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Abstract Abundance-weighted averaging is a simple and common method for estimating taxon preferences (optima) for phosphorus (P) and other environmental drivers of freshwater-ecosystem health. These optima can then be used to develop transfer functions to infer current and/or past environmental conditions of aquatic ecosystems in water-quality assessments and/or paleolimnological studies. However, estimates of species’ environmental preferences are influenced by the sample distribution and length of environmental gradients, which can differ between datasets used to develop and apply a transfer function. Here, we introduce a subsampling method to ensure a uniform and comparable distribution of samples along a P gradient in two similar ecosystems: the Everglades Protection Areas (EPA) and Big Cypress National Preserve (BICY) in South Florida, USA. Diatom optima were estimated for both wetlands using weighted averaging of untransformed and log-transformed periphyton mat total phosphorus (mat TP) values from the original datasets. We compared these estimates to those derived from random subsets of the original datasets. These subsets, referred to as “SUD” datasets, were created to ensure a uniform distribution of mat TP values along the gradient (both untransformed and log-transformed). We found that diatom assemblages in BICY and EPA were similar, dominated by taxa indicating oligotrophic conditions, and strongly influenced by P gradients. However, the original BICY datasets contained more samples with elevated mat TP concentrations than the EPA datasets, introducing a mathematical bias and resulting in a higher abundance of taxa with high mat TP optima in BICY. The weighted averaged mat TP optima of BICY and EPA taxa were positively correlated across all four dataset types, with taxa optima of SUD datasets exhibiting higher correlations than in the original datasets. Equalizing the mat TP sample distribution in the two datasets confirmed consistent mat TP estimates for diatom taxa between the two wetland complexes and improved transfer-function performance. Our findings suggest that diatom environmental preferences may be more reliable across regional scales than previously suggested and support the application of models developed in one region to another nearby region if environmental gradient lengths are equalized and data distribution along gradients is uniform. 

ABSTRACT Summer programs are a powerful educational tool for increasing student interest in science, technology, engineering, and mathematics (STEM) careers. However, barriers such as lack of awareness, transportation challenges, and financial constraints can hinder participation. This study examinesWater Dawgs, a paid summer initiative designed to provide high school students with hands‐on freshwater science education while ensuring accessibility for all interested students. UsingWater Dawgsas a case study, we explore how proactive planning and budgeting can help mitigate these participation barriers.Water Dawgssuccessfully engaged 16 participants, and survey results indicate increased self‐efficacy in STEM as well as greater awareness of how environmental science impacts daily life and career opportunities. We identify five key barriers—information gaps, resource deficiencies, transportation disparities, food insecurity, and economic limitations—and offer practical recommendations for addressing them through proactive planning and budgeting of direct costs. Strategies include planning and engagement well in advance of the event, allocating direct expenditures to compensate teacher partners and participants for their work, providing all necessary supplies for both classroom and field activities, offering transportation options for all participants, and ensuring access to meals. Our case study highlights the importance of thoughtful program planning and budget development that fully accounts for direct costs associated with removing barriers, making STEM summer programs an option for all interested students. 

{"Abstract":["Environmental and diatom data were collected from sites in the Big Cypress National Preserve (BICY) by the South Florida/Caribbean Inventory and Monitoring Network of the National Park Service and from sites in the Everglades Protection Area (EPA) as part of the Monitoring and Assessment Program of the Comprehensive Everglades Restoration Plan. Samples from years 2012, 2013, 2019, 2019, and 2020 are included in this dataset. Environmental data include drier variables that have been found to influence diatom assemblage composition in the greater Everglades ecosystem, including periphyton mat total phosphorus (a proxy for phosphorus in the environment), water column pH, water column conductivity, water depth, days since last dry, and hydroperiod. Diatom data include diatom species composition as percent relative abundances. Code included is pertinent to the methods described in "Robust species optima estimates from non-uniformly sampled environmental gradients" by Solomon et al. 2025, Journal of Paleolimnology."]} 

The Association for the Sciences of Limnology and Oceanography (ASLO) sponsors Eco-DAS, which is now in its 30th year. The program aims to unite aquatic scientists, develop diverse collaborations, and provide professional development training opportunities with guests from federal agencies, nonprofits, academia, tribal groups, and other workplaces (a previous iteration is summarized in Ghosh et al. 2022). Eco-DAS XV was one of the largest and most nationally diverse cohorts, including 37 early career aquatic scientists, 15 of whom were originally from 9 different countries outside the United States (Fig. 2). As the first cohort to meet in-person since the COVID-19 pandemic, Eco-DAS participants convened from 5 to 11 March 2023 to expand professional networks, create shared projects, and discuss areas of priority for the aquatic sciences. During the weeklong meeting, participants developed 46 proposal ideas, 16 of which will be further developed into projects and peer-reviewed manuscripts.