Do early warning indicators consistently predict nonlinear change in long-term ecological data?

1. Anthropogenic pressures, including climate change, are causing nonlinear changes in ecosystems globally. The development of reliable early warning indicators (EWIs) to predict these changes is vital for the adaptive management of ecosystems and the protection of biodiversity, natural capital and ecosystem services. Increased variance and autocorrelation are potential early warning indicators and can be readily estimated from ecological time series. Here, we undertook a comprehensive test of the consistency between early warning indicators and nonlinear abundance change across species, trophic levels and ecosystem types. 2. We tested whether long-term abundance time series of 55 taxa (126 data sets) across multiple trophic levels in marine and freshwater ecosystems showed (i) significant nonlinear change in abundance ‘turning points’ and (ii) significant increases in variance and autocorrelation (‘early warning indicators’). For each data set, we then quantified the prevalence of three cases: true positives (early warning indicators and associated turning point), false negatives (turning point but no associated early warning indicators) and false positives (early warning indicators but no turning point). 3. True positives were rare, representing only 9% (16 of 170) of cases using variance, and 13% (19 of 152) of cases using autocorrelation. False positives were more prevalent than false negatives (53% vs. 38% for variance; 47% vs. 40% for autocorrelation). False results were found in every decade and across all trophic levels and ecosystems. 4. Time series that contained true positives were uncommon (8% for variance; 6% for autocorrelation), with all but one time series also containing false classifications. Coherence between the types of early warning indicators was generally low with 43% of time series categorized differently based on variance compared to autocorrelation. 5. Synthesis and applications. Conservation management requires effective early warnings of ecosystem change using readily available data, and variance and autocorrelation in abundance data have been suggested as candidates. However, our study shows that they consistently fail to predict nonlinear change. For early warning indicators to be effective tools for preventative management of ecosystem change, we recommend that multivariate approaches of a suite of potential indicators are adopted, incorporating analyses of anthropogenic drivers and process-based understanding

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

The response of the rotifer community in Loch Leven, UK, to changes associated with a 60% reduction in phosphorus inputs from the catchment

Lakes across the world are suffering from anthropogenically induced nutrient enrichment problems and many attempts are being made to improve their water quality and ecosystem function. Most metrics that are being used to monitor recovery are based on relationships that have been established across a range of lakes. These may not respond quickly to in-lake changes in water quality when nutrient management strategies are put in place. This paper uses data routinely collected from Loch Leven, UK, to examine the immediate and longerterm responses of the rotifer community to a 60% reduction in phosphorus input from the catchment in the early 1990s. We conclude that changes in rotifer abundance and relative species composition are sensitive indicators of lake-specific changes in water quality, responding more quickly than more widely used metrics, such as total phosphorus and chlorophyll a concentrations. However, like all indicators of change, such indices must be used with care in situations where rotifer populations are subject to multiple stressors

Phosphorus partitioning in a shallow lake: implications for water quality management

This paper describes the seasonal partitioning of phosphorus (P) across the sediment–water interface in Loch Leven, Scotland, and discusses the implications for future lake management strategy with respect to recovery from eutrophication. In a 10-month survey, surface water total phosphorus (TP) concentrations were highest in late summer and lowest in early spring. In contrast, sediment TP concentrations were highest in mid-winter and lowest in late summer. Water discharge at the main outflow of the loch was highest when water-column TP was low and sediment TP high, and vice versa. Monthly sediment P uptake/release values showed significant cycling between the water-column and the sediment and showed seasonal variation in four release-sensitive P pools. Regulating the water level to increase flushing during sediment release periods and decrease flushing during uptake periods has the potential to significantly enhance the recovery of shallow lakes and reservoirs following historic nutrient loading