Western flower thrips,
Frankliniella occidentalis
, first arose as an important invasive pest of many crops during the 1970s-1980s. The tremendous growth in international agricultural trade that ...developed then fostered the invasiveness of western flower thrips. We examine current knowledge regarding the biology of western flower thrips, with an emphasis on characteristics that contribute to its invasiveness and pest status. Efforts to control this pest and the tospoviruses that it vectors with intensive insecticide applications have been unsuccessful and have created significant problems because of the development of resistance to numerous insecticides and associated outbreaks of secondary pests. We synthesize information on effective integrated management approaches for western flower thrips that have developed through research on its biology, behavior, and ecology. We further highlight emerging topics regarding the species status of western flower thrips, as well as its genetics, biology, and ecology that facilitate its use as a model study organism and will guide development of appropriate management practices.
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•The accuracy of species distribution models is influenced by physiological tolerance data.•The red-eared slider, as a typical invasive alien species, is widespread in China.•The ...embryo temperature tolerance range of the red-eared slider was between 21.8 °C and 33.1 °C.•Red-eared slider’s high suitability areas mainly in south and central. The suitability areas predicted by the SDMs reduced 20% when considering embryo temperature tolerance data of red-eared slider.•The high suitability areas for red-eared sliders are mainly concentrated in South China, Central China, and East China.
Species distribution models (SDMs) have been widely used to predict potentially suitable habitats for invasive alien species (IAS) and evaluate invasion risk. However, SDMs have been discredited because they ignore the physiological processes by which species respond to their environment. Integrating physiological tolerance into the model is essential to improve the prediction accuracy of SDMs. Currently, this approach has not been applied in the study of the worldwide invasive species, the red-eared slider (Trachemys scripta elegans), which is one of the world’s 100 worst invasive species and is widespread in China. In this study, based on hatching experiments, we found that the embryo temperature tolerance range of the red-eared slider was between 21.8 °C and 33.1 °C. Further, we studied the effect of embryo temperature tolerance on the prediction of potential invasion areas for this alien reptile species. The high suitability area (530,214.71 km2) predicted by the SDM incorporating embryo temperature tolerance data were 20.9% smaller than that (641,107.60 km2) predicted by the SDM without considering embryo temperature tolerance. The difference between the two SDMs is primarily concentrated at the edges of the high suitability areas. The incorporation of embryo temperature tolerance data influenced the model's predictions by effectively reducing the extent of edges of the high suitability areas. High suitability areas for red-eared sliders are mainly concentrated in South China, Central China, and East China, with a few in North and Southwest China. There is almost no invasion risk in most of the northeast and northwest provinces of China. This study not only has theoretical significance for optimizing model predictions, but also provides an important scientific basis for prevention and risk assessment of invasion by red-eared sliders in China.
The United States has thousands of invasive species, representing a sizable, but unknown burden to the national economy. Given the potential economic repercussions of invasive species, quantifying ...these costs is of paramount importance both for national economies and invasion management. Here, we used a novel global database of invasion costs (InvaCost) to quantify the overall costs of invasive species in the United States across spatiotemporal, taxonomic, and socioeconomic scales. From 1960 to 2020, reported invasion costs totaled $4.52 trillion (USD 2017). Considering only observed, highly reliable costs, this total cost reached $1.22 trillion with an average annual cost of $19.94 billion/year. These costs increased from $2.00 billion annually between 1960 and 1969 to $21.08 billion annually between 2010 and 2020. Most costs (73%) were related to resource damages and losses ($896.22 billion), as opposed to management expenditures ($46.54 billion). Moreover, the majority of costs were reported from invaders from terrestrial habitats ($643.51 billion, 53%) and agriculture was the most impacted sector ($509.55 billion). From a taxonomic perspective, mammals ($234.71 billion) and insects ($126.42 billion) were the taxonomic groups responsible for the greatest costs. Considering the apparent rising costs of invasions, coupled with increasing numbers of invasive species and the current lack of cost information for most known invaders, our findings provide critical information for policymakers and managers.
