Patterns and drivers of forest plant invasions revealed from FIA data

Transcription

1 Patterns and drivers of forest plant invasions revealed from FIA data Basil Iannone Purdue University Dept. Forestry and Natural Resources Microstegium vimineum Euonymus alata

2 Predicting Regional Invasion Dynamic Processes NSF Macrosystems Biology Grant # Songlin Fei * Bryan C. Pijanowski Gabriela V. Nunez-Mir Teresa Clark Hoa Zhang Andrew M. Liebhold Christopher M. Oswalt Qinfeng Guo Kevin M. Potter

3 Biological invasions = Global change Occur on all continents Many species / taxa Δ composition, functionality, services Affected by global-level processes Increased global commerce more invasions (Ricciardie 2007, Simberloff et al. 2013) national center for ecological analysis and synthesis

4 Macroecological Framework (Brown and Maurer 1989) Across many species / taxa Across large geographic areas Detect unifying patterns Broad mechanistic understanding Limit bias caused by investigating: - Too few species - Too small of spatial scale (Hulme et al. 2013) Small-scale studies cannot provide large-scale insights (Araújo & Rozenfeld, 2014)

5 Microstegium vimineum Euonymus alata Acer platanoides Lonicera maackii

6 Outline Introduce FIA Program / Invasion Plant Data Illustrate utility - Summarize invasions in MIPN region - Three regional investigations Overall invasion patterns (USA) Invasion drivers Biotic resistance to invasion Effects of species traits

7 Forest Inventory and Analysis Program USDA --- U.S. Forest Service Monitoring forest conditions over time --- Private and Public Forests: Area 37m wide, 0.40 ha in size, Tree cover 10% (currently or historically) Not slated for non-forest use

8 Forest Inventory and Analysis Program thousand permanent 0.40-ha plots (1 plot / 2,428 ha) 5 and 10-yr sampling rotations in East and West Used most recent data for a given plot

9 Icosahedroning the Sphere & Honeycombing the Icosahedron 1 (McCollum 2001)

10 Phases of data collection Phase 1: Area Estimation - NLCD - Forest / Nonforest Phase 2: Forest Mensuration - Tree measurements - Ancillary Data (Including regional variables) - Invasive Plants Phase 3: Forest Health Monitoring - Soils, Fuels, Disease, Ozone, Lichens - Vegetation Structure and Diversity (limited implementation)

11 Monitoring Plant Invasions --- FIA Plots FIA Regions

12 Monitoring Plant Invasions --- FIA Plots Invasive species: US Executive Order Invasive Species an alien [plant] species whose introduction does or is likely to cause economic or environmental harm or harm to human health (Ries et al. 2004) FIA Regions

13 Monitoring Plant Invasions --- FIA Plots Region-specific watch list --- State-specific in IMW ~ 40 species monitored in NE Lists expand over time Overlap in watch list --- cross-region invasions FIA Regions

14 Some limitations Excludes urban forests (beginning) Not useful for detecting new invaders - But expansion of existing invaders Underestimates invasion Limited to forest invasions FIA Regions

15 Midwest Invasions --- Summary

16 Midwest Invasions --- Summary 51% of plots invaded 32 invaders detected

17 Midwest Invasions --- Summary 51% of plots invaded 32 invaders detected 5 most common invaders Invader % plots Rosa spp. 26 Lonicera spp. 17 Phalaris arundinacea 12 Alliaria petiolata 7 Rhamnus cathartica 7

18 % of FIA Plots Invaded by State

19 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica Rosa spp. Lonicera japonica Lonicera spp.

20 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica Rosa spp. Lonicera japonica Lonicera spp.

21 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica Rosa spp. Lonicera japonica Lonicera spp.

22 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica Rosa spp. Lonicera japonica Lonicera spp.

23 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica (38%) Rosa spp. Lonicera japonica Lonicera spp.

24 3 Most Common Invaders by State Phalaris arundinacea Lonicera spp. Rhamnus cathartica Rosa spp. Phalaris arundinacea Lonicera spp. Cirsium arvense Lonicera spp. Rosa spp. Rosa spp. Lonicera spp. Lonicera japonica Rosa spp. Lonicera japonica Lonicera spp.

