Joseph Stachelek

Sustainable computational science: the ReScience initiative

Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In the best case, authors may provide their source code as a compressed archive and they may feel confident their research is reproducible. But this is not exactly true. James Buckheit and David Donoho proposed more than two decades ago that an article about computational results is advertising, not scholarship. The actual scholarship is the full software environment, code, and data that produced the result. This implies new workflows, in particular in peer-reviews. Existing journals have been slow to adapt: source codes are rarely requested, hardly ever actually executed to check that they produce the results advertised in the article. ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research can be replicated from its description. To achieve this goal, the whole publishing chain is radically different from other traditional scientific journals. ReScience resides on GitHub where each new implementation of a computational study is made available together with comments, explanations, and software tests.

LAGOS-NE: a multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes

Abstract Understanding the factors that affect water quality and the ecological services provided by freshwater ecosystems is an urgent global environmental issue. Predicting how water quality will respond to global changes not only requires water quality data, but also information about the ecological context of individual water bodies across broad spatial extents. Because lake water quality is usually sampled in limited geographic regions, often for limited time periods, assessing the environmental controls of water quality requires compilation of many data sets across broad regions and across time into an integrated database. LAGOS-NE accomplishes this goal for lakes in the northeastern-most 17 US states. LAGOS-NE contains data for 51u2009101 lakes and reservoirs larger than 4 ha in 17 lake-rich US states. The database includes 3 data modules for: lake location and physical characteristics for all lakes; ecological context (i.e., the land use, geologic, climatic, and hydrologic setting of lakes) for all lakes; and in situ measurements of lake water quality for a subset of the lakes from the past 3 decades for approximately 2600–12u2009000 lakes depending on the variable. The database contains approximately 150u2009000 measures of total phosphorus, 200u2009000 measures of chlorophyll, and 900u2009000 measures of Secchi depth. The water quality data were compiled from 87 lake water quality data sets from federal, state, tribal, and non-profit agencies, university researchers, and citizen scientists. This database is one of the largest and most comprehensive databases of its type because it includes both in situ measurements and ecological context data. Because ecological context can be used to study a variety of other questions about lakes, streams, and wetlands, this database can also be used as the foundation for other studies of freshwaters at broad spatial and ecological scales.

Functional and Compositional Responses of Periphyton Mats to Simulated Saltwater Intrusion in the Southern Everglades

Periphyton plays key ecological roles in karstic, freshwater wetlands and is extremely sensitive to environmental change making it a powerful tool to detect saltwater intrusion into these vulnerable and valuable ecosystems. We conducted field mesocosm experiments in the Florida Everglades, USA to test the effects of saltwater intrusion on periphyton metabolism, nutrient content, and diatom species composition, and how these responses differ between mats from a freshwater versus a brackish marsh. Pulsed saltwater intrusion was simulated by dosing treatment chambers monthly with a brine solution for 15xa0months; control chambers were simultaneously dosed with site water. Periphyton from the freshwater marsh responded to a 1-ppt increase in surface water salinity with reduced productivity and decreased concentrations of total carbon, nitrogen, and phosphorus. These functional responses were accompanied by significant shifts in periphytic diatom assemblages. Periphyton mats at the brackish marsh were more functionally resilient to the saltwater treatment (~u20092xa0ppt above ambient), but nonetheless experienced significant shifts in diatom composition. These findings suggest that freshwater periphyton is negatively affected by small, short-term increases in salinity and that periphytic diatom assemblages, particularly at the brackish marsh, are a better metric of salinity increases compared with periphyton functional metrics due to functional redundancy. This research provides new and valuable information regarding periphyton dynamics in response to changing water sources in the southern Everglades that will allow us to extend the use of periphyton, and their diatom assemblages, as tools for environmental assessments related to saltwater intrusion.

lakemorpho : Calculating lake morphometry metrics in R

Metrics describing the shape and size of lakes, known as lake morphometry metrics, are important for any limnological study. In cases where a lake has long been the subject of study these data are often already collected and are openly available. Many other lakes have these data collected, but access is challenging as it is often stored on individual computers (or worse, in filing cabinets) and is available only to the primary investigators. The vast majority of lakes fall into a third category in which the data are not available. This makes broad scale modelling of lake ecology a challenge as some of the key information about in-lake processes are unavailable. While this valuable in situ information may be difficult to obtain, several national datasets exist that may be used to model and estimate lake morphometry. In particular, digital elevation models and hydrography have been shown to be predictive of several lake morphometry metrics. The R package lakemorpho has been developed to utilize these data and estimate the following morphometry metrics: surface area, shoreline length, major axis length, minor axis length, major and minor axis length ratio, shoreline development, maximum depth, mean depth, volume, maximum lake length, mean lake width, maximum lake width, and fetch. In this software tool article we describe the motivation behind developing lakemorpho, discuss the implementation in R, and describe the use of lakemorpho with an example of a typical use case.

Application of inverse path distance weighting for high-density spatial mapping of coastal water quality patterns

One of the primary goals of coastal water quality monitoring is to characterize spatial variation. Generally, this monitoring takes place at a limited number of fixed sampling points. The alternative sampling methodology explored in this paper involves high-density sampling from an on-board flow-through water analysis system (Dataflow). Dataflow (West Palm Beach, FL, USA) has the potential to provide better spatial resolution of water quality features because it generates many closely spaced (<10 m) measurements. Regardless of the measurement technique, parameter values at unsampled locations must be interpolated from nearby measurement points in order to generate a comprehensive picture of spatial variations. Standard Euclidean interpolations in coastal settings tend to yield inaccurate results because they extend through barriers in the landscape such as peninsulas, islands, and submerged banks. We recently developed a method for non-Euclidean interpolation by inverse path distance weighting (IPDW) in order to account for these barriers. The algorithms were implemented as part of an R package and made available from R repositories. The combination of IPDW with Dataflow provided more accurate estimates of salinity patterning relative to Euclidean inverse distance weighting (IDW). IPDW was notably more accurate than IDW in the presence of intense spatial gradients.