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•From 1960 to 2020 reported costs of US biological invasions were at least $1.22 tril.•Annual invasion costs increased from $2 bil in 1960–69 to $21 bil in 2010–20.•Most costs were damages ($896 bil), with lower management investments ($47 bil).•Agriculture sector ($510 bil) and terrestrial habitat ($644 bil) were impacted most.•Knowledge gaps in reporting make these monetary costs severely underestimated.
Biological invasions are a global threat to biodiversity. Since the spread of invasive alien plants may have many impacts, an integrated approach, assessing effects across various ecosystem ...components, is needed for a correct understanding of the invasion process and its consequences. The nitrogen-fixing tree Robinia pseudoacacia (black locust) is a major invasive species worldwide and is used in forestry production. While its effects on plant communities and soils are well known, there have been few studies on soil fauna and microbes.
We investigated the impacts of the tree on several ecosystem components, using a multi-trophic approach to combine evidence of soil chemical properties and soil microbial, nematode, microarthropod and plant communities. We sampled soil and vegetation in managed forests, comparing those dominated by black locust with native deciduous oak stands.
We found qualitative and quantitative changes in all components analysed, such as the well-known soil nitrification and acidification in stands invaded by black locust. Bacterial richness was the only component favoured by the invasion. On the contrary, abundance and richness of microarthropods, richness of nematodes, and richness and diversity of plant communities decreased significantly in invaded stands. The invasion process caused a compositional shift in all studied biotic communities and in relationships between the different ecosystem components.
We obtained clear insights into the effects of invasion of managed native forests by black locust. Our data confirms that the alien species transforms several ecosystem components, modifying the plant-soil community and affecting biodiversity at different levels. Correct management of this aggressive invader in temperate forests is urgently required.
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•We analysed the impacts of Robinia pseudoacacia invasion.•We analysed impacts on soil chemical properties, plant and soil biotic communities.•We found qualitative and quantitative changes in all components analysed.•We detected soil nitrification and acidification in stands invaded by black locust.•Changes (mostly biodiversity reduction) were observed in biotic communities.
Addressing context dependence in ecology Catford, Jane A.; Wilson, John R.U.; Pyšek, Petr ...
Trends in ecology & evolution (Amsterdam),
February 2022, 2022-02-00, 20220201, Letnik:
37, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Context dependence is widely invoked to explain disparate results in ecology. It arises when the magnitude or sign of a relationship varies due to the conditions under which it is observed. Such ...variation, especially when unexplained, can lead to spurious or seemingly contradictory conclusions, which can limit understanding and our ability to transfer findings across studies, space, and time. Using examples from biological invasions, we identify two types of context dependence resulting from four sources: mechanistic context dependence arises from interaction effects; and apparent context dependence can arise from the presence of confounding factors, problems of statistical inference, and methodological differences among studies. Addressing context dependence is a critical challenge in ecology, essential for increased understanding and prediction.
‘Context dependence’ is widely used to describe disparate results in ecology, but the term is poorly defined and inconsistently used.Context dependence arises when ecological relationships vary in magnitude or sign, depending on the conditions under which they are observed.Context dependence can result from multiple factors and processes, so, unless the underlying causes are identified, concluding that relationships are context dependent provides limited understanding.We distinguish between apparent and mechanistic context dependence, with the former an artefact of study design and approach and the latter reflecting ecological interaction effects.Recognising and addressing the different sources of context dependence should facilitate increased understanding, prediction, and generalisation in ecology.
