probability that herbicide resistant strains of hybridizing species could result. In summary, contaminants may discourage or encourage the establishment of invasives or GMOs by altering the selective landscape at multiple biological scales.

START

Control District Extinction of

Plant

Establishment of Plant

SECONDARY SOURCE OF

GENE

SOURCE HABITATS

EFFECTS IMPACTS

Plug

Seed

Pollen Flow

Sagebrush

Grassland

Canals

Agricultural/ Range

Urban

Pollinization/Hybridization

Seedling Growth

Vegetative Translocation

Controlling Factors

Physical Parameters

Biological Parameters

Anthropogenic Parameters

Competitive Interactions

GrazingHabitat Suitability

Duration of Seed

Seed Size

Mowing

Glyphosate Application

Size of Source Patch

Wind Speed

Wind Direction

Pollen Size

Pollen Viability

Synchrony of Compatible Plants

Proximity of Compatible Plants

Machinery Transport

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Location of Compatible Plants

Water Flow in Canals

Selective Pressure

Backcrossing

Non-expression of gene

Local scale (-1) of the hierarchical conceptual model. This scale shows the pathways by which the gene could travel at the individual level. The solid lines show movement via pollen, the dashed line shows movement through seeds, and the dash-dot line shows movement through vegetative escape. The factors influencing movement for each of these pathways are shown. The point influenced by the herbicide application is in red.

Stolon

PATHWAYS OF STRESSOR

GMO Conceptual ModelToxicant Interaction

Figure 2. Hierarchical Patch Dynamics paradigm (HPDP) The HPDP allows the incorporation of different layers of scale with a framework for the

interactions at each level (Wu and David 2002)

Level +1

Level 0

Level -1

Higher LevelHigher Level

Focal LevelFocal Level

Lower LevelLower Level

Context,constraints, control, containment, boundary conditions

Components, mechanisms, initial conditions

Vertical Structure-Asymmetric relationships, Loose vertical coupling, a variety of ordering principals.

Horizontal Structure-Symmetric relationships, Loose horizontal coupling, a variety of strengths of interactions between components.

Dynamic Dynamic

InteractionsInteractions

Regional ScaleLarge-scale patches beyond Cherry Point

Introduction at the Local Scale

Colonization at the Local Scale

Dispersal (via reproduction) and Migration

Invasive Spread at the Focal Scale

Invasive Spread at the Regional Scale

Stages of Invasion

Establishment at the Local Scale

Integrated Hierarchical Conceptual Models

Local Scale Habitat patches within

Cherry Point

Focal ScalePatchy populations within the habitat

patches within Cherry Point

Figure 1. Invasive species and Regional Risk Assessment

Impact typesReplacement of economically, culturally or socially important speciesDecrease in available habitat for significant speciesDecrease in biodiversityTransformation of habitat typeDisease (human. plant and wildlife)Change in population dynamicsAlterations of landscape structure

Mortality due to disease or parasitismPredationInterspecific competitionIntraspecific competitionAlteration of the physical habitatAlteration of nutrient pathwaysChange in migration matrix

Pathogens (chestnut blight, West Nile virus, HIVWildlife species (pheasant, house sparrow, starlings, green crab, mongoose)Plant species (kudzu, Spartina)Insect pests

Human Accidental IntroductionsTankers (Ballast water and hulls)Trucking (Cargo, plants and animals)Aircraft ( On clothing, foodstuffs)

Human Intentional IntroductionsOrnamentalsCropsGEOsBiocontrol organismsRecreational introductions

Natural IntroductionsSpecies shifts and expansions due to climate changeColonization due to natural events (storms, currents, winds)

Source Habitat Impact

Stressor EffectHabitat typesMarine near shoreEstuariesRivers and streamsAgricultural areasUrban ParksCommercial areasIndustrial areasForests

Landis et al, 2004Risk Analysis

Background and Theory

Abstract

1

In order to estimate risk we base our approach upon the regional model developed by Landis and Wiegers (1997) that incorporates sources, stressors, habitats, effects and impacts (Figure 1). The relative risk model (RRM) has been adapted to the estimate of risk for invasive species (Landis 2004). The sources correspond to the areas or transportation activities from which invasives are derived. The stressors are the invasives. Habitats correspond to the specific locations and areas that are colonized by the introduced species. Interactions with other species and the physical attributes of the ecological system generate a series of effects that when they negatively affect the valued components result in impacts.

One of the biggest difficulties in estimating risk in ecological systems is the problem of dealing with multiple scales. We have adopted the Hierarchical Patch Dynamics paradigm (HPDP) as developed by Wu and colleagues (Wu and Loucks 1995, Wu and David 2002). This approach incorporates a variety of scales into an organizational construct that allows the description of the invasive-risk process at scales from the individual to the landscape. This is described in the next part of the presentation.

