What is the pollution limit? Comparing nutrient loads with thresholds to improve water quality in Lake Baiyangdian

Ecological thresholds are useful indicators for water quality managers to define limits to nutrient pollution. A common approach to estimating ecological thresholds is using critical nutrient loads. Critical nutrient loads are typically defined as the loads at which the phytoplankton chlorophyll-a exceeds a certain concentration. However, national policies, such as in China, use chemical indicators (nitrogen and phosphorus concentrations) rather than ecological indicators (phytoplankton chlorophyll-a) to assess water quality. In this study, we uniquely define the critical nutrient loads based on maximum allowable nutrient concentrations for lake Baiyangdian. We assess whether current and future nutrient loads in this lake comply with the Chinese Water Quality standards. To this end, we link two models (MARINA-Lakes and PCLake+). The PCLake+ model was applied to estimate the critical nutrient loads related to ecological thresholds for total nitrogen, total phosphorus and chlorophyll-a. The current (i.e., 2012) and future (i.e., 2050) nutrient loads were derived from the water quality MARINA-Lakes model. Nitrogen loads exceeded the nitrogen threshold in 2012. Phosphorus loads were below all ecological thresholds in 2012. Ecological thresholds are exceeded in 2050 with limited environmental policies, and urbanization may increase nutrient loads above the ecological thresholds in 2050. Recycling and reallocating animal manure is needed to avoid future water pollution in Lake Baiyangdian. Our study highlights the need for effective policies for clean water based on policy-relevant indicators.

Lichen-based critical loads for deposition of nitrogen and sulfur in US forests

Critical loads are thresholds of atmospheric deposition below which harmful ecological effects do not occur. Because lichens are sensitive to atmospheric deposition, lichen-based critical loads can foreshadow changes of other forest processes. Here, we derive critical loads of nitrogen (N) and sulfur (S) deposition for continental US and coastal Alaskan forests, based on nationally consistent lichen community surveys at 8855 sites. Across the eastern and western US ranges of 459 lichen species, each species' realized optimum was the N or S atmospheric deposition value at which it most frequently occurred. The mean of optima for all species at a site, weighted by their abundances, was defined as a community "airscore" indicative of species' collective responses to atmospheric deposition. To determine critical loads for adverse community compositional shifts, we then modeled changes in airscores as a function of deposition, climate and forest habitat predictors in nonparametric multiplicative regression. Critical loads, indicative of initial shifts from pollution-sensitive toward pollution-tolerant species, occurred at 1.5 kg N ha^-1 y^-1 and 2.7 kg S ha^-1 y^-1. Importantly, these critical loads remain constant under any climate regime nationwide, suggesting both simplicity and nationwide applicability. Our models predict that preventing excess N deposition of just 0.2-2.0 kg ha^-1 y^-1 in the next century could offset the detrimental effects of predicted climate warming on lichen communities. Because excess deposition and climate warming both harm the most ecologically influential species, keeping conditions below critical loads would sustain both forest ecosystem functioning and climate resilience.

Considering intervention intensity in habitat restoration planning: An application to Pacific salmon

Habitat restoration is a key strategy for recovering imperiled species, and planning habitat restoration activities cost effectively can help advance recovery objectives. Habitat restoration planning involves decisions about where and when to undertake restoration, and what type of restoration to undertake. This article focuses on decisions about the amount of restoration to undertake for a given type, location, and time, termed intervention intensity. A return on investment framework is developed for incorporating intervention intensity into habitat restoration planning. The framework is then applied in the context of planning habitat restoration for Pacific salmon recovery as a case study. Results showed that no single intervention type or location dominated, and several returns to scale relationships emerged across the candidate interventions. Scenarios that considered interventions across multiple intensities outperformed single-intensity scenarios in terms of total benefits and cost effectiveness. These findings highlight the usefulness of exploratory return on investment analysis for prioritizing habitat restoration interventions, and underscore the importance of systematically considering how much restoration to undertake, in addition to what to do and where.

