Examining Alternative Water Management Strategies to Support Rio Grande Silvery Minnow Conservation Within and Across Years

Rio Grande Silvery Minnow (RGSM) are currently constrained to only 5% of their historic range, and their persistence is threatened by highly altered and impaired habitat conditions (Bestgen and Platania 1991). These habitat conditions have resulted from reduced spring and summer flows due to natural variability and anthropogenic water development and extraction, which have resulted in substantial geomorphic changes (Swanson et al. 2011). Successful conservation of this endangered species will require determination of how available flows can be managed to provide conditions supporting growth, reproduction, and survival of RGSM within and across a variety of water years. Previous research has identified that years with large spring high flow events and years with higher summer base flows support greater densities of RGSM during fall surveys (Dudley and Platania 2007; Archdeacon 2016; Walsworth and Budy 2021). However, given that years with large spring high flows also tend to have greater summer base flows, it remains unclear whether spring or summer flows (or both) are more critical to successful conservation of RGSM

Improving Lake Mixing Process Simulations in the Community Land Model by Using K Profile Parameterization

We improved lake mixing process simulations by applying a vertical mixing scheme, K profile parameterization (KPP), in the Community Land Model (CLM) version 4.5, developed by the National Center for Atmospheric Research. Vertical mixing of the lake water column can significantly affect heat transfer and vertical temperature profiles. However, the current vertical mixing scheme in CLM requires an arbitrarily enlarged eddy diffusivity to enhance water mixing. The coupled CLM-KPP considers a boundary layer for eddy development, and in the lake interior water mixing is associated with internal wave activity and shear instability. We chose a lake in Arctic Alaska and a lake on the Tibetan Plateau to evaluate this improved lake model. Results demonstrated that CLM-KPP reproduced the observed lake mixing and significantly improved lake temperature simulations when compared to the original CLM. Our newly improved model better represents the transition between stratification and turnover. This improved lake model has great potential for reliable physical lake process predictions and better ecosystem services

Investigating the Morphological and Genetic Divergence of Arctic Char \u3ci\u3e(Salvelinus alpinus)\u3c/i\u3e Populations in Lakes of Arctic Alaska

Polymorphism facilitates coexistence of divergent morphs (e.g., phenotypes) of the same species by minimizing intraspecific competition, especially when resources are limiting. Arctic char (Salvelinus sp.) are a Holarctic fish often forming morphologically, and sometimes genetically, divergent morphs. In this study, we assessed the morphological and genetic diversity and divergence of 263 individuals from seven populations of arctic char with varying length-frequency distributions across two distinct groups of lakes in northern Alaska. Despite close geographic proximity, each lake group occurs on landscapes with different glacial ages and surface water connectivity, and thus was likely colonized by fishes at different times. Across lakes, a continuum of physical (e.g., lake area, maximum depth) and biological characteristics (e.g., primary productivity, fish density) exists, likely contributing to characteristics of present-day char populations. Although some lakes exhibit bimodal size distributions, using model-based clustering of morphometric traits corrected for allometry, we did not detect morphological differences within and across char populations. Genomic analyses using 15,934 SNPs obtained from genotyping by sequencing demonstrated differences among lake groups related to historical biogeography, but within lake groups and within individual lakes, genetic differentiation was not related to total body length. We used PERMANOVA to identify environmental and biological factors related to observed char size structure. Significant predictors included water transparency (i.e., a primary productivity proxy), char density (fish·ha-1), and lake group. Larger char occurred in lakes with greater primary production and lower char densities, suggesting less intraspecific competition and resource limitation. Thus, char populations in more productive and connected lakes may prove more stable to environmental changes, relative to food-limited and closed lakes, if lake productivity increases concomitantly. Our findings provide some of the first descriptions of genomic characteristics of char populations in arctic Alaska, and offer important consideration for the persistence of these populations for subsistence and conservation

Understanding the Effects of Climate Change via Disturbance on Pristine Arctic Lakes—Multitrophic Level Response and Recovery to a 12-Yr, Low-Level Fertilization Experiment

Effects of climate change-driven disturbance on lake ecosystems can be subtle; indirect effects include increased nutrient loading that could impact ecosystem function. We designed a low-level fertilization experiment to mimic persistent, climate change-driven disturbances (deeper thaw, greater weathering, or thermokarst failure) delivering nutrients to arctic lakes. We measured responses of pelagic trophic levels over 12 yr in a fertilized deep lake with fish and a shallow fishless lake, compared to paired reference lakes, and monitored recovery for 6 yr. Relative to prefertilization in the deep lake, we observed a maximum pelagic response in chl a (+201%), dissolved oxygen (DO, −43%), and zooplankton biomass (+88%) during the fertilization period (2001–2012). Other responses to fertilization, such as water transparency and fish relative abundance, were delayed, but both ultimately declined. Phyto- and zooplankton biomass and community composition shifted with fertilization. The effects of fertilization were less pronounced in the paired shallow lakes, because of a natural thermokarst failure likely impacting the reference lake. In the deep lake there was (a) moderate resistance to change in ecosystem functions at all trophic levels, (b) eventual responses were often nonlinear, and (c) postfertilization recovery (return) times were most rapid at the base of the food web (2–4 yr) while higher trophic levels failed to recover after 6 yr. The timing and magnitude of responses to fertilization in these arctic lakes were similar to responses in other lakes, suggesting indirect effects of climate change that modify nutrient inputs may affect many lakes in the future

