Climatic and Catchment-Scale Predictors of Chinese Stream Insect Richness Differ between Taxonomic Groups

Where does land use matter most? Contrasting land use effects on river quality at different spatial scales

Understanding the influence of land-use activities on river quality has been a key focus of river monitoring programs worldwide. However, defining which land-use spatial scale is relevant remains elusive. In this study, therefore, we contrasted the influence of land use on river quality using three types of land-use estimators, namely circular buffers around a monitoring site, circular buffers upstream of the monitoring site and the entire watershed area upstream of the monitoring site. The land-use percentage compositions within the Usa-Kikuletwa River catchment in northeastern Tanzania were quantified using Landsat-8 satellite images with a maximum mapping resolution of 30 m. Redundancy analysis models and generalized linear models were used to evaluate the influence of land use on macroinvertebrate assemblages and physico-chemical water quality at different spatial scales in the dry and wet seasons. Overall, a substantial fraction of variation in physico-chemical water quality, macroinvertebrate taxon richness, Chao-1 and TARISS (Tanzania River Scoring System) score could be explained by land use of the entire watershed area upstream of the monitoring site in the dry and wet seasons. However, macroinvertebrate abundances showed strong links with more local land-use patterns within 100 m and 2 km radii. Circular buffers upstream of monitoring sites were more informative for macroinvertebrate assemblages than circular buffers around the monitoring sites. However, the latter did correlate well with physico-chemical water quality variables. Land-use variables correlated across spatial scales (i.e., 100 m up to 2 km radii), but not with the land use in the entire watershed area above the monitoring site. Our results indicate that physico-chemical water quality variables and macroinvertebrates may respond differently to land-uses at different scales. More importantly, our results illustrate that the choice regarding spatial land-use metrics can bias conclusions of environmental impact studies in river systems.

Microphytobenthos diversity and community structure across different micro-estuaries and micro-outlets: Effects of environmental variables on community structure

This study forms the first basic assessment of microphytobenthos (MPB) dynamics in micro-estuaries and micro-outlets in southern Africa. It examines MPB community responses to environmental variables and further investigates MPB composition qualitatively across different micro-estuaries and micro-outlets over four seasons in a warm temperate region of the subcontinent. Combinations of multivariate analyses were used to explore similarities and differences in MPB communities between systems. Human-induced catchment changes between microsystems ranged from no alteration (rating 0; mostly micro-outlets) to extreme modification (rating 5; mostly micro-estuaries). Two hundred and sixty-seven MPB taxa were identified within all the microsystems, with 247 and 230 MPB taxa being observed in the micro-estuaries and micro-outlets, respectively. The MPB communities differed slightly in terms of microsystem types and seasons, but no significant differences were observed. Multivariate analyses (i.e. Boosted Regression Trees, Canonical Correspondence Analysis) showed that water column variables were significant and important in structuring MPB communities, with soluble reactive phosphorus, sediment pH, turbidity, ammonium and temperature being documented as key drivers. The MPB community composition clearly reflected the influence of catchment anthropogenic activities on species composition and structure. Moderately modified catchments resulted in MPB community structure variation among water bodies in relationship to land use and salinity gradients. The study found that; (i) by virtue of their size, microsystems and their catchments are likely to be particularly vulnerable to anthropogenic pressures when compared to systems of larger size; (ii) a typical impacted state may reflect reduced environmental heterogeneity which, compared to larger systems, may be achieved over much shorter time periods (following a particular event) or under much less intensive impacts; and (iii) the response in terms of MPB structure may predictably reflect a concomitant change from a complex community dynamic (structure and spatio-temporal attributes) to one that approaches a homogeneous structure (poor spatial zonation, strong taxonomic dominance, low species diversity).

