Prioritizing Management of Non-Native Eurasian Watermilfoil Using Species Occurrence and Abundance Predictions

Prioritizing the prevention and control of non-native invasive species requires understanding where introductions are likely to occur and cause harm. We developed predictive models for Eurasian watermilfoil (EWM) (Myriophyllum spicatum L.) occurrence and abundance to produce a smart prioritization tool for EWM management. We used generalized linear models (GLMs) to predict species occurrence and extended beta regression models to predict abundance from data collected on 657 Wisconsin lakes. Species occurrence was positively related to the nearby density of vehicle roads, maximum air temperature, lake surface area, and maximum lake depth. Species occurrence was negatively related to near-surface lithological calcium oxide content, annual air temperature range, and average distance to all known source populations. EWM abundance was positively associated with conductivity, maximum air temperature, mean distance to source, and soil erodibility, and negatively related to % surface rock calcium oxide content and annual temperature range. We extended the models to generate occurrence and predictions for all lakes in Wisconsin greater than 1 ha (N = 9825), then prioritized prevention and management, placing highest priority on lakes likely to experience EWM introductions and support abundant populations. This modelling effort revealed that, although EWM has been present for several decades, many lakes are still vulnerable to introduction

Commonly Rare and Rarely Common: Comparing Population Abundance of Invasive and Native Aquatic Species

<div><p>Invasive species are leading drivers of environmental change. Their impacts are often linked to their population size, but surprisingly little is known about how frequently they achieve high abundances. A nearly universal pattern in ecology is that species are rare in most locations and abundant in a few, generating right-skewed abundance distributions. Here, we use abundance data from over 24,000 populations of 17 invasive and 104 native aquatic species to test whether invasive species differ from native counterparts in statistical patterns of abundance across multiple sites. Invasive species on average reached significantly higher densities than native species and exhibited significantly higher variance. However, invasive and native species did not differ in terms of coefficient of variation, skewness, or kurtosis. Abundance distributions of all species were highly right skewed (skewness>0), meaning both invasive and native species occurred at low densities in most locations where they were present. The average abundance of invasive and native species was 6% and 2%, respectively, of the maximum abundance observed within a taxonomic group. The biological significance of the differences between invasive and native species depends on species-specific relationships between abundance and impact. Recognition of cross-site heterogeneity in population densities brings a new dimension to invasive species management, and may help to refine optimal prevention, containment, control, and eradication strategies.</p></div

Abundance distributions of all invasive and all native species combined.

<p>Probability density of standardized abundance (proportion maximum abundance observed within a taxonomic group) for invasive (light purple) and native (dark purple) species, with all species combined. Abundance values are grouped into 0.05 bins.</p

Effect size of origin (invasive vs. native status) on distributional parameters.

<p>Effects are presented as the restricted maximum likelihood (REML) estimate of the difference on the natural log scale between invasive and native species (or the natural log of the ratio of invasive:native species values). Bars are 95% highest probability density interval from Markov-chain Monte Carlo (MCMC) resampling; bars that do not overlap zero (dashed line) represent significant differences between invasive and native species.</p

Abundance distributions for each species used in this analysis.

<p>Labels are coded as follows: taxonomic group abbreviation. Origin. Species ID, where taxonomic group codes are Cr = Crayfish, FHI = Hawaiian fishes, FNA = North American fishes, FSw = Swedish fishes, M = Mussel, Pl = Plant, Pr = Prawn, and S = Snail; origin codes are I = Invasive and N = Native; see Table S3 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0077415#pone.0077415.s001" target="_blank">File S1</a> for species identities. Colors correspond to taxonomic groups and in every group the darker shade corresponds to invasive species in that group. The x-axis scale shows standardized abundance (proportion of taxonomic group-level maximum abundance) and ranges from 0 to 1; the y-axis scale shows the number of sites falling into each abundance class and varies by species to accommodate different numbers of observations (sites). Note that all abundance values are greater than zero.</p

Model results for hierarchical models of statistical moments.