25

26 OBJECTIVE 1: Spatial Patterns Mapped 2 Invasion measures 2,524 counties Invasion richness --- # invasive species Invasion prevalence --- % FIA plots invaded Establishment vs. Commonness

27 OBJECTIVE 2: Identify drivers Inv ~ 5 Invasion pressure + 17 Habitat invasibility (Liebhold et al., 2013) Eastern and Western U.S.A. - Isolated & Ecologically distinct - Distinct ownership --- Public vs. Private - County sizes differ West = 7400 vs. East = 1600 km 2

28 Patterns: East more invaded than west East West Inv Rich 6.1 ± ± 0.2 % 3 Sp 81% 45% Inv Prev 48 ± 1% 10 ± 1% % 50% Prev 48% 2% Still low-invasion areas

29 Understanding requires multiple measures

30 Understanding requires multiple measures Ag Midwest: Few common invaders Lonicera maackii

31 Understanding requires multiple measures Species-rich west: Prone to future high prevalence / dominance (Williamson & Fitter 1996)

32 Inv. Invasion Drivers: Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Pop to 0.4 Prop. pressure Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom NatSpRich PSV Elev PropFor

33 Inv. Invasion Drivers: Inv. press. and Hab. inv. contribute to invasions Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Pop to 0.4 Prop. pressure Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom NatSpRich PSV Elev PropFor

34 Inv. Invasion pressure increases establishment and commonness (Lockwood et al, 2005) Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Pop to 0.4 Prop. pressure Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom NatSpRich PSV Elev PropFor

35 Inv. Habitat invasibility: varying effects on establishment and commonness Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Pop to 0.4 Prop. pressure Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom NatSpRich PSV Elev PropFor

36 Spatial variability in policy Invasion pressure less influential in East than West - Fewer terms and weaker associations throughout west vs. targeted areas in east

37 Spatial variability in policy East: limit input and movement in targeted areas West: limit input and movement regionally

38 Inv. Spatial variability in policy Human disturbance --- National policies Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Prop. pressure Pop to 0.4 Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom NatSpRich PSV Elev PropFor

39 Inv. Spatial variability in policy Human disturbance --- National policies Biotic resistance --- Localized policies Eastern U.S. Western U.S. Pseudo RelativeR slopes 2 value Inv.R Inv.Prev Inv.R Inv.Prev > 0.4 Pop to 0.4 Prop. pressure Pop to 0.3 YrUnion 0.1 to 0.2 DistPort >0 to 0.1 HumFrag NA NatFrag <0 to -0.1 Habitat invasibility Temp -0.1 to -0.2 Area Precip NatBiom 0.16 NatSpRich PSV Elev PropFor

40 Summary: Understanding requires multiple invasion metrics e.g. Few dominant invaders in Ag. Midwest Invasion ~ Invasion pressure + Habitat Invasibility Habitat invasibility affects establishment and commonness differently Invasion pressure more influential in West than East Need for spatial variability in management and policy

41 Cedar Creek LTER Tilman 2000

42 Biotic Resistance Hypothesis More diverse communities are less invaded --- fewer open niches (Elton 1958; Levine and D'Antonio 1999) Support is low % of 129 studies (Jeschke et al. 2012) Cedar Creek LTER Tilman 2000

43 Biotic Resistance Hypothesis Invasion paradox --- findings are scale-dependent Shea & Chesson 2002

44 Biotic Resistance Hypothesis --- Improving Tests 42,626 FIA plots Multiple invasion measures: Inv. richness --- establishment Inv. cover --- dominance Biotic resistance (Native trees) Species richness Aboveground biomass Phylogenetic species variability Phylogenetic species clustering (Helmus 2007) Trees = most biomass / productivity = resource uptake = biotic resistance (Davis et al. 2000)

45 Inv. Cover Data analysis: Alternative approach needed Invasion ~ Biomass + Sp. Richness + PSV + PSC N = 42,626 = Too much statistical power! Statistically significance vs. ecologically importance (Anderson et al. 2000; Spanos 2014) R 2 = 0.04 P < Biomass

46 Mixed-effects model --- New approach Invasion ~ Biomass + Sp. Richness + PSV + PSC Slope estimates for each nested sub-region (random effects) Effects of Scale and Location 5 Ecological divisions 91 Ecological sections Cleland et al 2007

47 Indicators of biotic resistance Bootstrapped section-level slope estimates (10,000 x) 95% CIs Indicators: Biom, PSV, PSC PSC strongest Sp Richness indicator Increasing Biomass or evolutionary diversity may limit invasion

48 Spatial context Inv. Richness

49 Cross-scale variation in associations Inv. Richness

50 Cross-scale variation in associations Inv. Richness

51 Cross-scale variation in associations Inv. Richness

52 Spatial aggregation of biotic resistance Inv. Richness

53 Differences between invasion measures Inv. Cover

54 Differences between invasion measures Evolutionary diversity limits dominance more than establishment Inv. Cover Inv. Richness

