Modeling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists

Combining ranger records and biogeographical models to identify the current and potential distribution of an expanding mesocarnivore in southern Europe

Human-wildlife conflicts (HWC) are increasing and are potentially harmful to both people and wildlife. Understanding the current and potential distribution of wildlife species involved in HWC, such as carnivores, is essential for implementing management and conservation measures for such species. In this study, we assessed both the current distribution and potential distribution (forecast) of the Egyptian mongoose (Herpestes ichneumon) in the central part of the Iberian Peninsula. We acquired data concerning mongoose occurrences through an online questionnaire sent to environmental rangers. We used the municipality level as the sampling unit because all municipalities within the study area were covered at least by one ranger. Using the information provided by rangers (i.e. occurrences in their municipalities), we constructed environmental favourability distribution models to assess current and potential mongoose distribution through current distribution models (CDM) and ecological models (EM), respectively. >300 rangers participated in the survey and mongooses were reported in a total of 181 of 921 municipalities studied. The CDM model showed a current distribution mainly concentrated on the western part of the study area, where intermediate-high favourability values predominated. The EM model revealed a wider potential distribution, including the south-east part of the study area, which was also characterised by intermediate-high favourability values. Our predictions were verified using independent data, including confirmation of mongoose reproduction by rangers, reports by other experts, and field sampling in some areas. Our innovative approach based on an online survey to rangers coupled with environmental favourability models is shown to be a useful methodology for assessing the current distribution of cryptic but expanding wildlife species, while also enabling estimations of future steps in their expansion. The approach proposed may help policy decision-makers seeking to ensure the conservation of expanding wildlife species, for example, by designing awareness campaigns in areas where the target species is expected to arrive.

Habitat suitability modelling to predict the distribution of deep coral ecosystems: The case of Linosa Island (southern Mediterranean Sea, Italy)

In areas with limited field data, predictive habitat mapping is a valuable method for elucidating species-environment relationships and enhancing our knowledge of the spatial distribution and complexity of benthic habitats. Species distribution models (SDMs) can be an important tool to support in science-based ecosystem management. The availability of direct observations of mesophotic species, including gorgonians and black corals, during costly surveys is generally limited. Therefore, predicting the distribution of mesophotic species in relation to key physical parameters of the seafloor would help improving conservation strategies in existing and new Marine Protected Areas (MPAs). This study aims to assess the distribution of gorgonians and black corals off Linosa Island, in the Strait of Sicily, a biogeographic boundary area between the western and eastern Mediterranean. The volcanic island of Linosa represents a small, naturally preserved area, with very limited human pressure, hosting rich marine benthic biodiversity on its wide submarine portions. Distribution of the most common coral species off Linosa Island was modelled under an SDM framework, relying on direct observations collected during two research cruises in 2016 and 2017 and a series of terrain parameters acquired through geophysical techniques. We used the so-called "ensemble of small models" approach to calibrate SDMs, which achieved fair-to-excellent results (AUC >0.7). In addition to identifying depth as the primary factor influencing coral distribution, our study also highlighted ruggedness as a significant terrain variable. Specifically, the depth range of 110-230 m emerged as the critical parameter determining habitat suitability for all modelled species, also highlighting peculiar and specie-specific habitat requirements.

Utilizing Molecular Epidemiology and Citizen Science for the Surveillance of Lagoviruses in Australia

