Validation and comparison of geostatistical and spline models for spatial stream networks

Scientists need appropriate spatial-statistical models to account for the unique features of stream network data. Recent advances provide a growing methodological toolbox for modelling these data, but general-purpose statistical software has only recently emerged, with little information about when to use different approaches. We implemented a simulation study to evaluate and validate geostatistical models that use continuous distances, and penalised spline models that use a finite discrete approximation for stream networks. Data were simulated from the geostatistical model, with performance measured by empirical prediction and fixed effects estimation. We found that both models were comparable in terms of squared error, with a slight advantage for the geostatistical models. Generally, both methods were unbiased and had valid confidence intervals. The most marked differences were found for confidence intervals on fixed-effect parameter estimates, where, for small sample sizes, the spline models underestimated variance. However, the penalised spline models were always more computationally efficient, which may be important for real-time prediction and estimation. Thus, decisions about which method to use must be influenced by the size and format of the data set, in addition to the characteristics of the environmental process and the modelling goals

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises

Relating Spatial Patterns of Stream Metabolism to Distributions of Juveniles Salmonids at the River Network Scale

Understanding the factors that drive spatial patterns in stream ecosystem processes and the distribution of aquatic biota is important to effective management of these systems and the conservation of biota at the network scale. In this study, we conducted field surveys throughout an extensive river network in NE Oregon that supports diminishing populations of wild salmonids. We collected data on physical habitat, nutrient concentrations, biofilm standing stocks, stream metabolism (gross primary production [GPP] and ecosystem respiration [ER]), and ESA‐listed juvenile salmonid density from approximately 50 sites across two sub‐basins. Our goals were to (1) to evaluate network patterns in these metrics, and (2) determine network‐scale linkages among these metrics, thus providing inference of processes driving observed patterns. Ambient nitrate‐N and phosphate‐P concentrations were low across both sub‐basins (\u3c40 μg/L). Nitrate‐N decreased with watershed area in both sub‐basins, but phosphate‐P only decreased in one sub‐basin. These spatial patterns suggest co‐limitation in one sub‐basin but N limitation in the other; experimental results using nutrient diffusing substrates across both sub‐basins supported these predictions. Solar exposure, temperature, GPP, ER, and GPP:ER increased with watershed area, but biofilm Chl a and ash‐free dry mass (AFDM) did not. Spatial statistical network (SSN) models explained between 70% and 75% of the total variation in biofilm Chl a, AFDM, and GPP, but only 21% of the variation in ER. Temperature and nutrient concentrations were the most supported predictors of Chl aand AFDM standing stocks, but these variables explained little of the total variation compared to spatial autocorrelation. In contrast, solar exposure and temperature were the most supported variables explaining GPP, and these variables explained far more variation than autocorrelation. Solar exposure, temperature, and nutrient concentrations explained almost none of the variation in ER. Juvenile salmonids—a key management focus in these sub‐basins—were most abundant in cool stream sections where rates of GPP were low, suggesting temperature constraints on these species restrict their distribution to oligotrophic areas where energy production at the base of the food web may be limited

Haul-Out Behavior of Harbor Seals (Phoca vitulina) in Hood Canal, Washington

The goal of this study was to model haul-out behavior of harbor seals (Phoca vitulina) in the Hood Canal region of Washington State with respect to changes in physiological, environmental, and temporal covariates. Previous research has provided a solid understanding of seal haul-out behavior. Here, we expand on that work using a generalized linear mixed model (GLMM) with temporal autocorrelation and a large dataset. Our dataset included behavioral haul-out records from archival and VHF radio tag deployments on 25 individual seals representing 61,430 seal hours. A novel application for increased computational efficiency allowed us to examine this large dataset with a GLMM that appropriately accounts for temporal autocorellation. We found significant relationships with the covariates hour of day, day of year, minutes from high tide and year. Additionally, there was a significant effect of the interaction term hour of day : day of year. This interaction term demonstrated that seals are more likely to haul out during nighttime hours in August and September, but then switch to predominantly daylight haul-out patterns in October and November. We attribute this change in behavior to an effect of human disturbance levels. This study also examined a unique ecological event to determine the role of increased killer whale (Orcinus orca) predation on haul-out behavior. In 2003 and 2005 these harbor seals were exposed to unprecedented levels of killer whale predation and results show an overall increase in haul-out probability after exposure to killer whales. The outcome of this study will be integral to understanding any changes in population abundance as a result of increased killer whale predation

Combining geostatistical and biotic interaction modelling to predict amphibian refuges under crayfish invasion across dendritic stream networks

