The invasive species tiers framework was designed to help regional and state managers think strategically about which species to assign to which management priorities from overwhelmingly long lists of non-native and potentially invasive species. The data driven process developed here brings efficiency and standardization to the task of categorizing invasive species into priorities for a target region, which is often done with varying degrees of subjectivity by resource managers. However, since data gaps over large regions and lack of published information on impacts are common, the expertise of professionals dealing with invasive species was invaluable to informing the finalized tiers. By interacting with the experts, our work further informed expert opinions in different regions while also taking into account information not available in existing datasets.
Though the tier lists generated are particular to the invasive species of NYS, this process can be replicated with other similar sources of locational data and invasiveness information. Federal and non-governmental databases in the United States are available for focused invasive species reporting, such as USGS NAS, EDDMapS, and iMapInvasives (Reaser et al. 2020). However, in the absence of resources and political will for invasive species mapping projects, a region or state might have limited data entered into these targeted systems.
With the rise of simple and mobile mapping interfaces, species location data from the public has become more abundant, particularly as unstructured observation reports into systems such as iNaturalist (Rapacciuolo et al. 2021). There are at least 26 community science-focused databases containing nonnative species observations with most reporting in North America and Western Europe (Johnson et al. 2020). In Version 1 of the tiers process, iNaturalist data was not included, since the initial plan was to only use data from systems focused on invasive species reporting. However, after the first round of expert review, it became apparent that many species, particularly ones in low abundance, were underreported in the state invasive species database, yet captured by public reports in iNaturalist. Upon recommendations by the expert reviewers, iNaturalist data was incorporated into the tiering process for Version 2.
Bringing iNaturalist data into the tier analysis increased the number of high impact species and overall populations of non-native species. There were, however, some limitations important to note. Since much of the information in iNaturalist is crowdsourced, such as species identifications in reports and whether a species is flagged as introduced to a location, there is the possibility of errors in the dataset. Also, the comprehensive list of non-native species in iNaturalist greatly increased the number of species names to match to the baseline from iMapInvasives, which focuses on species known or suspected to be invasive. Species that were not flagged as “high impact” were categorized as untiered, making this list longer and more difficult for experts to review. And while the iNaturalist data was useful for new presumed invasive species, such as ornamental species that had been noted by the expert reviewers as growing aggressively outside of cultivation, many reports were obviously intentional plantings from the photos submitted. The field in iNaturalist for “captive / cultivated” species is underutilized; none of the approximately 200,000 introduced species records in New York downloaded for the analysis were marked as captive. Finally, not all species are reported evenly in unstructured community science databases (Ward 2014; Rapacciuolo et al. 2021; Callaghan et al. 2021). Expert reviewers noted improved alignment of data and expert tiers with iNaturalist data for showy species, such as Japanese primrose (Primula japonica), but not for less detectable species, such as grasses. Awareness of these and other caveats are important, yet in the absence of other data sources, iNaturalist data can offer a means to generating lists of invasive species observed in a region and watchlists of species in a buffer surrounding the region of interest (Young et al. 2021).
In addition to spatial information, the data tier analysis relied on ecological invasiveness and socioeconomic assessments for each species. It can take months, if not years of work to produce comprehensive assessments for regions with many species (Heikkilä 2011). We had the luxury of using impact assessments for over 600 species that were previously completed by the NYS Department of Environmental Conservation over the course of a decade using a standardized protocol (Jordan et al. 2012). Other standardized systems for evaluating invasiveness could be used, such as the IUCN Environmental Impact Classification for Alien Taxa (Hawkins et al. 2015).
The final critical element in this prioritization scheme is expert feedback. As previously stated, expert feedback filled in gaps in the data and provided a counterbalance to our automated approach. Expert feedback was responsible for several improvements to the data tiering process between the first and second versions, including lengthening the separation distance to 100 meters, using socioeconomic impacts as a criterion, and including observation records from iNaturalist. Also, comparing data tiers to expert tiers allowed us to evaluate the effectiveness of different variables to bin the high impact species into appropriate tiers; we found the simplistic method of binning the species into thirds by number of populations outperformed more complex approaches. Also, the expert feedback on species that were “underreported in the data” prompted a push for new observations to be reported to iMapInvasives so future tier analyses will be more accurate.
These new tier lists are currently being used in New York by state and regional invasive species managers in their prioritization decisions. Seven of the eight NY PRISMs incorporate the tier framework into their priority species webpages, and PRISM and statewide tier rankings are informing which species projects receive management contracts and where managers direct their resources. At the statewide level, the Tier 1 lists are being used for a ‘horizon scanning’ committee that will assess risks posed by new incoming invasive species, which is a recommended action set forth in the NYS Invasive Species Comprehensive Management Plan (NYS Department of Environmental Conservation 2018).
The online searchable tiers table and StoryMap developed to explain the process will help NYS managers communicate invasive species efforts with national invasive species organizations and neighboring states, as well as between NYS agencies and regions. These resources will also help connect and coordinate management efforts between PRISMs. And they will educate the public about how invasive species management decisions are made across the state.
The tiers process will be repeated each year by NYNHP with updated data from the previous field season. Scripts are being developed to automate the processing steps of Version 2, such as taxonomy matching and separation distance analyses. The expert review spreadsheets will have the previous year’s data and expert tiers, with changes in the new data tiers highlighted to facilitate expert review. Any changes to the expert tiers will be reflected on the publicly available online tiers table.
This process developed and tested for NYS and the NY PRISMs is replicable and scalable to other regions of interest. Widespread adoption of similar data-driven tiers would allow neighboring states and provinces to share a common management language and better coordinate invasive species management efforts.