Ostracods are important members of the benthos and littoral communities of lake ecosystems. Ostracods respond to hydrochemistry (water chemistry) which is influenced by climatic factors such as water balance, temperature, and chemicals in rainfall runoff from the land. Thus, at local scales, environmental preferences of ostracods and characteristics of lakes are used to infer changes in climate, hydrology, and erosion of lake catchments. This study addresses potential drivers of ostracod community structure and biodiversity at multiple spatial scales using NMS, CART Ò , and multiple regression models. We identified 23 ostracod species from 12 lake sites. Lake area, maximum depth, spring conductivity, chlorophyll a, pH, dissolved oxygen, sedimentary carbonate, and organic matter all influence ostracod community structure based on our NMS. Based on regression analysis, lake depth, chlorophyll a, and total dissolved solids best explained ostracod richness and abundance. Land uses are also important community structuring elements that varied with scale; locally and regionally agriculture, wetlands, and grasslands were important. Nationally, using regression tree analysis of lakes sites in the North American Non-marine ostracod database (NANODe), row-crop agriculture was the most important predictor of biodiversity. Low agriculture corresponded to low species richness but greater landscape heterogeneity produced sites of high ostracod richness.