Testing the applicability of random forest modeling to examine benthic foraminiferal responses to multiple environmental parameters

The main environmental variables controlling benthic foraminiferal distributions were identified and used to assess their influence on ecological indices developed as predictors of Ecological Quality Status (EcoQS) in marine ecosystems. Gradient forest and random forest models were applied to assess the predictive value of a selection of abiotic (environmental) and biotic (foraminifera) variables in a costal marine area in the central Adriatic Sea (Italy). This approach yields evidence that the predictor variables sand, silt, Pollution Load Index, and TN have the greatest influence on the distribution of benthic foraminifera in this area. In addition, we identify thresholds for the most important environmental variables that influence ecological indices. These findings contribute to efforts to determine how to best improve sediment quality and environmental stability for marine conservation. Further application of these approaches represents a useful tool for policymakers to survey the diversity of marine organisms and to improve the ability to protect and restore marine ecosystems by identifying predictors of diversity and identifying key thresholds in these predictors.

From a bat's perspective, protected riparian areas should be wider than defined by Brazilian laws

Riparian areas around streams are those areas in which biological communites are directly influenced by the stream. The size of protected riparian areas and their conservation has become a controversial topic after changes implemented in the Brazilian Forest Code (BFC): a set of laws that regulates the size of Permanent Protection Areas (PPA). Here, we investigate the influence of distance from water bodies on bat-species and guild composition in a lowland Amazonian rainforest. Our hypotheses were that bat assemblages would change depending on the distance to the water body and that the abundance of herbivorous bats (frugivorous and nectarivorous) would be greater in areas close to water. Bats were captured with mist-nets in 24 riparian and 25 non-riparian plots within a trail grid in an old-growth terra-firme forest, northeast of Manaus, Amazonas, Brazil. Each plot was sampled three times in a total of 7056 net-hours. We captured 1191 bats, comprising 51 species. We used model selection based on AIC (Akaike Information Criterion) to compare linear and piecewise regressions to estimate the ecological thresholds for different bat assemblages. Piecewise models with one breakpoint were more parsimonious than linear models for abundance data, and the species and guild composition of animalivorous and frugivorous bats. Animalivorous-bat abundance increased from the stream to about 181 m, and frugivorous-bat abundance decreased within 50 m of the stream. The patterns of guild abundance suggest that frugivorous bats may need greater access to streams than animalivorous bats. The most conservative model suggests that most of the variation in bat composition occurs close to the stream and extends to up 114 m from the banks. Therefore, the 30 m wide strip of riparian forest protected by Brazilian law would maintain a relatively small fraction of bat-species assemblages in Ducke Reserve, and is insufficient to represent most of the assemblage-composition variation within the riparian zone. The suggestion to reduce the width of the protected riparian zone from 30 to 15 m for streams smaller than 10 m wide, as is under discussion, would likely be prejudicial for bat assemblages.

Inductive reasoning and forecasting of population dynamics of Cylindrospermopsis raciborskii in three sub-tropical reservoirs by evolutionary computation

Seven-day-ahead forecasting models of Cylindrospermopsis raciborskii in three warm-monomictic and mesotrophic reservoirs in south-east Queensland have been developed by means of water quality data from 1999 to 2010 and the hybrid evolutionary algorithm HEA. Resulting models using all measured variables as inputs as well as models using electronically measurable variables only as inputs forecasted accurately timing of overgrowth of C. raciborskii and matched well high and low magnitudes of observed bloom events with 0.45≤r²>0.61 and 0.4≤r²>0.57, respectively. The models also revealed relationships and thresholds triggering bloom events that provide valuable information on synergism between water quality conditions and population dynamics of C. raciborskii. Best performing models based on using all measured variables as inputs indicated electrical conductivity (EC) within the range of 206-280mSm^-1 as threshold above which fast growth and high abundances of C. raciborskii have been observed for the three lakes. Best models based on electronically measurable variables for the Lakes Wivenhoe and Somerset indicated a water temperature (WT) range of 25.5-32.7°C within which fast growth and high abundances of C. raciborskii can be expected. By contrast the model for Lake Samsonvale highlighted a turbidity (TURB) level of 4.8 NTU as indicator for mass developments of C. raciborskii. Experiments with online measured water quality data of the Lake Wivenhoe from 2007 to 2010 resulted in predictive models with 0.61≤r²>0.65 whereby again similar levels of EC and WT have been discovered as thresholds for outgrowth of C. raciborskii. The highest validity of r²=0.75 for an in situ data-based model has been achieved after considering time lags for EC by 7 days and dissolved oxygen by 1 day. These time lags have been discovered by a systematic screening of all possible combinations of time lags between 0 and 10 days for all electronically measurable variables. The so-developed model performs seven-day-ahead forecasts and is currently implemented and tested for early warning of C. raciborskii blooms in the Wivenhoe reservoir.