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Seventy Years of Stream‐Fish Collections Reveal

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Seventy Years of Stream‐Fish Collections Reveal DOI: 10.1111/ddi.12671 BIODIVERSITY RESEARCH Seventy years of stream- fish collections reveal invasions and native range contractions in an Appalachian (USA) watershed Joseph D. Buckwalter1 | Emmanuel A. Frimpong1 | Paul L. Angermeier1,2 | Jacob N. Barney3 1Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, Abstract USA Aim: Knowledge of expanding and contracting ranges is critical for monitoring inva- 2 Virginia Cooperative Fish and Wildlife sions and assessing conservation status, yet reliable data on distributional trends are Research Unit, U. S. Geological Survey, Virginia Tech, Blacksburg, VA, USA lacking for most freshwater species. We developed a quantitative technique to detect 3Department of Plant Pathology, Physiology, the sign (expansion or contraction) and functional form of range- size changes for and Weed Science, Virginia Tech, Blacksburg, freshwater species based on collections data, while accounting for possible biases due VA, USA to variable collection effort. We applied this technique to quantify stream- fish range Correspondence expansions and contractions in a highly invaded river system. Emmanuel A. Frimpong, Department of Fish and Wildlife Conservation, Virginia Tech, Location: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA. Blacksburg, VA, USA. Methods: We compiled a 77- year stream- fish collections dataset partitioned into ten Email: [email protected] time periods. To account for variable collection effort among time periods, we aggre- Editor: John Wilson gated the collections into 100 watersheds and expressed a species’ range size as de- tections per watershed (HUC) sampled (DPHS). We regressed DPHS against time by species and used an information- theoretic approach to compare linear and nonlinear functional forms fitted to the data points and to classify each species as spreader, stable or decliner. Results: We analysed changes in range size for 74 UMNR fishes, including 35 native and 39 established introduced species. We classified the majority (51%) of introduced species as spreaders, compared to 31% of natives. An exponential functional form fits best for 84% of spreaders. Three natives were among the most rapid spreaders. All four decliners were New River natives. Main conclusions: Our DPHS- based approach facilitated quantitative analyses of dis- tributional trends for stream fishes based on collections data. Partitioning the dataset into multiple time periods allowed us to distinguish long- term trends from population fluctuations and to examine nonlinear forms of spread. Our framework sets the stage for further study of drivers of stream- fish invasions and declines in the UMNR and is widely transferable to other freshwater taxa and geographic regions. KEYWORDS conservation assessment, functional form, introduced species, native invaders, range expansion, species declines Diversity and Distributions. 2018;24:219–232. wileyonlinelibrary.com/journal/ddi © 2017 John Wiley & Sons Ltd | 219 220 | BUCKWALTER ET AL. 1 | INTRODUCTION (data points) enables trend detection through regression of range- size estimates against time. At least one- quarter of the world’s freshwater fishes (39% in North Range expansion approximates the logistic law (Verhulst, 1838; America) are imperiled (Helfman, 2007; Jelks et al., 2008). Freshwater i.e., initial exponential spread becoming dampened as accessible, fishes had the highest extinction rate among vertebrates in the 20th suitable sites are saturated) if sampling captures the entire scope of century, which was ~877 times greater than the background rate in an invasion, which is often not the case. Depending on the invasion North America (Burkhead, 2012). Biological invasions are among the stage attained and the window of time represented by a collections leading causes of extinction of freshwater fishes globally (Helfman, dataset, range expansion may exhibit alternate functional forms, such 2007) through adverse effects such as hybridization, competition, as exponential or linear, which are nested within the general logistic predation, disease, food web and ecosystem changes, and habitat al- model (Figure 1). Thus, detecting a trend entails comparing multiple teration (Cucherousset & Olden, 2011). Invasive species contributed candidate models of change in range size against the null hypothe- to 68% of the freshwater fish extinctions in North America (Miller, sis (no trend). Furthermore, the observed form of range- size change, Williams, & Williams, 1989). when interpreted in conjunction with other introduction attributes Knowledge of long- term trends in species’ range sizes is essen- (e.g., time since introduction, propagule pressure) may have