Biological invasions are one of the leading causes of global environmental change and their impacts can affect biodiversity, ecosystem services, human health and the economy. Yet, the understanding on the impacts of invasive alien species is still limited and mostly related to alien species outbreaks and losses in agricultural yield, followed by the understanding of the ecological impacts on natural systems. Notably, the economic impacts of biological invasions have rarely been quantified. Brazil has at least 1214 known alien species from which 460 are recognized as invasive alien species. Still, there are no comprehensive estimates of the cost of their impact and management. Here, we aimed at filling this gap by providing a comprehensive estimate of the economic cost of biological invasions in Brazil. In order to quantify these costs for species, ecosystems and human well-being we used the InvaCost database which is the first global compilation of the economic costs of biological invasions. We found that Brazil reportedly spent a minimum of USD 105.53 billions over 35 years (1984–2019), with an average spent of USD 3.02 (± 9.8) billions per year. Furthermore, USD 104.33 billion were due to damages and losses caused by invaders, whereas only USD 1.19 billion were invested in their management (prevention, control or eradication). We also found that recorded costs were unevenly distributed across ecosystems, and socio-economic sectors, and were rarely evaluated and published. We found that the economic costs with losses and damages were substantially greater than those used for prevention, control or eradication of IAS. Since our data show costs reported in Brazil for only 16 invasive alien species, our estimates are likely a conservative minimum of the actual economic costs of biological invasions in Brazil. Taken together, they indicate that invasive alien species are an important cause of economic losses and that Brazil has mostly opted for paying for the damage incurred by biological invasions rather than investing in preventing them from happening.
Restoration practices are designed to reverse the negative effects of human activities on the environment, allowing the recovery of biodiversity and ecosystem functions. However, restoration activities require monitoring the recolonization of faunal assemblages to assess whether ecosystem functions and services performed by them have been recovered. Because of the presumed link between species traits and ecosystem functioning, a potential solution to evaluate restoration efficiency is the grouping of species based on their ecological functions. Here, we review studies on bird assemblages of active restoration sites in Brazil and apply a data-driven approach to group bird species into functional groups using species trait information. We reviewed if studies provided detailed information (e.g., data on species composition and abundance) for comparative analyses and evaluated how restoration time (i.e., how long-ago restoration started) affected the similarity in bird species composition considering three restoration age classes: recent, intermediate, and old. We also tested whether the composition of bird functional groups varies in restoration sites of different age classes. Although we found a small number of studies (n = 8) with birds in restoration areas, we compiled a dataset consisting of 232 bird species from 14 different restoration sites. We found that bird assemblages from recent restoration sites (up to 5 years) were dissimilar to bird assemblages from older restoration sites (over 20 years). Also, older restoration sites had a higher occurrence of more specialist functional groups (e.g., small frugivores birds of superior stratum). Despite the small number of studies, our results reinforce the sensitivity of birds to habitat changes and their potential in indicating restoration efficiency. We argue for the necessity of standardized protocols in the collection and reporting of data on restoration activities, which will improve comparative analysis in theoretical and applied restoration ecology.
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