Projecting life-cycle environmental impacts of corn production in the U.S. Midwest under future climate scenarios using a machine learning approach

Climate change is exacerbating environmental pollution from crop production. Spatially and temporally explicit estimates of life-cycle environmental impacts are therefore needed for suggesting location and time relevant environmental mitigations strategies. Emission factors and process-based mechanism models are popular approaches used to estimate life-cycle environmental impacts. However, emission factors are often incapable of describing spatial and temporal heterogeneity of agricultural emissions, whereas process-based mechanistic models, capable of capturing the heterogeneity, tend to be very complicated and time-consuming. Efficient prediction of life-cycle environmental impacts from agricultural production is lacking. This study develops a rapid predictive model to quantify life-cycle global warming (GW) and eutrophication (EU) impacts of corn production using a novel machine learning approach. We used the boosted regression tree (BRT) model to estimate future life-cycle environmental impacts of corn production in U.S. Midwest counties under four emissions scenarios for years 2022-2100. Results from BRT models indicate that the cross-validation (R²) for predicting life cycle GW and EU impacts ranged from 0.78 to 0.82, respectively. Furthermore, results show that future life-cycle GW and EU impacts of corn production will increase in magnitude under all four emissions scenarios, with the highest environmental impacts shown under the high-emissions scenario. Moreover, this study found that changes in precipitation and temperature played a significant role in influencing the spatial heterogeneity in all life-cycle impacts across Midwest counties. The BRT model results indicate that machine learning can be a useful tool for predicting spatially and temporally explicit future life-cycle environmental impacts associated with corn production under different climate scenarios.

Water or sediment? Partitioning the role of water column and sediment chemistry as drivers of macroinvertebrate communities in an austral South African stream

Water pollution is a critical management issue, with many rivers and streams draining urban areas being polluted by the disposal of untreated solid waste and wastewater discharge, storm water and agricultural runoff. This has implications for biodiversity, and many rivers in the developing world are now considered compromised. We investigated benthic macroinvertebrate community structure and composition in relation to physico-chemical conditions of the water column and sediments. The study was conducted in an Austral catchment subject to both urban and agricultural pollutants in two different seasons. We assessed whether sediment characteristics were more important drivers of macroinvertebrate community composition than water column characteristics. We expected clear differences in macroinvertebrate community composition and in the associated community metrics due to distinct flow conditions between the two seasons. A combination of multivariate analyses (canonical correspondence analysis (CCA)) and biological indicator analysis were used to examine these patterns. Chironomidae was the most abundant family (>60%) in the upper mainstem river and stream sites. Stream sites were positively associated with CCA axis 2, being characterised by high turbidity and lower pH, salinity, phosphate concentration, channel width and canopy cover. Canopy cover, channel width, substrate embeddedness, phosphate concentration, pH, salinity and turbidity all had a significant effect on macroinvertebrate community composition. Using CCA variation partitioning, water quality was, however, a better predictor of benthic macroinvertebrate composition than sediment chemical conditions. Furthermore, our results suggest that seasonality had little effect on structuring benthic macroinvertebrate communities in this south-eastern zone of South Africa, despite clear changes in sediment chemistry. This likely reflects the relative lack of major variability in water chemistry compared to sediment chemistry between seasons and the relatively muted variability in precipitation between seasons than the more classic Austral temperate climates.

The long-term effects of invasive signal crayfish (Pacifastacus leniusculus) on instream macroinvertebrate communities

