Regional invasion history and land use shape the prevalence of non-native species in local assemblages.

The ecological impact of non-native species arises from their establishment in local assemblages. However, the rates of non-native spread in new regions and their determinants have not been comprehensively studied. Here, we combined global databases documenting the occurrence of non-native species and residence of non-native birds, mammals, and vascular plants at regional and local scales to describe how the likelihood of non-native occurrence and their proportion in local assemblages relate with their residence time and levels of human usage in different ecosystems. Our findings reveal that local non-native occurrence generally increases with residence time. Colonization is most rapid in croplands and urban areas, while it is slower and variable in natural or semi-natural ecosystems. Notably, non-native occurrence continues to rise even 200 years after introduction, especially for birds and vascular plants, and in other land-use types rather than croplands and urban areas. The impact of residence time on non-native proportions is significant only for mammals. We conclude that the continental exchange of biotas requires considerable time for effects to manifest at the local scale across taxa and land-use types. The unpredictability of future impacts, implied by the slow spread of non-native species, strengthens the call for stronger regulations on the exchange of non-native species to reduce the long-lasting invasion debt looming on ecosystems' future.

Using citizen science data for predicting the timing of ecological phenomena across regions.

The scarcity of long-term observational data has limited the use of statistical or machine-learning techniques for predicting intraannual ecological variation. However, time-stamped citizen-science observation records, supported by media data such as photographs, are increasingly available. In the present article, we present a novel framework based on the concept of relative phenological niche, using machine-learning algorithms to model observation records as a temporal sample of environmental conditions in which the represented ecological phenomenon occurs. Our approach accurately predicts the temporal dynamics of ecological events across large geographical scales and is robust to temporal bias in recording effort. These results highlight the vast potential of citizen-science observation data to predict ecological phenomena across space, including in near real time. The framework is also easily applicable for ecologists and practitioners already using machine-learning and statistics-based predictive approaches.

Assessing the Presence of Pithomyces chartarum in Pastureland Using IoT Sensors and Remote Sensing: The Case Study of Terceira Island (Azores, Portugal).

Spores from the fungus Pithomyces chartarum are commonly found on Azorean pastures. When consumed by cattle along with the grass, these spores cause health issues in the cattle, resulting in animal suffering and financial losses. For approximately two years, we monitored meteorological parameters using weather stations and collected and analyzed grass samples in a laboratory to control for the presence of spores. The data confirmed a connection between meteorology and sporulation, enabling the prediction of sporulation risk. To detect the presence of spores in pastures rather than predict it, we employed field spectrometry and Sentinel-2 reflectance data to measure the spectral signatures of grass while controlling for spores. Our findings indicate that meteorological variables from the past 90 days can be used to predict sporulation, which can enhance the accuracy of a web-based alert system used by farmers to manage the risk. We did not detect significant differences in spectral signatures between grass with and without spores. These studies contribute to a deeper understanding of P. chartarum sporulation and provide actionable information for managing cattle, ultimately improving animal welfare and reducing financial losses.

Predicting the risk of invasion by broadleaf watermilfoil (Myriophyllum heterophyllum) in mainland Portugal.

Broadleaf water milfoil (Myriophyllum heterophyllum) is an emerging invasive alien plant in Europe, and thus a priority for European Union (EU)-level surveillance, monitoring, and eradication. This species is native to North America and threatens aquatic ecosystems by creating dense stands that can fill an entire water body, leading to high economic costs and the loss of native biodiversity. Although its presence in Portugal is not reported, the species has already been established in several European countries, including neighboring Spain. In this study, we assessed the risk of invasion by this species in mainland Portugal by jointly considering environmentally suitable areas and the risk of human-mediated introduction. Environmental suitability was estimated using MaxEnt, which relates the known species distribution to climate, topography, and soil variables. The model achieved a mean area under the curve value of 0.96 ± 0.008 and identified the mean temperature of the warmest quarter as the most relevant variable for explaining the species distribution (67.2 %). Predictions from the model indicated that the peaks of suitability values were distributed mainly in temperate climate regions along central and northern coastal areas in Portugal. The risk of introduction was estimated by mapping and calculating the spatial density of the aquarium stores. Jointly considering environmental suitability and risk of introduction, we observed that hotspots at risk of invasion are concentrated on the Portuguese central and northern coasts and in the two main metropolitan areas, Lisbon and Porto. Several risk hotspots fall within protected areas and sites designated under the EU Habitats Directive, comprising water bodies of high significance for maintaining local vegetation and fauna. Therefore, it is necessary to take measures to reduce the risk of invasion by this species, namely, surveillance and monitoring efforts confirming its absence in the national territory and preventing its future arrival.

Potential sources of time lags in calibrating species distribution models.

The Anthropocene is characterized by a rapid pace of environmental change and is causing a multitude of biotic responses, including those that affect the spatial distribution of species. Lagged responses are frequent and species distributions and assemblages are consequently pushed into a disequilibrium state. How the characteristics of environmental change-for example, gradual 'press' disturbances such as rising temperatures due to climate change versus infrequent 'pulse' disturbances such as extreme events-affect the magnitude of responses and the relaxation times of biota has been insufficiently explored. It is also not well understood how widely used approaches to assess or project the responses of species to changing environmental conditions can deal with time lags. It, therefore, remains unclear to what extent time lags in species distributions are accounted for in biodiversity assessments, scenarios and models; this has ramifications for policymaking and conservation science alike. This perspective piece reflects on lagged species responses to environmental change and discusses the potential consequences for species distribution models (SDMs), the tools of choice in biodiversity modelling. We suggest ways to better account for time lags in calibrating these models and to reduce their leverage effects in projections for improved biodiversity science and policy.

Economic costs of invasive non-native species in urban areas: An underexplored financial drain.

Urbanization is an important driver of global change associated with a set of environmental modifications that affect the introduction and distribution of invasive non-native species (species with populations transported by humans beyond their natural biogeographic range that established and are spreading in their introduced range; hereafter, invasive species). These species are recognized as a cause of large ecological and economic losses. Nevertheless, the economic impacts of these species in urban areas are still poorly understood. Here we present a synthesis of the reported economic costs of invasive species in urban areas using the global InvaCost database, and demonstrate that costs are likely underestimated. Sixty-one invasive species have been reported to cause a cumulative cost of US$ 326.7 billion in urban areas between 1965 and 2021 globally (average annual cost of US$ 5.7 billion). Class Insecta was responsible for >99 % of reported costs (US$ 324.4 billion), followed by Aves (US$ 1.4 billion), and Magnoliopsida (US$ 494 million). The reported costs were highly uneven with the sum of the five costliest species representing 80 % of reported costs. Most reported costs were a result of damage (77.3 %), principally impacting public and social welfare (77.9 %) and authorities-stakeholders (20.7 %), and were almost entirely in terrestrial environments (99.9 %). We found costs reported for 24 countries. Yet, there are 73 additional countries with no reported costs, but with occurrences of invasive species that have reported costs in other countries. Although covering a relatively small area of the Earth's surface, urban areas represent about 15 % of the total reported costs attributed to invasive species. These results highlight the conservative nature of the estimates and impacts, revealing important biases present in the evaluation and publication of reported data on costs. We emphasize the urgent need for more focused assessments of invasive species' economic impacts in urban areas.