The global increase in biological invasions is placing growing pressure on the management of ecological and economic systems. However, the effectiveness of current management expenditure is difficult ...to assess due to a lack of standardised measurement across spatial, taxonomic and temporal scales. Furthermore, there is no quantification of the spending difference between pre-invasion (e.g. prevention) and post-invasion (e.g. control) stages, although preventative measures are considered to be the most cost-effective. Here, we use a comprehensive database of invasive alien species economic costs (InvaCost) to synthesise and model the global management costs of biological invasions, in order to provide a better understanding of the stage at which these expenditures occur. Since 1960, reported management expenditures have totalled at least US$95.3 billion (in 2017 values), considering only highly reliable and actually observed costs — 12-times less than damage costs from invasions ($1130.6 billion). Pre-invasion management spending ($2.8 billion) was over 25-times lower than post-invasion expenditure ($72.7 billion). Management costs were heavily geographically skewed towards North America (54%) and Oceania (30%). The largest shares of expenditures were directed towards invasive alien invertebrates in terrestrial environments. Spending on invasive alien species management has grown by two orders of magnitude since 1960, reaching an estimated $4.2 billion per year globally (in 2017 values) in the 2010s, but remains 1–2 orders of magnitude lower than damages. National management spending increased with incurred damage costs, with management actions delayed on average by 11 years globally following damage reporting. These management delays on the global level have caused an additional invasion cost of approximately $1.2 trillion, compared to scenarios with immediate management. Our results indicate insufficient management — particularly pre-invasion — and urge better investment to prevent future invasions and to control established alien species. Recommendations to improve reported management cost comprehensiveness, resolution and terminology are also made.
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•Since 1960, management for biological invasions totalled at least $95.3 billion.•Damage costs from invasions were substantially higher ($1130.6 billion).•Pre-invasion management spending is 25-times lower than post-invasion.•Management and damage costs are increasing rapidly over time.•Proactive management substantially reduces future costs at the trillion-$ scale.
The Mediterranean Sea provides fertile ground for understanding the complex interplay between invasive species and native habitats, particularly within the context of climate change. This thermal ...tolerance study reveals the remarkable ability of Lophocladia trichoclados, a red algae species that has proven highly invasive, to adapt to varying temperatures, particularly thriving in colder Mediterranean waters, where it can withstand temperatures as low as 14 °C, a trait not observed in its native habitat. This rapid acclimation, occurring in less than a century, might entail a trade-off with high temperature resistance. Additionally, all sampled populations in the Mediterranean share the same haplotype, suggesting a common origin and the possibility that we might be facing an exceptionally acclimatable and invasive strain. This high degree of acclimatability could determine the future spread capacity in a changing scenario, highlighting the importance of considering both acclimation and adaptation in understanding the expansion of invasive species' ranges.
•Lophocladia trichoclados could pose a significant threat to ecosystems.•L. trichoclados exhibits remarkable acclimation flexibility to temperature fluctuations.•Different populations reveal variations in growth rates and adaptation strategies.•Haplotypes may suggest a potential link between specific strains and thermal tolerance.
Crypticity in Biological Invasions Jarić, Ivan; Heger, Tina; Castro Monzon, Federico ...
Trends in ecology & evolution (Amsterdam),
April 2019, 2019-Apr, 2019-04-00, 20190401, Letnik:
34, Številka:
4
Journal Article
Recenzirano
Ecological effects of alien species can be dramatic, but management and prevention of negative impacts are often hindered by crypticity of the species or their ecological functions. Ecological ...functions can change dramatically over time, or manifest after long periods of an innocuous presence. Such cryptic processes may lead to an underestimation of long-term impacts and constrain management effectiveness. Here, we present a conceptual framework of crypticity in biological invasions. We identify the underlying mechanisms, provide evidence of their importance, and illustrate this phenomenon with case studies. This framework has potential to improve the recognition of the full risks and impacts of invasive species.
Crypticity of biological invasions may blur invasion impacts and reduce their predictability.
The impacts are often only detected in retrospect, and understood with delay, long after control measures would have been effective.
Crypticity of biological invasions can be driven by inherent crypticity of alien species and their ecological functions and by time lags, spatio-temporal variability, and anthropogenic impacts.
Considering crypticity in biological invasions would strongly enhance efficiency of monitoring and management planning.
