Understanding global ecological patterns and processes, from biogeochemical to biogeographical, requires broad‐scale macrosystems context for comparing and contrasting ecosystems. Climate gradients (precipitation and temperature) and other continental‐scale patterns shape freshwater environments due to their influences on terrestrial environments and their direct and indirect effects on the abiotic and biotic characteristics of lakes, streams, and wetlands. We combined literature review, analyses of open access data, and logical argument to assess abiotic and biotic characters of freshwater systems across gradients of latitude and elevation that drive precipitation, temperature, and other variability. We explored the predictive value of analyzing patterns in freshwater ecosystems at the global macrosystems scale. We found many patterns based on climate, particularly those dependent upon hydrologic characteristics and linked to characteristics of terrestrial biomes. For example, continental waters of dry areas will generally be widely dispersed and have higher probability of drying and network disconnection, greater temperatures, greater inorganic turbidity, greater salinity, and lower riparian canopy cover relative to areas with high precipitation. These factors will influence local community composition and ecosystem rates. Enough studies are now available at the continental or global scale to start to characterize patterns under a coherent conceptual framework, though considerable gaps exist in the tropics and less developed regions. We present illustrative global‐scale trends of abiotic, biotic, and anthropogenic impacts in freshwater ecosystems across gradients of precipitation and temperature to further understanding of broad‐scale trends and to aid prediction in the face of global change. We view freshwater systems as occurring across arrays of multiple gradients (including latitude, altitude, and precipitation) rather than areas with specific boundaries. While terrestrial biomes capture some variability along these gradients that influence freshwaters, other features such as, slope, geology, and historical glaciation also influence freshwaters. Our conceptual framework is not so much a single hypothesis as a way to logically characterize patterns in freshwaters at scales relevant to (1) evolutionary processes that give rise to freshwater biodiversity, (2) regulatory units that influence freshwater ecosystems, and (3) the current scope of anthropogenic impacts on freshwaters and the vital ecosystem services they provide.

Resident characteristics were the most important predictors for cardiovascular and central nervous system medication prescriptions of new and readmitted nursing home residents.

No abstract

We evaluated growth of Bluegill Lepomis macrochirus in 24 small Kansas impoundments to understand variability in populations statewide. We assigned ages to 1,323 Bluegill, and when combined, growth parameters using the Ogle–Isermann parameterization of the von Bertalanffy growth model were: L∞ = 228 mm, K = 0.25, and t152 = 3.10 y. Growth was variable among the 24 populations and t152 (time to reach 152 mm total length) ranged from 1.56 to 4.87 y. We selected four representative limnological variables (latitude, maximum depth, total nitrogen, and total phosphorus) and four representative catch variables (catch-per-effort [CPE] of Bluegill, proportional size distribution of 178-mm Bluegill, CPE of stock-length Largemouth Bass Micropterus salmoides, and CPE of Gizzard Shad Dorosoma cepedianum) to elucidate mechanisms that explained t152 in Bluegill populations. We fit all subset candidate models using the eight variables to predict t152. Top candidate models (corrected Akaike's information criterion scores within two units of the most parsimonious model) comprised a confidence model set, and we used model-weighted averaging to calculate parameter estimates with 95% confidence intervals for each independent variable present in the confidence model set to develop a single explanatory model. The final model suggested that Bluegill size structure, latitude, and CPE of stock-length Largemouth Bass affected Bluegill growth, whereas a smaller effect was attributed to CPE of Gizzard Shad. Combined, these variables explained 40% of variation in observed Bluegill growth rate. Results from this study summarize Bluegill growth in Kansas and highlight variation in growth rates across small impoundments. Further, they suggest that Bluegill size structure, latitude, and relative abundance of stock-length Largemouth Bass are important factors regulating Bluegill growth in small Kansas impoundments.