The recent widespread adoption of citizen science represents a significant source of species occurrence data for spatial ecology and conservation biology. Many opportunities for the conservation of rare species and species assemblages arise from the wealth of data made available by sources such as iNaturalist, eBird, and MonarchWatch. However, inconsistencies arising from the spatial locations and distributions of citizen science data, such as biases towards large population centers and charismatic, easily-identifiable species, require further analyses to understand the implications of the uses of these data in conservation planning. This research identifies spatial patterns in citizen science data points across the blackland prairie ecoregion of Texas, an area home to remnants of the rarest prairie ecosystem in North America. Specifically, the occurrence of citizen science data in public and private lands are discerned and mapped across the ecoregion for three plant species representative of the Texas Blackland Prairies ecoregion, 2 invasive grasses (Bothriochloa ischaemum and Sorghum halepense) and 1 native grass (Bothriochloa laguroides var. torreyana). The distribution of these species occurrences were assessed with regards to both large population centers and public and private land and quantified using geographically weighted regression (GWR), with comparisons made to highly observed monarch butterflies (Danaus plexxipus).
Results/Conclusions
Analysis of the abundance and distribution of three Blackland Prairie grasses revealed distinct patterns in iNaturalist observations. Both invasive species, Johnsongrass (Sorghum halepense) and King Ranch Bluestem (Bothriochloa ischaemum), were reported significantly more times than the native Silverbeard Grass (Bothriochloa laguroides). While King Ranch Bluestem is more widespread than Johnsongrass throughout this region, the charismatic and large spikelet inflorescence of Johnsongrass potentially make it more easily recognized. Both species’ negative reputations as invasive likely further contribute to the greater number of citizen science occurrences. The findings suggest opportunities to target large gaps and inconsistencies in the seemingly vast datasets offered by citizen science platforms and support recommendations for land managers and landowners. This work provides valuable insight into the use of citizen science data for both public and private land conservation, especially important in Texas, a state with 97% privately-held land.