Publications by authors named "Ian Pfingsten"

2 Publications

  • Page 1 of 1

Population extinctions driven by climate change, population size, and time since observation may make rare species databases inaccurate.

PLoS One 2019 17;14(10):e0210378. Epub 2019 Oct 17.

Wildlife/Botany & Fisheries/Aquatics Data Coordinator, Branch of Biological Resources, United States Bureau of Land Management, Oregon State Office, Portland, OR, United States of America.

Loss of biological diversity through population extinctions is a global phenomenon that threatens many ecosystems. Managers often rely on databases of rare species locations to plan land use actions and conserve at-risk taxa, so it is crucial that the information they contain is accurate and dependable. However, small population sizes, long gaps between surveys, and climate change may be leading to undetected extinctions of many populations. We used repeated survey records for a rare but widespread orchid, Cypripedium fasciculatum (clustered lady's slipper), to model population extinction risk based on elevation, population size, and time between observations. Population size and elevation were negatively associated with extinction, while extinction probability increased with time between observations. We interpret population losses at low elevations as a potential signal of climate change impacts. We used this model to estimate the probability of persistence of populations across California and Oregon, and found that 39%-52% of the 2415 populations reported in databases from this region are likely extinct. Managers should be aware that the number of populations of rare species in their databases is potentially an overestimate, and consider resurveying these populations to document their presence and condition, with priority given to older reports of small populations, especially those at low elevations or in other areas with high vulnerability to climate or land cover change.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210378PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797133PMC
March 2020

Trends in nonindigenous aquatic species richness in the United States reveal shifting spatial and temporal patterns of species introductions.

Aquat Invasions 2018 Sep;13(3):323-338

U.S. Environmental Protection Agency, National Exposure Research Laboratory, Research Triangle Park, NC 27711, USA.

Understanding the spatial and temporal dynamics underlying the introduction and spread of nonindigenous aquatic species (NAS) can provide important insights into the historical drivers of biological invasions and aid in forecasting future patterns of nonindigenous species arrival and spread. Increasingly, public databases of species observation records are being used to quantify changes in NAS distributions across space and time, and are becoming an important resource for researchers, managers, and policy-makers. Here we use publicly available data to describe trends in NAS introduction and spread across the conterminous United States over more than two centuries of observation records. Available data on first records of NAS reveal significant shifts in dominance of particular introduction patterns over time, both in terms of recipient regions and likely sources. These spatiotemporal trends at the continental scale may be subject to biases associated with regional variation in sampling effort, reporting, and data curation. We therefore also examined two additional metrics, the number of individual records and the spatial coverage of those records, which are likely to be more closely associated with sampling effort. Our results suggest that broad-scale patterns may mask considerable variation across regions, time periods, and even entities contributing to NAS sampling. In some cases, observed temporal shifts in species discovery may be influenced by dramatic fluctuations in the number and spatial extent of individual observations, reflecting the possibility that shifts in sampling effort may obscure underlying rates of NAS introduction.
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http://dx.doi.org/10.3391/ai.2018.13.3.02DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707539PMC
September 2018
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