Australia has multiple lagoviruses with differing pathogenicity. The circulation of these viruses was traditionally determined through opportunistic sampling events. In the lead up to the nationwide release of RHDVa-K5 (GI.1aP-GI.1a) in 2017, an existing citizen science program, RabbitScan, was augmented to allow members of the public to submit samples collected from dead leporids for lagovirus testing. This study describes the information obtained from the increased number of leporid samples received between 2015 and 2022 and focuses on the recent epidemiological interactions and evolutionary trajectory of circulating lagoviruses in Australia between October 2020 and December 2022. A total of 2771 samples were tested from January 2015 to December 2022, of which 1643 were lagovirus-positive. Notable changes in the distribution of lagovirus variants were observed, predominantly in Western Australia, where RHDV2-4c (GI.4cP-GI.2) was detected again in 2021 after initially being reported to be present in 2018. Interestingly, we found evidence that the deliberately released RHDVa-K5 was able to establish and circulate in wild rabbit populations in WA. Overall, the incorporation of citizen science approaches proved to be a cost-efficient method to increase the sampling area and enable an in-depth analysis of lagovirus distribution, genetic diversity, and interactions. The maintenance of such programs is essential to enable continued investigations of the critical parameters affecting the biocontrol of feral rabbit populations in Australia, as well as to enable the detection of any potential future incursions.

China-US grain trade shapes the spatial genetic pattern of common ragweed in East China cities

Common ragweed is an invasive alien species causing severe allergies in urban residents. Understanding its urban invasion pathways is crucial for effective control. However, knowledge is limited, with most studies focusing on agricultural and natural areas, and occurrence record-based studies exhibiting uncertainties. We address this gap through a study in East China cities, combining population genetics and occurrence records. Leaf samples from 37 urban common ragweed populations across 15 cities are collected. Genomic and chloroplast DNA extraction facilitate analysis of spatial genetic patterns and gene flows. Additionally, international grain trade data is examined to trace invasion sources. Results indicate spatial genetic patterns impacted by multiple introductions over time. We infer the modern grain trade between the United States and China as the primary invasion pathway. Also, cities act as transportation hubs and ports of grain importation might disperse common ragweed to urban areas. Invasive species control should account for cities as potential landing and spread hubs of common ragweed.

Different facets of the same niche: Integrating citizen science and scientific survey data to predict biological invasion risk under multiple global change drivers

Citizen science initiatives have been increasingly used by researchers as a source of occurrence data to model the distribution of alien species. Since citizen science presence-only data suffer from some fundamental issues, efforts have been made to combine these data with those provided by scientifically structured surveys. Surprisingly, only a few studies proposing data integration evaluated the contribution of this process to the effective sampling of species' environmental niches and, consequently, its effect on model predictions on new time intervals. We relied on niche overlap analyses, machine learning classification algorithms and ecological niche models to compare the ability of data from citizen science and scientific surveys, along with their integration, in capturing the realized niche of 13 invasive alien species in Italy. Moreover, we assessed differences in current and future invasion risk predicted by each data set under multiple global change scenarios. We showed that data from citizen science and scientific surveys captured similar species niches though highlighting exclusive portions associated with clearly identifiable environmental conditions. In terrestrial species, citizen science data granted the highest gain in environmental space to the pooled niches, determining an increased future biological invasion risk. A few aquatic species modelled at the regional scale reported a net loss in the pooled niches compared to their scientific survey niches, suggesting that citizen science data may also lead to contraction in pooled niches. For these species, models predicted a lower future biological invasion risk. These findings indicate that citizen science data may represent a valuable contribution to predicting future spread of invasive alien species, especially within national-scale programmes. At the same time, citizen science data collected on species poorly known to citizen scientists, or in strictly local contexts, may strongly affect the niche quantification of these taxa and the prediction of their future biological invasion risk.

Plant invasion risk inside and outside protected areas: Propagule pressure, abiotic and biotic factors definitively matter