<p>The intercept represents the restricted maximum likelihood (REML) estimate of the value for invasive species, and the origin effect is the difference between invasive and native species values on the natural log scale. Upper and lower highest probability density (HPD) intervals are the 95% confidence intervals of the fixed effects estimates generated from Markov-chain Monte Carlo resampling. Random effects and their explained variance are also presented for each model, where the taxa effect is the variance attributable to differences among taxonomic groups in statistical moments.</p

Global variation in the beta diversity of lake macrophytes is driven by environmental heterogeneity rather than latitude

Aim : We studied global variation in beta diversity patterns of lake macrophytes using regional data from across the world. Specifically, we examined (1) how beta diversity of aquatic macrophytes is partitioned between species turnover and nestedness within each study region, and (2) which environmental characteristics structure variation in these beta diversity components. Location : Global. Methods : We used presence–absence data for aquatic macrophytes from 21 regions distributed around the world. We calculated pairwise‐site and multiple‐site beta diversity among lakes within each region using Sørensen dissimilarity index and partitioned it into turnover and nestedness coefficients. Beta regression was used to correlate the diversity coefficients with regional environmental characteristics. Results : Aquatic macrophytes showed different levels of beta diversity within each of the 21 study regions, with species turnover typically accounting for the majority of beta diversity, especially in high‐diversity regions. However, nestedness contributed 30–50% of total variation in macrophyte beta diversity in low‐diversity regions. The most important environmental factor explaining the three beta diversity coefficients (total, species turnover and nestedness) was elevation range, followed by relative areal extent of freshwater, latitude and water alkalinity range. Main conclusions : Our findings show that global patterns in beta diversity of lake macrophytes are caused by species turnover rather than by nestedness. These patterns in beta diversity were driven by natural environmental heterogeneity, notably variability in elevation range (also related to temperature variation) among regions. In addition, a greater range in alkalinity within a region, likely amplified by human activities, was also correlated with increased macrophyte beta diversity. These findings suggest that efforts to conserve aquatic macrophyte diversity should primarily focus on regions with large numbers of lakes that exhibit broad environmental gradients

Global variation in the beta diversity of lake macrophytes is driven by environmental heterogeneity rather than latitude

Abstract Aim: We studied global variation in beta diversity patterns of lake macrophytes using regional data from across the world. Specifically, we examined (1) how beta diversity of aquatic macrophytes is partitioned between species turnover and nestedness within each study region, and (2) which environmental characteristics structure variation in these beta diversity components. Location: Global. Methods: We used presence–absence data for aquatic macrophytes from 21 regions distributed around the world. We calculated pairwise‐site and multiple‐site beta diversity among lakes within each region using Sørensen dissimilarity index and partitioned it into turnover and nestedness coefficients. Beta regression was used to correlate the diversity coefficients with regional environmental characteristics. Results: Aquatic macrophytes showed different levels of beta diversity within each of the 21 study regions, with species turnover typically accounting for the majority of beta diversity, especially in high‐diversity regions. However, nestedness contributed 30–50% of total variation in macrophyte beta diversity in low‐diversity regions. The most important environmental factor explaining the three beta diversity coefficients (total, species turnover and nestedness) was elevation range, followed by relative areal extent of freshwater, latitude and water alkalinity range. Main conclusions: Our findings show that global patterns in beta diversity of lake macrophytes are caused by species turnover rather than by nestedness. These patterns in beta diversity were driven by natural environmental heterogeneity, notably variability in elevation range (also related to temperature variation) among regions. In addition, a greater range in alkalinity within a region, likely amplified by human activities, was also correlated with increased macrophyte beta diversity. These findings suggest that efforts to conserve aquatic macrophyte diversity should primarily focus on regions with large numbers of lakes that exhibit broad environmental gradients