1. Predictions of the identities and ecological impacts of invasive alien species are critical for risk assessment, but presently we lack universal and standardized metrics that reliably predict the ...likelihood and degree of impact of such invaders (i.e. measurable changes in populations of affected species). This need is especially pressing for emerging and potential future invaders that have no invasion history. Such a metric would also ideally apply across diverse taxonomic and trophic groups. 2. We derive a new metric of invader ecological impact that blends: (i) the classic Functional Response (FR; consumer per capita effect) and Numerical Response (NR; consumer population response) approaches to determining consumer impact, that is, the Total Response (TR = FR × NR), with; (ii) the Tarker-Lonsdale equation' for invader impact, where Impact = Range × Abundance × Effect (per capita effect), into; (iii) a new metric, Relative Impact Potential (RIP), where RIP = FR × Abundance. The RIP metric is an invader/native ratio, where values > 1 predict that invader ecological impact will occur, and increasing values above 1 indicate increasing impact. In addition, the invader/invader RIP ratio allows comparisons of the ecological impacts of different invaders. 3. Across a diverse range of trophic and taxonomic groups, including predators, herbivores, animals and plants (22 invader/native systems with 47 individual comparisons), high-impact invaders were significantly associated with higher FRs compared to native trophic analogues. However, the RIP metric substantially improves this association, with 100% predictive power of high-impact invaders. 4. Further, RIP scores were significantly and positively correlated with two independent ecological impact scores for invaders, allowing prediction of the degree of impact of invasive alien species with the RIP metric. Finally, invader/invader RIP scores were also successful in identifying and associating with higher impacting invasive alien species. 5. Synthesis and applications. The Relative Impact Potential metric combines the per capita effects of invaders with their abundances, relative to trophically analogous natives, and is successful in predicting the likelihood and degree of ecological impact caused by invasive alien species. As the metric constitutes readily measurable features of individuals, populations and species across abiotic and biotic context-dependencies, even emerging and potential future invasive alien species can be assessed. The Relative Impact Potential metric can be rapidly utilized by scientists and practitioners and could inform policy and management of invasive alien species across diverse taxonomic and trophic groups.
•Background points are widely used in species distribution models.•The standard background point sampling method is inferior.•Sampling background points in environmental space yields more stable and ...more accurate models.•Stratified random in environmental space sampling yields the most accurate models.•Fully random in environmental space sampling yields the most stable models.
Species distribution models (SDMs) have become central tools in ecology and biogeography. Although they can be fitted with different types of species data (e.g. presence-absence, abundance), the most common approach, based on data from large species repositories, is to use simple occurrences (i.e. presence-only) combined with background points (BP; also called pseudo-absences). But how should we sample these background points, and how does this choice affect SDMs? In most studies so far, BP were sampled randomly in geographic space, yet theory rather suggests, if a species is at equilibrium, that it is better to sample them in a stratified way in environmental space. However, this potential improvement of SDM predictions has never been tested. Furthermore, a typical assumption behind SDMs is that the modelled species are at equilibrium with their environment. But how do these models perform when species are in disequilibrium, as is the case for most invasive species? To answer these questions, we selected 30 different species (10 insects, 10 mammals and 10 plants; for each group 5 were invasive and 5 were considered at equilibrium) and for each we calibrated SDMs with different types of background selections: random in environmental space, random-stratified in environmental space, random in geographic space, and random-stratified in geographic space. For each SDM we assessed both predictive performance using standard metrics and their stability using a new approach that compares the model's habitat suitability projection with those of a SDM calibrated with virtual occurrence data generated from the most suitable areas. Finally, we compared the predictive performance of species distribution models of invasive alien (disequilibrium) species versus native (equilibrium) species by comparing model stability and performance metrics of the two groups. We found that sampling BP in a stratified-random way in environmental space yields the highest performance metrics, and that sampling fully randomly in environmental space yields the most stable models. This has implications for the use of SDMs in conservation, as the classical and frequently used fully random in geographic space BP are found to produce both less accurate and less stable models. Our results indicate that the best approach is to use stratified random in environmental space BP sampling if accuracy is essential, and fully random in environmental space BP sampling if model stability is essential.
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