Compounding Fire Disturbance History Encourages Coast Redwood (Sequoia sempervirens) Regeneration and Community Dominance

Disturbance is fundamental to forest ecosystem function and overall health, but climate change is likely to increase both disturbance frequency and intensity in the future. Forests subject to increasingly frequent and intense disturbances are more likely to experience compounding disturbance effects. Compounding disturbances may exert unpredicted, non-additive stresses on ecosystems, leading to novel conditions that may exceed the capacity for local species to survive and regenerate. I further hypothesize that compounding disturbances could create conditions misaligned with species’ adaptations by altering physical and chemical growing conditions in forest soils, affecting forest composition, structure, and, subsequently, function for many years following disturbance. A better understanding of these remnant effects will be essential to managing and conserving coast redwood forests, which are projected to see increased frequency of fire under future climate scenarios. My objectives in this study were to quantify the effects of time-since-fire and single vs. compounding disturbances on coast redwood forest structure, composition, and regeneration dynamics and to evaluate the effects of abiotic soil qualities on post-fire regeneration. I mapped and sampled coast redwood forests burned in 1985, both 1985 and 1999, 2008, and 2013; modeled regeneration as a function of burn history, understory light, and post-fire nutrient levels; and tested redwood seed regeneration in post-fire soils in a greenhouse experiment. Forest structure, composition, and regeneration following compounding disturbance were most similar to the homogenous, redwood-dominated forest of the recent 2013 burn. There were no unique effects of compounding disturbance on soil nutrient levels, although variations in nutrient levels generally followed patterns seen in previous studies. Soil nitrate was positively associated with coast redwood regeneration levels, showing that soil nutrients may be influential in regeneration processes following disturbance. Time since burn and single burn histories were negatively associated with regeneration levels in the field, and there were no differences in seed germination in the greenhouse between soils from different fire histories. Increases in coast redwood forest dominance accompanied declines in bay laurel and tanoak presence, indicating a shift in post-fire forest structure and composition resulting from compounding disturbance. These results illustrate a complex relationship between regeneration dynamics, post-fire soil quality, and disturbance histories. Forest homogenization from compounding disturbances may have negative implications for ecosystem services and overall function if compounding disturbances are more frequent as predicted under future climate conditions

A unified dataset of colocated sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia)

Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world’s most ancient, biodiverse, and voluminous freshwater lake, has been experiencing localized sewage pollution from lakeside settlements. Nearby increasing filamentous algal abundance suggests benthic communities are responding to localized pollution. We surveyed 40-km of Lake Baikal’s southwestern shoreline from 19 to 23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics, with colocated periphyton, macroinvertebrate, stable isotope, and fatty acid samplings. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage reuse. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset’s 150+ variables. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales

Effects of spatially heterogeneous lakeside development on nearshore biotic communities in a large, deep, oligotrophic lake

Sewage released from lakeside development can reshape ecological communities. Nearshore periphyton can rapidly assimilate sewage-associated nutrients, leading to increases of filamentous algal abundance, thus altering both food abundance and quality for grazers. In Lake Baikal, a large, ultra-oligotrophic, remote lake in Siberia, filamentous algal abundance has increased near lakeside developments, and localized sewage input is the suspected cause. These shifts are of particular interest in Lake Baikal, where endemic littoral biodiversity is high, lakeside settlements are mostly small, tourism is relatively high (~1.2 million visitors annually), and settlements are separated by large tracts of undisturbed shoreline, enabling investigation of heterogeneity and gradients of disturbance. We surveyed sites along 40 km of Baikal’s southwestern shore for sewage indicators—pharmaceuticals and personal care products (PPCPs) and microplastics—as well as periphyton and macroinvertebrate abundance and indicators of food web structure (stable isotopes and fatty acids). Summed PPCP concentrations were spatially related to lakeside development. As predicted, lakeside development was associated with more filamentous algae and lower abundance of sewagesensitive mollusks. Periphyton and macroinvertebrate stable isotopes and essential fatty acids suggested that food web structure otherwise remained similar across sites; yet, the invariance of amphipod fatty acid composition, relative to periphyton, suggested that grazers adjust behavior or metabolism to compensate for different periphyton assemblages. Our results demonstrate that even low levels of human disturbance can result in spatial heterogeneity of nearshore ecological responses, with potential for changing trophic interactions that propagate through the food web