Non-native species represent a significant threat to indigenous biodiversity and ecosystem functioning worldwide. It is widely acknowledged that invasive crayfish species may be instrumental in modifying benthic invertebrate community structure, but there is limited knowledge regarding the temporal and spatial extent of these effects within lotic ecosystems. This study investigates the long term changes to benthic macroinvertebrate community composition following the invasion of signal crayfish, Pacifastacus leniusculus, into English rivers. Data from long-term monitoring sites on 7 rivers invaded by crayfish and 7 rivers where signal crayfish were absent throughout the record (control sites) were used to examine how invertebrate community composition and populations of individual taxa changed as a result of invasion. Following the detection of non-native crayfish, significant shifts in invertebrate community composition were observed at invaded sites compared to control sites. This pattern was strongest during autumn months but was also evident during spring surveys. The observed shifts in community composition following invasion were associated with reductions in the occurrence of ubiquitous Hirudinea species (Glossiphonia complanata and Erpobdella octoculata), Gastropoda (Radix spp.), Ephemeroptera (Caenis spp.), and Trichoptera (Hydropsyche spp.); although variations in specific taxa affected were evident between regions and seasons. Changes in community structure were persistent over time with no evidence of recovery, suggesting that crayfish invasions represent significant perturbations leading to permanent changes in benthic communities. The results provide fundamental knowledge regarding non-native crayfish invasions of lotic ecosystems required for the development of future management strategies.

Boosted regression tree model-based assessment of the impacts of meteorological drivers of hand, foot and mouth disease in Guangdong, China

BACKGROUND

Hand, foot and mouth disease (HFMD) is a common childhood infection and has become a major public health issue in China. Considerable research has focused on the role of meteorological factors in HFMD development. Nonlinear relationship, delayed effects and collinearity problems are key issues for achieving robust and accurate estimations in this kind of weather-health relationship explorations. The current study was designed to address these issues and assess the impact of meteorological factors on HFMD in Guangdong, China.

METHODS

Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from China CDC and the National Meteorological Information Center, respectively. After a preliminary variable selection, for each dataset boosted regression tree (BRT) models were applied to determine the optimal lag for meteorological factors at which the variance of HFMD cases was most explained, and to assess the impacts of these meteorological factors at the optimal lag.

RESULTS

Variance of HFMD cases was explained most by meteorological factors about 1 week ago. Younger children and those from the Pearl-River Delta Region were more sensitive to weather changes. Temperature had the largest contribution to HFMD epidemics (28.99-71.93%), followed by precipitation (6.52-16.11%), humidity (3.92-17.66%), wind speed (3.84-11.37%) and sunshine (6.21-10.36%). Temperature between 10°C and 25°C, as well as humidity between 70% and 90%, had a facilitating effect on the epidemic of HFMD. Sunshine duration above 9h and wind speed below 2.5m/s also contributed to an elevated risk of HFMD. The positive relationship between HFMD and precipitation reversed when the daily amount of rainfall exceeded 25 mm.

CONCLUSIONS

This study indicated significantly facilitating effects of five meteorological factors within some range on the epidemic of HFMD. Results from the current study were particularly important for developing early warning and response system on HFMD in the context of global climate change.

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users.

Environmental Controls on River Assemblages at the Regional Scale: An Application of the Elements of Metacommunity Structure Framework

Understanding factors that structure regional biodiversity is important for linking ecological and biogeographic processes. Our objective was to explore regional patterns in riverine benthic invertebrate assemblages in relation to their broad positioning along the river network and examine differences in composition, biodiversity (alpha and beta diversity), and environmental drivers. We up-scaled methods used to examine patterns in metacommunity structure (Elements of Metacommunity Structure framework) to examine faunal distribution patterns at the regional extent for 168 low-mountain stream invertebrate assemblages in central Germany. We then identified the most influential environmental factors using boosted regression trees. Faunal composition patterns were compartmentalised (Clementsian or quasi-Clementsian), with little difference from headwaters to large rivers, potentially reflecting the regional scale of the study, by crossing major catchment boundaries and incorporating different species pools. While idealised structures did not vary, environmental drivers of composition varied considerably between river sections and with alpha diversity. Prediction was substantially weaker, and the importance of space was greater, in large rivers compared to other sections suggesting a weakening in species sorting downstream. Further, there was a stronger transition in composition than for alpha diversity downstream. The stronger links with regional faunal composition than with richness further emphasises the importance of considering the alternative ways in which anthropogenic stressors are operating to affect biodiversity patterns. Our approach allowed bridging the gap between local (or metacommunity) and regional scales, providing key insights into drivers of regional biodiversity patterns.