Invasive alien species are among the main global drivers of biodiversity loss posing major challenges to nature conservation and to managers of protected areas. The present study applied a methodological framework that combined invasive Species Distribution Models, based on propagule pressure, abiotic and biotic factors for 14 invasive alien plants of Union concern in Italy, with the local interpretable model-agnostic explanation analysis aiming to map, evaluate and analyse the risk of plant invasions across the country, inside and outside the network of protected areas. Using a hierarchical invasive Species Distribution Model, we explored the combined effect of propagule pressure, abiotic and biotic factors on shaping invasive alien plant occurrence across three biogeographic regions (Alpine, Continental, and Mediterranean) and realms (terrestrial and aquatic) in Italy. We disentangled the role of propagule pressure, abiotic and biotic factors on invasive alien plant distribution and projected invasion risk maps. We compared the risk posed by invasive alien plants inside and outside protected areas. Invasive alien plant distribution varied across biogeographic regions and realms and unevenly threatens protected areas. As an alien's occurrence and risk on a national scale are linked with abiotic factors followed by propagule pressure, their local distribution in protected areas is shaped by propagule pressure and biotic filters. The proposed modelling framework for the assessment of the risk posed by invasive alien plants across spatial scales and under different protection regimes represents an attempt to fill the gap between theory and practice in conservation planning helping to identify scale, site, and species-specific priorities of management, monitoring and control actions. Based on solid theory and on free geographic information, it has great potential for application to wider networks of protected areas in the world and to any invasive alien plant, aiding improved management strategies claimed by the environmental legislation and national and global strategies.

Designing a large-scale track-based monitoring program to detect changes in species distributions in arid Australia

Monitoring trends in animal populations in arid regions is challenging due to remoteness and low population densities. However, detecting species' tracks or signs is an effective survey technique for monitoring population trends across large spatial and temporal scales. In this study, we developed a simulation framework to evaluate the performance of alternative track-based monitoring designs at detecting change in species distributions in arid Australia. We collated presence-absence records from 550 2-ha track-based plots for 11 vertebrates over 13 years and fitted ensemble species distribution models to predict occupancy in 2018. We simulated plausible changes in species' distributions over the next 15 years and, with estimates of detectability, simulated monitoring to evaluate the statistical power of three alternative monitoring scenarios: (1) where surveys were restricted to existing 2-ha plots, (2) where surveys were optimized to target all species equally, and (3) where surveys were optimized to target two species of conservation concern. Across all monitoring designs and scenarios, we found that power was higher when detecting increasing occupancy trends compared to decreasing trends owing to the relatively low levels of initial occupancy. Our results suggest that surveying 200 of the existing plots annually (with a small subset resurveyed twice within a year) will have at least an 80% chance of detecting 30% declines in occupancy for four of the five invasive species modeled and one of the six native species. This increased to 10 of the 11 species assuming larger (50%) declines. When plots were positioned to target all species equally, power improved slightly for most compared to the existing survey network. When plots were positioned to target two species of conservation concern (crest-tailed mulgara and dusky hopping mouse), power to detect 30% declines increased by 29% and 31% for these species, respectively, at the cost of reduced power for the remaining species. The effect of varying survey frequency depended on its trade-off with the number of sites sampled and requires further consideration. Nonetheless, our research suggests that track-based surveying is an effective and logistically feasible approach to monitoring broad-scale occupancy trends in desert species with both widespread and restricted distributions.

Contradictory effect of climate change on American and European populations of Impatiens capensis Meerb. - is this herb a global threat?

AIMS

The present study is the first-ever attempt to generate information on the potential present and future distribution of Impatiens capensis (orange balsam) under various climate change scenarios. Moreover, the differences in bioclimatic preferences of native and non-native populations were evaluated.

LOCATION

Global.

TAXON

Angiosperms.

METHODS

A database of I. capensis localities was compiled based on the public database - the Global Biodiversity Information Facility (GBIF), herbarium specimens, and a field survey in Poland. The initial dataset was verified, and each record was assigned to one of two groups - native (3664 records from North America) or non-native (750 records from Europe and the western part of North America). The analyses involved bioclimatic variables in 2.5 arc-minutes of interpolated climate surface downloaded from WorldClim v. 2.1. MaxEnt version 3.3.2 was used to conduct the ecological niche modeling based on presence-only observations of I. capensis. Forecasts of the future distribution of the climatic niches of the studied species in 2080-2100 were made based on climate projections developed by the CNRM/CERFACS modeling and Model for Interdisciplinary Research on Climate (MIROC-6).

