Refinement of weed risk assessments for biofuels using Camelina sativa as a model species

Summary 1. Biofuel production has the potential of reducing CO2 emissions while decreasing global dependence on fossil fuels. However, concerns have been raised on the invasiveness of biofuel feedstocks. Estimating invasion potential remains a challenge because of inconsistencies and inherent limitations of using first-tier qualitative weed risk assessment (WRA) protocols singularly. 2. We evaluated the usefulness of second-tier quantitative WRA methods using a recently introduced oilseed crop, Camelina sativa, as a model species. First, we subjected C. sativa to the qualitative Australian WRA and found that it should not be allowed entry. We then used demographic models fit with field-estimated parameters as a second-tier approach to quantitatively evaluate its invasion potential. Data on disturbance (two herbicides, mechanical, none) and seeding season (autumn, spring) relative to C. sativa demography were obtained over 2 years in two rangeland ecosystems in Montana, USA. Population growth (k) was forecast by developing population dynamics models using field data. 3. Emergence rates were greatest when C. sativa was spring-seeded; all survivors to maturity occurred only in mechanically disturbed plots. Population growth rate never exceeded 0AE03, and the maximum time to extinction was 6 years. Perturbation analyses indicated that consistent propagule pressure and biologically improbable rates of seed survival are necessary to sustain C. sativa populations, indicating that the risk of invasion by this species in the studied ecosystems is low. 4. Synthesis and applications. Although more site-years of demographic data would strengthen our conclusions about the invasion potential of C. sativa, we contend that the methods developed provide a useful contribution to WRA. If applied to proposed plant biofuel species, our second-tier quantitative refinements will elucidate important population dynamics often overlooked by qualitative WRAs and, in turn, may reduce the frequency of invasions or rejection of potentially useful species.

[1]  W. Artz,et al.  Camelina oil and its unusual cholesterol content , 2002 .

[2]  C. Ghersa,et al.  Ecology of Weeds and Invasive Plants , 2007 .

[3]  D. O'beirne,et al.  Oxidative Stability of ω3-rich Camelina Oil and Camelina Oil-based Spread Compared with Plant and Fish Oils and Sunflower Spread , 2003 .

[4]  Philip A. Stephens,et al.  Predictive models of weed population dynamics , 2009 .

[5]  D. Simberloff,et al.  Adding Biofuels to the Invasive Species Fire? , 2006, Science.

[6]  A. Davis,et al.  Introduction to the Invasive Plant Species and the New Bioeconomy Symposium , 2008, Weed Science.

[7]  J. Ditomaso,et al.  Nonnative Species and Bioenergy: Are We Cultivating the Next Invader? , 2008 .

[8]  P. Holgate,et al.  Matrix Population Models. , 1990 .

[9]  H. G. Baker,et al.  The Evolution of Weeds , 1974 .

[10]  S. Polasky,et al.  Land Clearing and the Biofuel Carbon Debt , 2008, Science.

[11]  Division on Earth Risk Assessment in the Federal Government: Managing the Process , 1983 .

[12]  Richard N. Mack,et al.  Naturalization of plant populations: the role of cultivation and population size and density , 2010, Oecologia.

[13]  R. Freckleton,et al.  How does temporal variability affect predictions of weed population numbers , 1998 .

[14]  Shahin Ansari,et al.  Guidance for addressing the Australian Weed Risk Assessment questions , 2010 .

[15]  R. Cousens Risk Assessment of Potential Biofuel Species: An Application for Trait-Based Models for Predicting Weediness , 2008, Weed Science.

[16]  W. M. Lonsdale,et al.  Quantifying Uncertainty in Predictions of Invasiveness , 2006, Biological Invasions.

[17]  Ingrid M. Parker,et al.  Evaluating approaches to the conservation of rare and endangered plants , 1994 .

[18]  J. Denslow,et al.  A Risk‐Assessment System for Screening Out Invasive Pest Plants from Hawaii and Other Pacific Islands , 2004 .

[19]  Reuben P Keller,et al.  Risk assessment for invasive species produces net bioeconomic benefits , 2007, Proceedings of the National Academy of Sciences.

[20]  H. Fineberg,et al.  Understanding Risk: Informing Decisions in a Democratic Society , 1996 .

[21]  R. N. Mack Cultivation Fosters Plant Naturalization by Reducing Environmental Stochasticity , 2004, Biological Invasions.

[22]  C. Daehler,et al.  Predicting Invasive Plants: Prospects for a General Screening System Based on Current Regional Models , 2000, Biological Invasions.

[23]  Daphne A. Onderdonk,et al.  Lessons Learned from Testing the Australian Weed Risk Assessment System: The Devil is in the Details , 2010 .

[24]  Eric S. Menges,et al.  Population Viability Analysis for an Endangered Plant , 1990 .

[25]  J. Wiens Spatial Scaling in Ecology , 1989 .

[26]  I. Forseth,et al.  POPULATION MATRIX MODELS OF AESCHYNOMENE VIRGINICA, A RARE ANNUAL PLANT: IMPLICATIONS FOR CONSERVATION , 2005 .

[27]  David A. Mortensen,et al.  Simulation analysis of crop rotation effects on weed seedbanks. , 1995 .

[28]  D. Walker Biofuels – for better or worse? , 2010 .

[29]  I. Parker Invasion dynamics of Cytisus scoparius: a matrix model approach. , 2000 .

[30]  D. Simberloff,et al.  Screening bioenergy feedstock crops to mitigate invasion risk , 2010 .

[31]  Doria R. Gordon,et al.  Consistent accuracy of the Australian weed risk assessment system across varied geographies , 2008 .

[32]  Andrea Sissons,et al.  Evaluation of the Australian weed risk assessment system for the prediction of plant invasiveness in Canada , 2010, Biological Invasions.

[33]  M Rejmánek,et al.  Plant invasions — the role of mutualisms , 2000, Biological reviews of the Cambridge Philosophical Society.

[34]  Mark V. Wilson,et al.  Population Modeling Approach for Evaluating Leafy Spurge (Euphorbia esula) Development and Control , 1988, Weed Technology.

[35]  D. Landis,et al.  Demographic models inform selection of biocontrol agents for garlic mustard (Alliaria petiolata). , 2006, Ecological applications : a publication of the Ecological Society of America.

[36]  C. Buddenhagen,et al.  Assessing Biofuel Crop Invasiveness: A Case Study , 2009, PloS one.

[37]  J. Zubr DIETARY FATTY ACIDS AND AMINO ACIDS OF CAMELINA SATIVA SEED , 2003 .

[38]  Corina Basnou,et al.  Predicting plant invaders in the Mediterranean through a weed risk assessment system , 2010, Biological Invasions.

[39]  Philip M. Dixon,et al.  Are many little hammers effective? Velvetleaf (Abutilon theophrasti) population dynamics in two- and four-year crop rotation systems , 2005, Weed Science.

[40]  Philip Browning. Davis,et al.  The invasion potential and competitive ability of Camelina sativa (L.) Crantz (camelina) in rangeland ecosystems , 2010 .

[41]  N. Ellstrand,et al.  Hybridization as an avenue of escape for engineered genes-strategies for risk reduction , 1990 .