Biodiversity ResearchAim: Biological invasions are pervasive in freshwater ecosystems, often causing native species to contract into areas that remain largely free from invasive species impacts. Predicting the location of such ecological refuges is challenging, because they are shaped by the habitat requirements of native and invasive species, their biotic interactions, and the spatial and temporal invasion patterns. Here, we investigated the spatial distribution and environmental drivers of refuges from invasion in river systems, by considering biotic interactions in geostatistical models accounting for stream network topology. We focused on Mediterranean amphibians negatively impacted by the invasive crayfishes Procambarus clarkii and Pacifastacus leniusculus. Location: River Sabor, NE Portugal. Methods: We surveyed amphibians at 168 200-m stream stretches in 2015. Geostatistical models were used to relate the probabilities of occurrence of each species to environmental and biotic variables, while controlling for linear (Euclidean) and hydrologic spatial dependencies. Biotic interactions were specified using crayfish probabilities of occurrence extracted from previously developed geostatistical models. Models were used to map the distribution of potential refuges for the most common amphibian species, under current conditions and future scenarios of crayfish expansion. Results: Geostatistical models were produced for eight out of 10 species detected, of which five species were associated with lower stream orders and only one species with higher stream orders. Six species showed negative responses to one or both crayfish species, even after accounting for environmental effects and spatial dependencies. Most amphibian species were found to retain large expanses of potential habitat in stream headwaters, but current refuges will likely contract under plausible scenarios of crayfish expansion. Main conclusions: Incorporating biotic interactions in geostatistical modelling provides a practical and relatively simple approach to predict present and future distributions of refuges from biological invasion in stream networks. Using this approach, our study shows that stream headwaters are key amphibian refuges under invasion by alien crayfishinfo:eu-repo/semantics/publishedVersio

Increase in the flock prevalence of lameness in ewes is associated with a reduction in farmers using evidence-based management of prompt treatment : a longitudinal observational study of 154 English sheep flocks 2013–2015

Since 2006, farmers in England have received new recommendations on best practice to manage lameness in sheep through a range of knowledge exchange activities. The adoption of each recommendation varied, but in 2013 approximately 50% of farmers reported treating all lame sheep within 3 days of onset of lameness (prompt treatment), 41% did not practice routine foot trimming, 50% culled sheep that had been lame and 14% vaccinated against footrot; all recommended best practices. The aim of this study was to investigate the prevalence of lameness in ewes in England from 2013 to 2015 and to identify changes in practice to manage lameness between 2013 and 2015 and the population attributable fraction for these managements. A longitudinal study with a cohort of 154 English sheep farmers was run for three years, farmers completed questionnaires on lameness in their flock for the previous 12 months in 2013, 2014 and 2015. The geometric mean prevalence of lameness in ewes was 4.1% in 2015, significantly higher than 3.3% and 3.2% for the same 128 farmers who provided data in both 2013 and 2014. Between 2013 and 2015 there was a significant reduction in farmers practising prompt treatment (50.6%–28.6%) but an increase in not practising routine foot trimming (40.9%–79.2%), culling sheep that had been lame (49.4%–81.8%), and vaccinating against footrot (14.3%–29.2%). Not practising prompt treatment, ≥5% of sheep feet bleeding during routine foot trimming, vaccinating ewes for 5 years, not treating lame sheep promptly, ≥5% of sheep feet bleeding during routine foot trimming, and mixing of flocks were 34.5%, 25.3%, 2.9% and 2.4%. In 2013, when 50% of farmers used prompt treatment, the PAF for not using prompt treatment was only 13.3%. We conclude that the change in practice by these farmers towards flock-level managements and a reduction in individual prompt treatment of lame sheep negatively impacted the prevalence of lameness in sheep. This change occurred despite the evidence that prompt treatment of lame sheep is highly effective at reducing the prevalence of lameness in sheep flocks and is an example of cognitive dissonance

The european water framework directive facing current challenges: recommendations for a more efficient biological assessment of inland surface waters

High quality water is vital for human life, and ensuring its availability is a basic requirement and a major societal aim. The Water Framework Directive (WFD; 2000/60/EC) is a key piece of legislation for the protection and sustainable use of water in the European Union. In this work we briefly review the WFD directive and the current status of European inland surface waters. Additionally, we summarize major challenges and threats for the biological assessment of inland surface waters under climate change effects and invasion by alien species, and highlight the emerging tools and approaches that might help improve biological assessments, including molecular indices based on environmental DNA (eDNA), to new data from the Earth Observation programmes, and data-sharing platforms. Finally, we present recommendations to improve monitoring systems and assessments in the context of the WFD. Developments in this field may increase the likelihood of assuring high quality water for societyFRESHING Project funded by the Portuguese Foundation for Science and Technology (FCT) and COMPETE (PTDC/AAG-MAA/ 2261/2014 – POCI-01-0145-FEDER-356 016824). AFF, AGR, and JPR were supported by FRESHING. FMSM was supported by FCT grant SFRH/BD/104703/2014. MJF was supported by the strategic project UID/MAR/04292/2013 granted to MAR