MAIN CONCLUSIONS

Distribution models created for "present time" showed slightly broader potential geographical ranges of both native and invasive populations of orange balsam. On the other hand, some areas (e.g. NW Poland, SW Finland), settled by the species, are far outside the modeled climate niche, which indicates a much greater adaptation potential of I. capensis. In addition, the models have shown that climate change will shift the native range of orange balsam to the north and the range of its European populations to the northwest. Moreover, while the coverage of niches suitable for I. capensis in America will extend due to climate change, the European populations will face 31-95 % habitat loss.

Habitat distribution change of commercial species in the Adriatic Sea during the COVID-19 pandemic

The COVID-19 pandemic has led to reduced anthropogenic pressure on ecosystems in several world areas, but resulting ecosystem responses in these areas have not been investigated. This paper presents an approach to make quick assessments of potential habitat changes in 2020 of eight marine species of commercial importance in the Adriatic Sea. Measurements from floating probes are interpolated through an advection-equation based model. The resulting distributions are then combined with species observations through an ecological niche model to estimate habitat distributions in the past years (2015–2018) at 0.1° spatial resolution. Habitat patterns over 2019 and 2020 are then extracted and explained in terms of specific environmental parameter changes. These changes are finally assessed for their potential dependency on climate change patterns and anthropogenic pressure change due to the pandemic. Our results demonstrate that the combined effect of climate change and the pandemic could have heterogeneous effects on habitat distributions: three species (Squilla mantis, Engraulis encrasicolus, and Solea solea) did not show significant niche distribution change; habitat suitability positively changed for Sepia officinalis, but negatively for Parapenaeus longirostris, due to increased temperature and decreasing dissolved oxygen (in the Adriatic) generally correlated with climate change; the combination of these trends with an average decrease in chlorophyll, probably due to the pandemic, extended the habitat distributions of Merluccius merluccius and Mullus barbatus but reduced Sardina pilchardus distribution. Although our results are based on approximated data and reliable at a macroscopic level, we present a very early insight of modifications that will possibly be observed years after the end of the pandemic when complete data will be available. Our approach is entirely based on Findable, Accessible, Interoperable, and Reusable (FAIR) data and is general enough to be used for other species and areas.

A framework to integrate innovations in invasion science for proactive management

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

A review of invasive species reporting apps for citizen science and opportunities for innovation

Smartphone apps have enhanced the potential for monitoring of invasive alien species (IAS) through citizen science. They now have the capacity to massively increase the volume and spatiotemporal coverage of IAS occurrence data accrued in centralised databases. While more reporting apps are developed each year, innovation across diverse functionalities and data management in this field are occurring separately and simultaneously amongst numerous research groups with little attention to trends, priorities and opportunities for improvement. This creates the risk of duplication of effort and missed opportunities for implementing new and existing functionalities that would directly benefit IAS research and management. Using a literature search of Early Detection and Rapid Response implementation, smartphone app development and invasive species reporting apps, we developed a rubric for quantitatively assessing the functionality of IAS reporting apps and applied this rubric to 41 free, English-language IAS reporting apps, available via major mobile app stores in North America. The five highest performing apps achieved scores of 61.90% to 66.35% relative to a hypothetical maximum score, indicating that many app features and functionalities, acknowledged to be useful for IAS reporting in literature, are not present in sampled apps. This suggests that current IAS reporting apps do not make use of all available and known functionalities that could maximise their efficacy. Major implementation gaps, highlighted by this rubric analysis, included limited implementation in user engagement (particularly gamification elements and social media compatibility), ancillary information on search effort, detection method, the ability to report absences and local habitat characteristics. The greatest advancement in IAS early detection would likely result from app gamification. This would make IAS reporting more engaging for a growing community of non-professional contributors and encourage frequent and prolonged participation. We discuss these implementation gaps in relation to the increasingly urgent need for Early Detection and Rapid Response frameworks. We also recommend future innovations in IAS reporting app development to help slow the spread of IAS and curb the global economic and biodiversity extinction crises. We also suggest that further funding and investment in this and other implementation gaps could greatly increase the efficacy of current IAS reporting apps and increase their contributions to addressing the contemporary biological invasion threat.