import- tial for assessments of conservation status and invasive spread, but ant implications for the future trajectory of an invasion. For instance, such analyses require long- term, broadscale species distribution exponential increase in range size implies that a species is likely to data. Since long- term monitoring datasets collected using consis- continue spreading in the near future and its impacts likely to increase. tent, systematic protocols are scarce, distributional trends have Slow linear growth co- occurring with relatively small range size or re- yet to be quantitatively assessed for most freshwater fishes, and cent introduction may characterize an invasion in lag phase (Aagaard evidence of changing distributions has been largely subjective and & Lockwood, 2014), whereas slow linear growth with large range size lacking in rigorous quantification (Olden & Poff, 2005). However, may indicate logistic dampening (Figure 1). collections data compiled from museums, universities, agencies, Unless an ecosystem has been greatly altered from its natural state, and individuals can support sound empirical analyses of distribu- native species as a group, given their longer biogeographic history in a tional trends if sources of bias are accounted for (Botts, Erasmus, & basin, are typically assumed to be in equilibrium with the environment Alexander, 2012; Shaffer, Fisher, & Davidson, 1998; Telfer, Preston, and therefore to exhibit relatively stable range sizes, whereas invaders & Rothery, 2002). remain in disequilibrium (i.e., spreading logistically, Figure 1) until suit- When comparing historical and modern collections data, several able areas have been filled (Araújo & Pearson, 2005; Guisan & Thuiller, sources of bias associated with collection effort must be considered: 2005; Peterson, 2003). Thus, comparing the spread rates of introduced (1) collection effort must be sufficient in each time period such that versus native species may provide exploratory insights into the degree absence from a sampling unit is meaningful (Shaffer et al., 1998). to which (1) introduced species have achieved equilibrium in the re- The rate of omission errors (“false absences”; i.e., non- detection of ceiving environment, with implications for possible future impacts; and a resident species) can be reduced by pooling collections over larger (2) environmental changes have altered native species ranges. spatial (e.g., grid cells, stream reaches or watersheds) or temporal units; (2) variation in sampling intensity among time periods biases Lag phaseExponential phaseStable phase observed trends in range size, but can be accounted for by express- Saturation E ing range size for a given time period as the proportion of all units sampled in which a focal species was found (Botts et al., 2012; Loo, D Keller, & Leung, 2007; Olden & Poff, 2005; Telfer et al., 2002); (3) uneven spatial distribution of collections among time periods may size nge Inflection point confound analyses of trends in range size. If necessary, analyses can Ra C be done using only data from units sampled during all time periods, or by subsampling densely sampled units (Botts et al., 2012); (4) sam- pling efficiency or selectivity may also change over time (e.g., due to B a shift in sampling gear or targeted species; Botts et al., 2012; Shaffer A et al., 1998). Time (generations) since introduction Population fluctuation is a possible source of bias (e.g., mistak- FIGURE 1 The logistic law of population growth (Verhulst, 1838) ing noise for a signal) when measuring changes in range size (Faber- adapted to reflect observable functional forms of range expansion. Langendoen et al., 2012; IUCN, 2016). However, prior studies to Depending on which phase of the underlying logistic growth curve detect range changes based on presence- only collections data (Botts is represented in a collections dataset, an invasion may exhibit alternate forms of spread such as stable or slowly rising linear (A, et al., 2012; Olden & Poff, 2005; Telfer et al., 2002) considered only E), exponential (B), rapidly rising linear (C) or logistic dampening two time periods (historical vs. modern), an approach that provides no (D). “Saturation” indicates that an invading organism occupies all statistical basis to distinguish a long- term trend in range size (signal) accessible, suitable sites in the invaded area. [Colour figure can be from short- term fluctuations (noise). Including multiple time periods viewed at wileyonlinelibrary.com] BUCKWALTER ET AL. | 221 Our objectives for this study were to (1) develop a quantita- the 1970s, supplemented by unauthorized interbasin transfers of tive framework to detect the sign and functional form of long- term baitfishes since the mid- 20th century, has added 56 established in- changes in range size of freshwater species based
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