Ecosystem managers face a difficult decision when managing invasive species. If they use aggressive practices to reduce invader abundances, they will likely reduce invaders' competitive impacts on natives. But it is often difficult or impossible to reduce invaders without damaging natives. So a critical question becomes: Which is worse for native biota, invaders or things done to control invaders? We attempted to answer this question for a common scenario. We studied several grassland natives exhibiting long-term coexistence with an invader and asked how aggressive management (herbicide use) affected the natives. Whether or not grazing was excluded, one-time herbicide use made two native forbs exceedingly rare for our entire 16-year study period. Herbicide also made several other native forbs rare, but only when grazing was excluded, and there is evidence that the dominant invader became more abundant in response to the decreases in native-forb abundances. Throughout the world, terrestrial and aquatic ecosystems are receiving herbicide applications for exotic-species control. Some of the applications are doubtless warranted because they target small invader patches or larger areas with virtually no remaining natives. However, other herbicide applications occur where large native populations occur, and our data suggest that these applications can be ill advised. Our cautionary tale is told using an herbicide-treated grassland, but our results should be considered wherever invasive-species management damages native species.

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Questions: How similar are solutions of eight commonly used vegetation classification methods? Which classification methods are most effective according to classification validity evaluators? How do evaluators with different optimality criteria differ in their assessments of classification efficacy? In particular, do evaluators which use geometric criteria (e.g. cluster compactness) and non‐geometric evaluators (which rely on diagnostic species) offer similar classification evaluations? Methods: We analysed classifications of two vegetation data‐sets produced by eight classification methods. Classification solutions were assessed with five geometric and four non‐geometric internal evaluators. We formally introduce three new evaluators: PARTANA, an intuitive variation on evaluators which use the ratio of within/between cluster dissimilarity as the optimality criterion, an adaptation of Morisita's index of niche overlap, and ISAMIC, an algorithm which measures the degree to which species are either always present or always absent within clusters. Results and Conclusions: 1. With the exception of single linkage hierarchical clustering, classifications resulting from the eight methods were often similar. 2. Although evaluators varied in their assessment of best overall classification method, they generally favored three hierarchical agglomerative clustering strategies: flexible beta (β=– 0.25), average linkage, and Ward's linkage. 3. Among introduced evaluators PARTANA appears to be an effective geometric strategy which provides assessments similar to C‐index and Gamma evaluators. Non‐geometric evaluators ISAMIC and Morisita's index demonstrate a strong bias for single linkage solutions. 4. Because non‐geometric criteria are of interest to phytosociologists there is a strong need for their continued development for use with vegetation classifications.

Increasing aridity and drought severity forecast for many land areas could reduce the land carbon (C) sink. However, with limited long-term direct measures, it is difficult to distinguish direct drying effects from counter effects of CO2 enrichment and nitrogen (N) deposition. Here, we document a >50% decline in production of a native C3 grassland over four decades and assign the forcing and timing to increasing aridity and specifically to declining late-summer rainfall. Analysis of C and N stable isotopes in biomass suggests that enhanced water use efficiency via CO2 enrichment may have slightly ameliorated the productivity decline but that changes in N had no effects. Identical declines in a long-term snow-addition experiment definitively identified increasing late-summer dryness as the cause. Our results demonstrate lasting consequences of recent climate change on grassland production and underscore the importance of understanding past climate–ecosystem coupling to predicting future responses to changing climate.