Quantifying Relationships Among Phosphorus, Agriculture, and Lake Depth at an Inter-Regional Scale

To date, studies examining the impact of agricul-ture on freshwater systems have been spatially confined (that is, single drainage basin or regional level). Across regions, there are considerable dif-ferences in a number of factors, including geology, catchment morphometry, and hydrology that affect water quality. Given this heterogeneity, it is un-known whether agricultural activities have a per-vasive impact on lake trophic state across large spatial scales. To address this issue, we tested whether the proportion of agricultural land in a catchment ( % Agr) could explain a significant portion of the variation in lake water quality at a broad inter-regional scale. As shallow, productive systems have been shown to be particularly sus-ceptible to eutrophication, we further investigated how lake mean depth modulates the relationship between % Agr and lake total phosphorus (TP) concentration. We applied both traditional meta-analytic techniques and more sophisticated linear mixed-effects models to a dataset of 358 temperate lakes that spanned an extensive spatial gradient (5E to 73W) to address these issues. With meta-analytical techniques we detected an across-study correlation between TP and % Agr of 0.53 (one-tailed P-value = 0.021). The across-study correla-tion coefficient between TP and mean depth was substantially lower (r =)0.38; P = 0.057). With linear mixed-effects modeling, we detected among-study variability, which arises from differences in pre-impact (background) lake trophic state and in the relationship between lake mean depth and lake TP. To our knowledge, this is the first quantitative synthesis that defines the influence of agriculture on lake water quality at such a broad spatial scale. Syntheses such as these are required to define the global relationship between agricultural land-use and water quality. Key words: agriculture; non-point source; water quality; phosphorus; eutrophication; morphome-try; meta-analysis; mixed-effects model