Documenting whether a biotic taxon is native or alien to an ecosystem has theoretical value for ecological and evolutionary studies, and has practical value because it can potentially identify a taxon as a desirable component of an ecosystem or target it for removal. In some cases, however, such background information is inadequate or unavailable. Here we use paleo-DNA to re-evaluate the historical status of yellow perch in the 6 million acre Adirondack State Park of northern New York. Yellow perch DNA in a 2200-year sediment record reveals a long-term native status for these supposedly alien fish and challenges assumptions that they necessarily exclude native trout from upland lakes. Similar approaches could be applied to other species with uncertain historical distributions and could help to identify unrecognized pockets of biodiversity.

Road runoff is understood to be a significant stressor in terrestrial and aquatic ecosystems, yet the effects of this stressor are poorly understood at large spatial scales. We developed an efficient method for estimating the spatial impact of road runoff on lands and waters over large geographic areas and then applied our methodology to the 2.4 million ha Adirondack Park in New York State. We used TauDEM hydrologic modeling and a series of ESRI GIS processes to delineate surface flow downslope of paved roads, illustrating the potential movement of pollutants originating from paved roads through the USGS 10 m DEM topography. We then estimated the land and surface water areas, number of water bodies, and total stream length potentially impacted by road runoff from paved roads. We found that as much as 11% of land area, 77% of surface water area, 1/3 of the water bodies, and 52% of stream length in the Adirondack Park may be impacted by road runoff. The high degree of hydrologic association between paved roads and the lands and waters of this region strongly suggests that the environmental impacts of road runoff should be evaluated along with other regional stressors currently being studied. Being able to estimate the spatial impact of road runoff is important for designing monitoring programs that can explicitly monitor this stressor while also providing opportunities to understand the interaction of multiple environmental stressors.