We have incorporated the HPDP into the RRM framework so that all hierarchies of scale are integrated with the risk assessment process (Figure 3). Audrey Colnar has applied the RRM-HPDP process to the risk assessment for the European Green Crab (Colnar and Landis 2007). The hierarchical approach allowed organization of the conceptual model by both scale and risk assessment process so that risk could be calculated. The effect of contaminants upon the invasives can be incorporated at each of these scales. Uncertainty is estimated using Monte Carlo analysis. This same approach has been used to estimate risks due to the Nun Moth, the Asian Oyster and for genetically modified organisms.

General Model2

Application-Invasives3

Figure 3. Basic framework for risk assessment incorporating invasive species

Three risk assessments have been performed for a number of endpoints at Cherry Point, Washington (Figure 4), one dealing with contaminants and physical stressors and two with invasive species. The methods used were comparable, including the Relative Risk Method and similar processes of ranking. The results are summarized and compared below.

-300 -200 -100 0 100 200 300

Surf smelt

Pacific herring

Macroalgae

Littleneck clam

Juvenile English sole

Juvenile Dungeness crab

Great blue heron

Eelgrass

Coho Salmon

Risk Score

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essm

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En

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oin

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Relative risk from S. muticum to each assessment endpoint. Positive values indicate risk while negative values indicate potentially beneficial effects on the endpoints. In the case of Sargassum the habitat it provides results in negative scores for many of the endpoints.

Figure 5. Chemical and Physical Stressors (Hart Hayes and Landis 2004)

Figure 7. Sargassum muticum (Seebach et al.)

Figure 6. European Green Crab (Colnar and Landis 2007)

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CS DC ES GBH LC SSE

CS DC ES GBH LC SSE

CS DC ES GBH LC SSE

CS DC ES GBH LC SSE

CS DC ES GBH LC SSE

Point RobertsTotal Risk Score 1449

Cherry PointTotal Risk Score 2206

Drayton HarborTotal Risk Score 3072

LummiTotal Risk Score 3564

Birch BayTotal Risk Score 2372

Alden BankTotal Risk Score 228

Relative risk to biological assessment endpoints in sub-regions

Relative risk to assessment endpoints in sub-regions. Y-axis is the relative risk score. X-axis from left to right: CS = Coho salmon, DC = juvenile Dungeness crab, ES = juvenile English sole, GBH = great blue heron, LC = native littleneck clam and SSE = surf smelt embryos. The contaminants or physical stressors did not enhance any of the chosen endpoints.

Conclusions5

Unlike contaminants, the European Green Crab had risks to some endpoints, but would enhance others. The enhancement is due to the crab acting as a food source. These risks are for an El Nino year when the currents would be more likely to spread the European Green Crab from coastal Washington.

Application-Genetically Modified Organisms-Sellens and Landis4

Figure 4. Cherry Point Washington study area

The invasive species can provide habitat or a food resource for a number of endpoints. Subsequent assessment with Asian Oyster provided a similar pattern of both risk and enhancement. Nun moth has been the exception. The alteration of forests affected a number of endpoints at a large scale.

Many aspects of the spread of genetically modified organisms are similar to invasive species. In the case of GMOs the gene can be the marker that is being considered. In this instance we modeled a risk scenario based upon a herbicide resistant strain of bentgrass near Madras, Oregon. Creeping bentgrass (Agrostis stolonifera L.) is a high value golf course turf grass. It differs from previously deregulated species in having a stoloniferous growth habit, and in having at least 13 native and non-native species with which it can freely hybridize. In 2003, eight fields totaling approximately 162 ha of RoundUp Ready® creeping bentgrass were grown within a 4,453 ha control district outside of Madras, Oregon. Watrud et al. (2004) found pollen-mediated gene flow up to 21 km from this site, about 10 times the expected distance. Reichman et al. (2006) has demonstrated that gene flow has occurred to surrounding populations.

Figure 8 presents the conceptual model at the -1 scale for the bentgrass that incorporates glyphosate application. This stressor is one of three that form a selective pressure on the host.

The top portion shows the classic stressor-receptor-impact flow chart for environmental risk assessment and the bottom portion shows how the RRM can be applied directly to GM bentgrass.

Figure 10. Total risk estimate for each assessment endpoint.

Figure 9. Local level diagram of gene flow and establishment of resistant plants.

Risk to the endpoint species can be calculated for the region under study.

1. It is possible to incorporate contaminant stressors into a risk assessment evaluation with invasive species and genetically modified organisms.

2. The patterns of risk expressed by invasives tend to be different than from contaminants towards typical endpoints.

3. In the evaluation of GMOs contaminants can be incorporated as a selective pressure towards both the GMO and the organisms receiving the genetic construct.