Citizen science reveals current distribution, predicted habitat suitability and resource requirements of the introduced African Carder Bee Pseudoanthidium (Immanthidium) repetitum in Australia

The introduction of non-native bee species is a major driver of ecosystem change resulting in the spread of non-native weeds, alterations to plant-pollinator interactions and competition with native species for food and nesting resources. Our lack of ecological information for many non-native organisms hinders our ability to understand the impacts of species introductions. This is often compounded by the Wallacean Shortfall—a lack of adequate knowledge of a species’ distribution in geographic space. In Australia, the African carder bee (Pseudoanthidium (Immanthidium) repetitum) was first observed in 2000 and has since become one of the most common bees in some regions. Despite its rapid population increase and range expansion, little is known about the ecology or distribution of P. repetitum. In this study, we determine the flower preferences, current distribution and predicted areas at risk of future invasion of P. repetitum using opportunistic data collected from citizen science websites, social media and museum records. We found that the current distribution of P. repetitum in Australia encompasses approximately 332,000 km2 concentrated along the eastern coast. We found considerable suitable habitat outside the current distribution including biodiversity hotspots and world heritage listed natural areas. Pseudoanthidium repetitum foraged on a wide range of plants from many families and can thus be classified as a generalist forager (polylectic). Our results suggest that P. repetitum is well suited for continued expansion in coastal Australia. Our results demonstrate the effective application of opportunistic data in overcoming knowledge gaps in species ecology and modelling of introduced species distribution.

Habitat prediction modelling for vulture conservation in Gangetic-Thar-Deccan region of India

Ecologically and economically important obligate scavengers like vultures are under threat of extinction in the old world. Several resident and migratory vulture sites and individuals are hosted by the Gangetic-Thar-Deccan region of India with varied landscapes. The landscape is under threat from anthropogenic activities and climate change impacting the habitat. Therefore, habitat suitability of vultures was analysed using species distribution model, MaxEnt, ensemble of global circulation models (CCSM4, HadGEM2AO and MIROC5), citizen science and expert collected data. Altogether, 51 models were developed and their robustness was assessed to be good for conservation purpose (AUC range 0.719-0.906). Predicted unsuitable and suitable area categories of all vultures, resident vultures and migratory vultures were identified for the present and future years (2050 and 2070) under moderate and extreme emission scenarios (RCP 4.5 and RCP 8.5). The short-term and long-term area suitability change varied between 1 and 3%. Area suitability differences were also noticed among larger (global) and smaller (local) geographical areas. The bioenvironmental parameters (land use, land cover and human footprint) played a major role in habitat determination in the current scenario. Bioclimatic factors, like precipitation parameters (precipitation seasonality bio 15 and annual precipitation bio12) and temperature parameters (isothermality bio 3 and temperature seasonality bio04), were the main model determining covariates for future prediction. An earlier hypothesis of higher suitability of forest and lower suitability of agriculture area tested in this study stood modified. Implications of the results are discussed, and conservation strategies are suggested with an advice of global strategy and local execution.

