Different environmental drivers of alien tree invasion affect different life-stages and operate at different spatial scales

FOREST ECOLOGY AND MANAGEMENT

卷:433

Article

Vicente, Joana R.^1,2,3  Kueffer, Christoph^4,5  Richardson, David M.⁵  Vaz, Ana Sofia^1,2  Cabral, Joao A.³  Hui, Cang^6,7  Araujo, Miguel B.^8,9,10  Kuehn, Ingolf^11,12,13  Kull, Christian A.¹⁴  Verburg, Peter H.^15,16  Marchante, Elizabete¹⁷  Honrado, Joao P.^1,2 

[1] Univ Porto, CIBIO Ctr Invest Biodiversidade & Recursos Genet, InBIO Rede Invest Biodiversidade & Biol Evolut, P-4485601 Vairao, Portugal

[2] Univ Porto, Fac Ciencias, Porto, Portugal

[3] Univ Tras Os Montes & Alto Douro, Ctr Res & Technol Agroenvironm & Biol Sci, Lab Appl Ecol, Vila Real, Portugal

[4] Swiss Fed Inst Technol, Inst Integrat Biol, Univ Str 16, CH-8092 Zurich, Switzerland

[5] Stellenbosch Univ, Dept Bot & Zool, Ctr Invas Biol, ZA-7602 Matieland, South Africa

[6] Stellenbosch Univ, Dept Math Sci, Ctr Invas Biol, ZA-7602 Matieland, South Africa

[7] African Inst Math Sci, Theoret Ecol Grp, ZA-7945 Cape Town, South Africa

[8] CSIC, Museo Nacl Ciencias Nat, Calle Jose Gutierrez Abascal 2, Madrid 28006, Spain

[9] Univ Evora, Ctr Invest Biodiversidade & Recursos Genet CIBIO, P-7000890 Evora, Portugal

[10] Univ Copenhagen, Nat Hist Museum Denmark, Ctr Macroecol Evolut & Climate, DK-2100 Copenhagen, Denmark

[11] UFZ Helmholtz Ctr Environm Res, Dept Community Ecol, Theodor Lieser Str 4, D-06120 Halle, Germany

[12] Martin Luther Univ Halle Wittenberg, Geobot & Bot Garden, Kirchtor 1, D-06108 Halle, Germany

[13] Deutsch Zentrum Integrat Biodiversitatsforsch iDi, Deutsch Pl 5e, D-04103 Leipzig, Germany

[14] Univ Lausanne, Inst Geog & Sustrzinabil, CH-1015 Lausanne, Switzerland

[15] Vrije Univ Amsterdam, Fac Earth & Life Sci, Environm Geog Grp, de Boelelaan 1087, NL-1081 HV Amsterdam, Netherlands

[16] Swiss Fed Inst Forest Snow & Landscape Res WSL, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland

[17] Univ Coimbra, Ctr Funct Ecol, P-3000456 Coimbra, Portugal

关键词: Acacia dealbata;    Biological invasions;    Environmental factors;    Multimodel inference;    Scale-dependence;   

DOI  :  10.1016/j.foreco.2018.10.065

来源: Elsevier

【 摘 要 】

Identifying the key factors driving invasion processes is crucial for designing and implementing appropriate management strategies. In fact, the importance of (model-based) prevention and early detection was highlighted in the recent European Union regulation on Invasive Alien Species. Models based on abundance estimates for different age/size classes would represent a significant improvement relative to the more usual models based only on species' occurrence data. Here, we evaluate the relative contribution of different environmental drivers to the spatial patterns of abundance of several height classes (or life-stages) of invasive tree populations at the regional scale, using a data-driven hierarchical modelling approach. A framework for modelling life-stages to obtain spatial projections of their potential occurrence or abundance has not been formalized before. We used Acacia dealbata (Silver-wattle) as a test species in northwest of Portugal, a heavily invaded region, and applied a multimodel inference to test the importance of various environmental drivers in explaining the abundance patterns of five plant height classes in local landscape mosaics. The ensemble of height classes is considered here as a proxy for population dynamics, life-stages and age of adult trees. In this test with A. dealbata, we used detailed field data on population height structure and calibrated an independent model for each height class. We found evidence to support our hypothesis that the distribution of height classes is mostly influenced by distinct factors operating at different scales. The spatial projections which resulted from several height class models provide an overview of population structure and invasion dynamics considering various life-stages, that is widely used in biodiversity and invasion research. The approach proposed here provides a framework to guide forest management to deal more effectively with plant invasions. It allows to test the effects of key invasion factors (depending on the focal species and on data availability) and supports the spatial identification of suitable areas for invasive species' occurrence while also accounting for the structural complexity of invasive species populations, thereby anticipating future invasion dynamics. The approach thus constitutes a step forward for establishing management actions at appropriate spatial scales and for focusing on earlier stages of invasion and their respective driving factors (regeneration niche), thereby enhancing the efficiency of control actions on major forest invaders.

【 授权许可】

Free