Estimating Population Abundance with a Mixture of Physical Capture and PIT Tag Antenna Detection Data

The inclusion of passive interrogation antenna (PIA) detection data has promise to increase precision of population abundance estimates (Nˆ ). However, encounter probabilities are often higher for PIAs than for physical capture. If the difference is not accounted for, Nˆ may be biased. Using simulations, we estimated the magnitude of bias resulting from mixed capture and detection probabilities and evaluated potential solutions for removing the bias for closed capture models. Mixing physical capture and PIA detections (pdet) resulted in negative biases in Nˆ . However, using an individual covariate to model differences removed bias and improved precision. From a case study of fish making spawning migrations across a stream-wide PIA (pdet ≤ 0.9), the coefficient of variation (CV) of Nˆ declined 39%–82% when PIA data were included, and there was a dramatic reduction in time to detect a significant change in Nˆ . For a second case study, with modest pdet (≤0.2) using smaller PIAs, CV (Nˆ ) declined 4%–18%. Our method is applicable for estimating abundance for any situation where data are collected with methods having different capture–detection probabilities

Resilient and Rapid Recovery of Native Trout After Removal of a Non-Native Trout

While the importance of reducing impacts of non-native species is increasingly recognized in conservation, the feasibility of such actions is highly dependent upon several key uncertainties including stage of invasion, size of the ecosystem being restored, and magnitude of the restoration activity. Here, we present results of a multi-year, non-native brown trout (Salmo trutta) removal and native Bonneville cutthroat trout (Oncorhynchus clarkii utah) response to this removal in a small tributary in the Intermountain West, United States. We monitored trout for 10 years prior to the onset of eradication efforts, which included 2 years of mechanical removal followed by 2 years of chemical treatment. Cutthroat trout were then seeded with low numbers of both eggs and juvenile trout. We monitored demographics and estimated population growth rates and carrying capacities for cutthroat trout from long-term depletion estimate data, assuming logistic population growth. Following brown trout eradication and initial seeding efforts, cutthroat trout in this tributary have responded rapidly and have approached their estimated carrying capacity within 6 years. Population projections suggest a 95% probability that cutthroat trout will be at or above 90% of their carrying capacity within 10 years of the eradication of brown trout. Additionally, at least four age-classes are present including adults large enough to satisfy angling demand. These results demonstrate native trout species have substantial capacity to rapidly recover following removal of invasive species in otherwise minimally altered habitats. While tributaries such as like this study location are likely limited in extent individually, collectively they may serve such as source populations for larger connected systems. In such cases, these source populations may provide additional conservation potential through biotic resistance

Assessment of Potential Augmentation and Management Strategies for Razorback Sucker \u3cem\u3eXyrauchen texanus\u3c/em\u3e in Lake Mead and Grand Canyon: A 2021 Science Panel Summary

Razorback Sucker Xyrauchen texanus is a large-bodied, long-lived species endemic to the Colorado River Basin. This species historically ranged throughout the basin from the Colorado River delta in Mexico to Wyoming and Colorado. Currently, the species persists ,in a small portion of its historical range with the help of intensive management efforts including augmentation. Recruitment to adult life stages is extremely limited in the wild, but is documented consistently in Lake Mead. Research and monitoring efforts in Lake Mead are ongoing since 1996 and have recently expanded to include the Colorado River inflow area and portions of lower Grand Canyon. Despite evidence of recruitment, the current population size in Lake Mead and Grand Canyon is believed to be small (data) and susceptible to stochastic effects. This raised interest in the potential to augment the population to prevent loss of genetic diversity and increase abundance and distribution in general, as well as explore recruitment bottlenecks. To address critical uncertainties surrounding this management option and to brainstorm other potential options, a Planning Committee and Steering Committee made up of representatives of state (Arizona, Nevada), tribal (Hualapai Tribe, Navajo Nation), and federal (Bureau of Reclamation, National Park Service, and U.S. Fish and Wildlife Service) management agencies convened an Expert Science Panel (ESP; 2021), to consider augmentation and management strategies for Razorback Sucker in Lake Mead and Grand Canyon. The purpose of this report is to summarize those findings

BioTIME: A database of biodiversity time series for the Anthropocene.

MotivationThe BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables includedThe database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grainBioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).Time period and grainBioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurementBioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.Software format.csv and .SQL