Climate Change Can Drive a Significant Loss of Suitable Habitat for Polylepis quadrijuga, a Treeline Species in the Sky Islands of the Northern Andes

It is predicted that climate change will strongly affect plant distributions in high elevation “sky islands” of tropical Andes. Polylepis forests are a dominant element of the treeline throughout the Andes Cordillera in South America. However, little is known about the climatic factors underlying the current distribution of Polylepis trees and the possible effect of global climate change. The species Polylepis quadrijuga is endemic to the Colombian Eastern Cordillera, where it plays a fundamental ecological role in high-altitude páramo-forest ecotones. We sought to evaluate the potential distribution of P. quadrijuga under future climate change scenarios using ensemble modeling approaches. We conducted a comprehensive assessment of future climatic projections deriving from 12 different general circulation models (GCMs), four Representative Concentration Pathways (R) emissions scenarios, and two different time frames (2041–2060 and 2061–2080). Additionally, based on the future projections, we evaluate the effectiveness of the National System of Protected Natural Areas of Colombia (SINAP) and Páramo Complexes of Colombia (PCC) in protecting P. quadrijuga woodlands. Here, we compiled a comprehensive set of observations of P. quadrijuga and study them in connection with climatic and topographic variables to identify environmental predictors of the species distribution, possible habitat differentiation throughout the geographic distribution of the species, and predict the effect of different climate change scenarios on the future distribution of P. quadrijuga. Our results predict a dramatic loss of suitable habitat due to climate change on this key tropical Andean treeline species. The ensemble Habitat Suitability Modeling (HSM) shows differences in suitable scores among north and south regions of the species distribution consistent with differences in topographic features throughout the available habitat of P. quadrijuga. Future projections of the HSM predicted the Páramo complex “Sumapaz-Cruz Verde” as a major area for the long-term conservation of P. quadrijuga because it provides a wide range of suitable habitats for the different evaluated climate change scenarios. We provide the first set of priority areas to perform both in situ and ex situ conservation efforts based on suitable habitat projections.

From Phenology and Habitat Preferences to Climate Change: Importance of Citizen Science in Studying Insect Ecology in the Continental Scale with American Red Flat Bark Beetle, Cucujus clavipes, as a Model Species

Simple Summary

Studies of widely distributed species often are problematic as such research usually needs to engage a lot of time, a large team of field workers, and big financial support before good quality data will be collected. Citizen scientists allow to study different aspects of species biology and ecology with significantly reduced basic operational costs of such studies. Based on the data deposited in the iNaturalist database, we studied the ecology of the American flat bark beetle in the entire area of its species range. The results clearly show high value of citizen science, particularly in studies focused on habitat preferences and phenology in both recognized subspecies of this taxon.

Abstract

The American red flat bark beetle, Cucujus clavipes, is a wide distributed saproxylic species divided into two subspecies: ssp. clavipes restricted to eastern regions of North America and ssp. puniceus occurring only in western regions of this continent. Unique morphological features, including body shape and body coloration, make this species easy to recognize even for amateurs. Surprisingly, except some studies focused on physiological adaptations of the species, the ecology of C. clavipes was almost unstudied. Based on over 500 records collected by citizen scientists and deposited in the iNaturalist data base, we studied phenological activity of adult beetles, habitat preferences and impact of future climate change for both subspecies separately. The results clearly show that spp. clavipes and ssp. puniceus can be characterized by differences in phenology and macrohabitat preferences, and their ranges do not overlap at any point. Spp. clavipes is found as more opportunistic taxon occurring in different forests as well as in urban and agricultural areas with tree vegetation always in elevations below 500 m, while elevational distribution of ssp. puniceus covers areas up to 2300 m, and the beetle was observed mainly in forested areas. Moreover, we expect that climate warming will have negative influence on both subspecies with the possible loss of proper niches at level even up to 47–70% of their actual ranges during next few decades. As the species is actually recognized as unthreatened and always co-occurs with many other species, we suggest, because of its expected future habitat loss, to pay more attention to conservationists for possible negative changes in saproxylic insects and/or forest fauna in North America. In addition, as our results clearly show that both subspecies of C. clavipes differ ecologically, which strongly supports earlier significant morphological and physiological differences noted between them, we suggest that their taxonomical status should be verified by molecular data, because very probably they represent separate species.