55 Summary: Evidence of biotic resistance at large geographic scales Evolutionary diversity and Biomass limit invasion Species richness does not Associations vary with scale and location Aggregation of strong effects: - Appalachians - Midwest (Evolutionary diversity / PSC) Evolutionary diversity limits dominance more than establishment Mechanisms? How to better manage tree diversity to limit future invasions

56 Invasion ~ Socioeconomic and Ecological Drivers Community Characteristics Invader Traits (Catsford et al. 2009)

57 Invasion ~ Socioeconomic and Ecological Drivers Community Characteristics Invader Traits (Catsford et al. 2009) AIM: Contribution of species traits to macroscale invasion patterns

58 Methods: Divided forests into 7,904 hexagons (40-km 2 ) Determined: Invasive species richness Species richness for five plant growth forms: Forbs, Grasses, Shrubs, Trees, Vines

59 Methods: Invasion Hotspots --- Getis-Ord Gi* statistic Detects groups of hexagons having values higher than expected based on random chance relative to the overall mean Separate analyses for East and West

60 Methods: Mapped hotspots: Species richness and Growth forms Estimated overlap East-West comparison

61 Hotspots: Spanned 9 to 23% of USA forests Forests are highly invaded

62 Hotspots are trait specific % Non overlap = 20 to 59% Overlooked had traits not been considered

63 Hotspots: Invasive species richness Not a lot in MIPN states Species richness

64 Hotspots: Invasive forbs species Alliaria petiolata Cirsium arvense Cirsium vulgare Lysimachia nummularia Centaurea stoebe Hesperis matronalis Euphorbia esula Polygonum cuspidatum Polygonum sachalinense Lythrum salicaria garlic mustard Canada thistle bull thistle creeping jenny spotted knapweed dames rocket leafy spurge Japanese knotweed giant knotweed purple loosestrife

65 Hotspots: Invasive shrubs species Rosa sp Lonicera sp. Rhamnus cathartica Elaeagnus umbellata Frangula alnus Berberis thunbergii Ligustrum sinense & vulgare non-native rose bush honeysuckles common buckthorn autumn olive glossy buckthorn Japanese barberry Common and Chinese Privet Berberis vulgaris Common barberry Elaeagnus angustifolia Russian olive Viburnum opulus European cranberrybush Spiraea japonica Japanese meadowsweet

66 Hotspots: Invasive grasses species Phalaris arundinacea Microstegium vimineum Phragmites australis reed canarygrass Nepalese browntop common reed

67 Hotspots: Invasive trees and vines and 3 species Robinia pseudoacacia Ailanthus altissima Ulmus pumila black locust tree of heaven Siberian elm Lonicera japonica Celastrus orbiculatus Hedera helix Japanese honeysuckle Oriental bittersweet English ivy Acer platanoides Albizia julibrissin Norway maple Silktree/ mimosa

68 East-West Comparisons Spatial extent is similar to 23% of surveyed forests

69 East-West Comparisons Species richness greater in East than West 3.10 ± ± 0.07

70 East-West Comparisons Not consistent across all growth forms 2.33 ± ± ± ± 0.02

71 East-West Comparisons Not consistent across all growth forms Suggests drivers vary among growth forms 2.33 ± ± ± ± 0.02

72 East-West Comparisons: More shrubs, trees, and vines Species Richness Shrub Trees* Vines* 3.17 ± ± ± ± ± ± 0.00

73 Summary: A lot of forests are highly invaded - Dealing with multiple invaders Hotspots are trait specific - Midwest: Shrubs, Forbs, and Grasses Only looked at hotspots of establishment Hotspots of dominance/cover?

74 Overall Conclusions: FIA Program --- Invasive plant dataset Utility for understanding invasion: - Identify key invaders / distributions / movement - Detect regional variability in drivers --- Policy - Biotic resistance ~ Evolutionary diversity and Biomass How to manage diversity? - Invasion hotspots/vulnerable areas are trait-specific

