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Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.

 

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.

 

Abstract The quality of lake ice is of uppermost importance for ice safety and under-ice ecology, but its temporal and spatial variability is largely unknown. Here we conducted a coordinated lake ice quality sampling campaign across the Northern Hemisphere during one of the warmest winters since 1880 and show that lake ice during 2020/2021 commonly consisted of unstable white ice, at times contributing up to 100% to the total ice thickness. We observed that white ice increased over the winter season, becoming thickest and constituting the largest proportion of the ice layer towards the end of the ice cover season when fatal winter drownings occur most often and light limits the growth and reproduction of primary producers. We attribute the dominance of white ice before ice-off to air temperatures varying around the freezing point, a condition which occurs more frequently during warmer winters. Thus, under continued global warming, the prevalence of white ice is likely to substantially increase during the critical period before ice-off, for which we adjusted commonly used equations for human ice safety and light transmittance through ice. 

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 thetargets rpackage 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.

 

Abstract In recent decades, lakes have experienced unprecedented ice loss with widespread ramifications for winter ecological processes. The rapid loss of ice, resurgence of winter biology, and proliferation of remote sensing technologies, presents a unique opportunity to integrate disciplines to further understand the broad spatial and temporal patterns in ice loss and its consequences. Here, we summarize ice phenology records for 78 lakes in 12 countries across North America, Europe, and Asia to permit the inclusion and harmonization of in situ ice phenology observations in future interdisciplinary studies. These ice records represent some of the longest climate observations directly collected by people. We highlight the importance of applying the same definition of ice-on and ice-off within a lake across the time-series, regardless of how the ice is observed, to broaden our understanding of ice loss across vast spatial and temporal scales. 

Abstract One of the most important physical characteristics driving lifecycle events in lakes is stratification. Already subtle variations in the timing of stratification onset and break-up (phenology) are known to have major ecological effects, mainly by determining the availability of light, nutrients, carbon and oxygen to organisms. Despite its ecological importance, historic and future global changes in stratification phenology are unknown. Here, we used a lake-climate model ensemble and long-term observational data, to investigate changes in lake stratification phenology across the Northern Hemisphere from 1901 to 2099. Under the high-greenhouse-gas-emission scenario, stratification will begin 22.0 ± 7.0 days earlier and end 11.3 ± 4.7 days later by the end of this century. It is very likely that this 33.3 ± 11.7 day prolongation in stratification will accelerate lake deoxygenation with subsequent effects on nutrient mineralization and phosphorus release from lake sediments. Further misalignment of lifecycle events, with possible irreversible changes for lake ecosystems, is also likely. 

Abstract Frozen winters define life at high latitudes and altitudes. However, recent, rapid changes in winter conditions have highlighted our relatively poor understanding of ecosystem function in winter relative to other seasons. Winter ecological processes can affect reproduction, growth, survival, and fitness, whereas processes that occur during other seasons, such as summer production, mediate how organisms fare in winter. As interest grows in winter ecology, there is a need to clearly provide a thought-provoking framework for defining winter and the pathways through which it affects organisms. In the present article, we present nine maxims (concise expressions of a fundamentally held principle or truth) for winter ecology, drawing from the perspectives of scientists with diverse expertise. We describe winter as being frozen, cold, dark, snowy, less productive, variable, and deadly. Therefore, the implications of winter impacts on wildlife are striking for resource managers and conservation practitioners. Our final, overarching maxim, “winter is changing,” is a call to action to address the need for immediate study of the ecological implications of rapidly changing winters.