An overview of the history, current contributions and future outlook of iNaturalist in Australia

Citizen science initiatives and the data they produce are increasingly common in ecology, conservation and biodiversity monitoring. Although the quality of citizen science data has historically been questioned, biases can be detected and corrected for, allowing these data to become comparable in quality to professionally collected data. Consequently, citizen science is increasingly being integrated with professional science, allowing the collection of data at unprecedented spatial and temporal scales. iNaturalist is one of the most popular biodiversity citizen science platforms globally, with more than 1.4 million users having contributed over 54 million observations. Australia is the top contributing nation in the southern hemisphere, and in the top four contributing nations globally, with over 1.6 million observations of over 36000 identified species contributed by almost 27000 users. Despite the platform’s success, there are few holistic syntheses of contributions to iNaturalist, especially for Australia. Here, we outline the history of iNaturalist from an Australian perspective, and summarise, taxonomically, temporally and spatially, Australian biodiversity data contributed to the platform. We conclude by discussing important future directions to maximise the usefulness of these data for ecological research, conservation and policy.

Observer-oriented approach improves species distribution models from citizen science data

Citizen science platforms are increasingly growing, and, storing a huge amount of data on species locations, they provide researchers with essential information to develop sound strategies for species conservation. However, the lack of information on surveyed sites (i.e., where the observers did not record the target species) and sampling effort (e.g., the number of surveys at a given site, by how many observers, and for how much time) strongly limit the use of citizen science data. Thus, we examined the advantage of using an observer-oriented approach (i.e., considering occurrences of species other than the target species collected by the observers of the target species as pseudo-absences and additional predictors relative to the total number of observations, observers, and days in which locations were collected in a given sampling unit, as proxies of sampling effort) to develop species distribution models. Specifically, we considered 15 mammal species occurring in Italy and compared the predictive accuracy of the ensemble predictions of nine species distribution models carried out considering random pseudo-absences versus observer-oriented approach. Through cross-validations, we found that the observer-oriented approach improved species distribution models, providing a higher predictive accuracy than random pseudo-absences. Our results showed that species distribution modeling developed using pseudo-absences derived citizen science data outperform those carried out using random pseudo-absences and thus improve the capacity of species distribution models to accurately predict the geographic range of species when deriving robust surrogate of sampling effort.

Models of spatiotemporal variation in rabbit abundance reveal management hot spots for an invasive species

The European rabbit (Oryctolagus cuniculus) is a notorious economic and environmental pest species in its invasive range. To better understand the population and range dynamics of this species, 41 yr of abundance data have been collected from 116 unique sites across a broad range of climatic and environmental conditions in Australia. We analyzed this time series of abundance data to determine whether interannual variation in climatic conditions can be used to map historic, contemporary, and potential future fluctuations in rabbit abundance from regional to continental scales. We constructed a hierarchical Bayesian regression model of relative abundance that corrected for observation error and seasonal biases. The corrected abundances were regressed against environmental and disease variables in order to project high spatiotemporal resolution, continent-wide rabbit abundances. We show that rabbit abundance in Australia is highly variable in space and time, being driven primarily by internnual variation in temperature and precipitation in concert with the prevalence of a non-pathogenic virus. Moreover, we show that internnual variation in local spatial abundances can be mapped effectively at a continental scale using highly resolved spatiotemporal predictors, allowing "hot spots" of persistently high rabbit abundance to be identified. Importantly, cross-validated model performance was fair to excellent within and across distinct climate zones. Long-term monitoring data for invasive species can be used to map fine-scale spatiotemporal fluctuations in abundance patterns when accurately accounting for inherent sampling biases. Our analysis provides ecologists and pest managers with a clearer understanding of the determinants of rabbit abundance in Australia, offering an important new approach for predicting spatial abundance patterns of invasive species at the near-term temporal scales that are directly relevant to resource management.