title: Predicting trends of invasive plants richness using local socio-economic data: an application in North Portugal.
abstract: This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasing populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology.
authors.affiliation: University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. mgsantoss@gmail.com
authors.forename: Mário
authors.initials: M
authors.lastname: Santos
authors.forename: Raul
authors.initials: R
authors.lastname: Freitas
authors.forename: António L
authors.initials: AL
authors.lastname: Crespí
authors.forename: Samantha Jane
authors.initials: SJ
authors.lastname: Hughes
authors.forename: João Alexandre
authors.initials: JA
authors.lastname: Cabral
mesh_terms: D044822:Biodiversity; D017753:Ecosystem; D006802:Human Activities; D058865:Introduced Species / Q000639:trends*; D008954:Models, Biological; D015233:Models, Statistical; D010944:Plants; D011174:Portugal; D012959:Socioeconomic Factors; D014507:Urbanization