Summary 1. Existing methods for identifying ecological community thresholds are designed for univariate indicators or multivariate dimension‐reduction of community structure. Most are insensitive to responses of individual taxa with low occurrence frequencies or highly variable abundances, properties of the vast majority of taxa in community data sets. We introduce Threshold Indicator Taxa ANalysis (TITAN) to detect changes in taxa distributions along an environmental gradient over space or time, and assess synchrony among taxa change points as evidence for community thresholds. 2. TITAN uses indicator species scores to integrate occurrence, abundance and directionality of taxa responses. It identifies the optimum value of a continuous variable, x, that partitions sample units while maximizing taxon‐specific scores. Indicator z scores standardize original scores relative to the mean and SD of permuted samples along x, thereby emphasizing the relative magnitude of change and increasing the contributions of taxa with low occurrence frequencies but high sensitivity to the gradient. TITAN distinguishes negative (z−) and positive (z+) taxa responses and tracks cumulative responses of declining [sum(z−)] and increasing [sum(z+)] taxa in the community. Bootstrapping is used to estimate indicator reliability and purity as well as uncertainty around the location of individual taxa and community change points. 3. Using two simulated data sets, TITAN correctly identified taxon and community thresholds in more than 99% of 500 unique versions of each simulation. In contrast, multivariate change‐point analysis did not distinguish directional taxa responses, resulting in much wider confidence intervals that in one instance failed to capture thresholds in 38% of the iterations. 4. Retrospective analysis of macroinvertebrate community response to a phosphorus gradient supported previous threshold estimates, although TITAN produced narrower confidence limits and revealed that several taxa declined at lower levels of phosphorus. Re‐analysis of macroinvertebrate responses to an urbanization gradient illustrated disparate change points for declining (0·81–3·3% urban land) and increasing (6·8–26·6%) taxa, whereas the published threshold estimate (20–30%) missed the declining‐taxa threshold because it could not distinguish their synchronous decline from the gradual increase in ubiquitous taxa. 5. Synthesis and applications. By deconstructing communities to assess synchrony of taxon‐specific change points, TITAN provides a sensitive and precise alternative to existing methods for assessing community thresholds. TITAN has tremendous potential to inform conservation of rare or threatened species, develop species sensitivity models, identify reference conditions and to support development of numerical regulatory criteria.

Watershed land cover is widely used as a predictor of stream‐ecosystem condition. However, numerous spatial factors can confound the interpretation of correlative analyses between land cover and stream indicators, particularly at broad spatial scales. We used a stream‐monitoring data set collected from the Coastal Plain of Maryland, USA to address analytical challenges presented by (1) collinearity of land‐cover class percentages, (2) spatial autocorrelation of land cover and stream data, (3) intercorrelations among and spatial autocorrelation within abiotic intermediaries that link land cover to stream biota, and (4) spatial arrangement of land cover within watersheds. We focused on two commonly measured stream indicators, nitrate‐nitrogen (NO3–N) and macroinvertebrate assemblages, to evaluate how different spatial considerations may influence results. Partial correlation analysis of land‐cover percentages revealed that simple correlations described relationships that could not be separated from the effects of other land‐cover classes or relationships that changed substantially when the influences of other land‐cover classes were taken into account. Partial Mantel tests showed that all land‐cover percentages were spatially autocorrelated, and this spatial phenomenon accounted for much of the variation in macroinvertebrate assemblages that could naively be attributed to certain classes (e.g., percentage cropland). We extended our use of partial Mantel tests into a path‐analytical framework and identified several independent pathways between percentage developed land and in‐stream measurements after factoring out spatial autocorrelation and other confounding variables; however, under these conditions, percentage cropland was only linked to nitrate‐N. Further analyses revealed that spatial arrangement of land cover, as measured by areal buffers and distance weighting, influenced the amount of developed land, resulting in a threshold change in macroinvertebrate‐assemblage composition. Moreover, distance‐weighted percentage cropland improved predictions of stream nitrate‐N concentrations in small watersheds, but not in medium or large ones. Collectively, this series of analyses clarified the magnitude and critical scales of effects of different land‐cover classes on Coastal Plain stream ecosystems and may serve as an analytical framework for other studies. Our results suggest that greater emphasis should be placed on these important spatial considerations; otherwise, we risk obscuring the relationships between watershed land cover and the condition of stream ecosystems.

Surface coal mining is the dominant form of land cover change in Central Appalachia, yet the extent to which surface coal mine runoff is polluting regional rivers is currently unknown. We mapped surface mining from 1976 to 2005 for a 19,581 km(2) area of southern West Virginia and linked these maps with water quality and biological data for 223 streams. The extent of surface mining within catchments is highly correlated with the ionic strength and sulfate concentrations of receiving streams. Generalized additive models were used to estimate the amount of watershed mining, stream ionic strength, or sulfate concentrations beyond which biological impairment (based on state biocriteria) is likely. We find this threshold is reached once surface coal mines occupy >5.4% of their contributing watershed area, ionic strength exceeds 308 μS cm(-1), or sulfate concentrations exceed 50 mg L(-1). Significant losses of many intolerant macroinvertebrate taxa occur when as little as 2.2% of contributing catchments are mined. As of 2005, 5% of the land area of southern WV was converted to surface mines, 6% of regional streams were buried in valley fills, and 22% of the regional stream network length drained watersheds with >5.4% of their surface area converted to mines.

A nonparametric method and a Bayesian hierarchical modeling method are proposed in this paper for the detection of environmental thresholds. The nonparametric method is based on the reduction of deviance, while the Bayesian method is based on the change in the response variable distribution parameters. Both methods are tested using macroinvertebrate composition data from a mesocosm experiment conducted in the Everglades wetlands, where phosphorus is the limiting nutrient. Using the percent of phosphorus tolerant species and a dissimilarity index as the response variables, both methods resulted in a similar and well-defined TP concentration threshold, with a distribution function that can be used to determine the probability of exceeding the threshold.