A unified dataset of colocated sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia)

Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world’s most ancient, biodiverse, and voluminous freshwater lake, has been experiencing localized sewage pollution from lakeside settlements. Nearby increasing filamentous algal abundance suggests benthic communities are responding to localized pollution. We surveyed 40-km of Lake Baikal’s southwestern shoreline from 19 to 23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics, with colocated periphyton, macroinvertebrate, stable isotope, and fatty acid samplings. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage reuse. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset’s 150+ variables. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales

targets_ecology_minimal

A worked example for ecologists learning to use the targets package for

Winter and summer storms modify chlorophyll relationships with nutrients in seasonally ice‐covered lakes

Abstract At broad spatial scales, primary productivity in lakes is known to increase in concert with nutrients, and variables that may disrupt or modify the tight coupling of nutrients and algae are of increasing interest, particularly for those shifting with climate change. Storms may disrupt algae–nutrient relationships, but the expected effects differ between winter and summer seasons, particularly for seasonally ice‐covered lakes. In winter, storms can dramatically change the under‐ice light environment, creating light limitation that disrupts algae–nutrient relationships. Further, storms can bring both snow that blocks light and also wind that blows snow off of ice. In open water conditions, storms may promote turbulence and external nutrient loading. Here, we test the hypotheses that winter and summer storms differentially affect algae–nutrient relationships across 84 seasonally ice‐covered lakes included in the Ecology Under Lake Ice dataset. While nutrients explained most of the variation in chlorophyll across these lakes, we found that secondary drivers differed between seasons. Under‐ice chlorophyll was higher under a variety of precipitation and wind conditions that tend to promote snow‐free clear ice, highlighting the importance of light as a limiting factor for algal growth during winter. In summer, higher water temperatures and storms corresponded with higher chlorophyll. Our study suggests that examining ice‐covered lakes in a gradient from the perennial ice cover of the poles to the intermittent ice cover of lower latitudes would yield key information on the shifts in light and nutrient limitation that control algal biomass

Improving ecological data science with workflow management software

Abstract Pressing environmental research questions demand the integration of increasingly diverse and large‐scale ecological datasets as well as complex analytical methods, which require specialized tools and resources. Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor‐ and time‐intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies. Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with the targets r package to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers. Although WMS requires familiarity with function‐oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales

PPCPs in Urban Pollinators

Code and data for Meyer et al. "Identifying drivers of sewage-associated human pollutants in pollinators across urban landscapes". This project is meant to serve as a living repository for this project, so that the data can be repurposed beyond their original research questions

The global lake area, climate, and population dataset

An increasing population in conjunction with a changing climate necessitates a detailed understanding of water abundance at multiple spatial and temporal scales. Remote sensing has provided massive data volumes to track fluctuations in water quantity, yet contextualizing water abundance with other local, regional, and global trends remains challenging by often requiring large computational resources to combine multiple data sources into analytically-friendly formats. To bridge this gap and facilitate future freshwater research opportunities, we harmonized existing global datasets to create the Global Lake area, Climate, and Population (GLCP) dataset. The GLCP is a compilation of lake surface area for 1.42 + million lakes and reservoirs of at least 10 ha in size from 1995 to 2015 with co-located basin-level temperature, precipitation, and population data. The GLCP was created with FAIR (findable, accessible, interoperable, reusable) data principles in mind and retains unique identifiers from parent datasets to expedite interoperability. The GLCP offers critical data for basic and applied investigations of lake surface area and water quantity at local, regional, and global scales

Flathead Lake Nearshore Communities

This OSF page is to help all collaborators for the Flathead Lake Field season and associated dose-response experiments share data, metadata, and references through Zotero. Please contact the project lead, Michael Meyer michael.f.meyerATwsuDOTedu for questions, comments, or concerns