Abstract
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.
Highlights
Invasive alien species (IAS) are a leading contributor to biodiversity loss (Bellard et al 2013; Simberloff et al 2013; IPBES 2019) and cause annual economic damage in the order of hundreds of billions of US dollars in each of many countries around the world (Pimentel et al 2005; Bradshaw et al 2016; Sepulveda et al 2020)
Total rubric scores for the 41 IAS reporting apps in our sample ranged from 27.93% to 66.35% of the maximum score (29.33 – 69.67 points; Fig. 2), with a mean of 46.64% ± 10.88% (48.98 ± 11.42 points; Fig. 2)
We found that 28 of 41 (68.29%) sampled apps were from North America, followed by five apps from the European Union, two apps from the United Kingdom, three from Australia and one app focused on Eastern and Southern Africa (Suppl. material 3: Table S3)
Summary
Invasive alien species (IAS) are a leading contributor to biodiversity loss (Bellard et al 2013; Simberloff et al 2013; IPBES 2019) and cause annual economic damage in the order of hundreds of billions of US dollars in each of many countries around the world (Pimentel et al 2005; Bradshaw et al 2016; Sepulveda et al 2020). Reports from volunteers (commonly called community or citizen scientists) make growing contributions to meeting these monitoring data needs, from providing first detections of new invasions (Vendetti et al 2018; Eritja et al 2019) to providing additional data that improves species distribution models The advent and rapid growth of mobile technology and smartphone software applications (hereafter apps) have greatly enhanced the potential for IAS reporting and the collection of crowdsourced (i.e. derived from many contributions) IAS occurrence data at unprecedented scales (Silvertown 2009; Teacher et al 2013; Adriaens et al 2015; Marchante et al 2017). The integration of mobile apps with centralised databases is a major technological innovation contributing to the potential increase in available community science data for meeting the data demands of EDRR (Andrachuk et al 2019; Wallace et al 2020)
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