75 Questions? Microstegium vimineum Euonymus alata Acer platanoides Lonicera maackii

76 References Araújo MB, Rozenfeld A (2014) The geographic scaling of biotic interactions. Ecography 37(5): Anderson DR, Burnham KP, Thompson WL (2000) Null hypothesis testing: problems, prevalence, and an alternative. The Journal of Wildlife Management 64(4): Brown, J.H. (1999) Macroecology: progress and prospect. Oikos, 87, Catford JA, Vesk PA, Richardson DM, Pyšek P (2012) Quantifying levels of biological invasion: towards the objective classification of invaded and invasible ecosystems. Global Change Biol. 18(1): Cleland DT, Freeouf JA, Keys JE, Nowacki GJ, Carpenter CA, McNab WH (2007) Ecological Subregions: Sections and Subsections for the conterminous United States. General Technical. Report WO-76. U.S. Department of Agriculture, Forest Service, Washington, DC. Map, presentation scale 1:3,500,000; Albers equal area projection; colored. Davis MA, Grime JP, Thompson K (2000) Fluctuating resources in plant communities: a general theory of invasibility. J. Ecol. 88(3): Elton CS (1958) The Ecology of Invasions by Animals and Plants. Methuen, London Helmus MR, Bland TJ, Williams CK, Ives AR (2007) Phylogenetic measures of biodiversity. The American Naturalist 169(3):E68-E83 Hulme PE (2009) Trade, transport and trouble: managing invasive species pathways in an era of globalization. J. Appl. Ecol. 46(1): Iannone, B. V., III, C. M. Oswalt, A. M. Liebhold, Q. Guo, K. M. Potter, G. C. Nunez-Mir, O. S.N., B. C. Pijanowski, and S. Fei Region-specific patterns and drivers of macroscale forest plant invasions Diversity and Distributions. 21: Iannone, B. V., III, K. M. Potter, K. Dixon Hamil, W. Huang, H. Zhang, Q. Guo, C. M. Oswalt, C. W. Woodall, and S. Fei. In press. Evidence of biotic resistance to invasions in forests of the Eastern USA. Landscape Ecology. Iannone, B. V., III, K. M. Potter, Q. Guo, A. M. Liebhold, B. C. Pijanowski, C. M. Oswalt, and S. Fei. In press. Biological invasion hotspots: a trait-based perspective reveals new sub-continental patterns. Ecography DOI: /ecog Jeschke JM, Gómez Aparicio L, Haider S, Heger T, Lortie CJ, Pyšek P, Strayer DL (2012) Support for major hypotheses in invasion biology is uneven and declining. NeoBiota(14):1-20

77 References Liebhold, A. M., D. G. McCullough, L. M. Blackburn, S. J. Frankel, B. Von Holle, and J. E. Aukema A highly aggregated geographical distribution of forest pest invasions in the USA. Diversity and Distributions 19: Levine JM, D'Antonio CM (1999) Elton revisited: a review of evidence linking diversity and invasibility. Oikos 87(1):15-26 Lockwood, J. L., P. Cassey, and T. Blackburn The role of propagule pressure in explaining species invasions. Trends in Ecology & Evolution 20: Martin, P. H. et al Why forests appear resistant to exotic plant invasions: intentional introductions, stand dynamics, and the role of shade tolerance. Front. Ecol. Environ. 7: McCollum, Joseph M Honeycombing The Icosahedron and Icosahedroning the Sphere In: Reams, Gregory A.; McRoberts, Ronald E.; Van Deusen, Paul C., eds Proceedings of the second annual Forest Inventory and Analysis symposium; 2000 October 17-18; Salt Lake City, UT. Gen. Tech. Rep. SRS-47. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp Oswalt, C. et al A subcontinental view of forest plant invasions using national inventory data. NeoBiota 24: Ricciardi, A Are modern biological invasions an unprecedented form of global change? Conserv. Biol. 21: Ries P., Dix M.E., Lelmini M. & Thomas D. (2004). National Strategy and Implementation Plan for Invasive Species Management. FS-805. U.S. Department of Agriculture, Forest Service, Washington, DC. Shea, K. and Chesson, P Community ecology theory as a framework for biological invasions. Trends Ecol. Evol. 17: Simberloff, D. et al Impacts of biological invasions: what's what and the way forward. Trends Ecol. Evol. 28: Spanos A (2014) Recurring controversies about P values and confidence intervals revisited. Ecology 95(3): Tilman D (2000) Causes, consequences and ethics of biodiversity. Nature 405: Williamson, M. and A. Fitter The varying success of invaders. Ecology 77:

78 Evolutionary diversity metrics Calculated from Phylogenetic supertree 397 native tree species Phylogenetic species variability (PSV; 0-1) (Helmus 2007) Phylogenetic species clustering (PSC; 0-1) Lower Higher Juglans cinerea Juglans hindsii Juglans nigra Juglans major Carya aquatica Carya illinoinensis Carya cordiformis Carya laciniosa Carya ovata Carya carolinae Carya myristiciformis Carya pallida Carya texana Carya alba Carya ovalis Carya glabra Juglans cinerea Juglans hindsii Juglans nigra Juglans major Carya aquatica Carya illinoinensis Carya cordiformis Carya laciniosa Carya ovata Carya carolinae Carya myristiciformis Carya pallida Carya texana Carya alba Carya ovalis Carya glabra

79

80