Challenges to Accurate Estimation of Methane Emission from Septic Tanks with Long Emptying Intervals.

Septic tanks in low- and middle-income countries are often not emptied for a long time, potentially resulting in poor pollutant removal efficiency and increased greenhouse gas emissions, including methane (CH4). We examined the impact of long emptying intervals (4.0-23 years) on the biochemical oxygen demand (BOD) removal efficiency of 15 blackwater septic tanks and the CH4 emission rates of 23 blackwater septic tanks in Hanoi. The average BOD removal efficiency was 37% (-2-65%), and the average CH4 emission rate was 10.9 (2.2-26.8) g/(cap·d). The emptying intervals were strongly negatively correlated with BOD removal efficiency (R = -0.676, p = 0.006) and positively correlated with CH4 emission rates (R = 0.614, p = 0.001). CH4 emission rates were positively correlated with sludge depth (R = 0.596, p = 0.002), but against expectation, negatively correlated with BOD removal efficiency (R = -0.219, p = 0.451). These results suggest that shortening the emptying interval improves the BOD removal efficiency and reduces the CH4 emission rate. Moreover, the CH4 emission estimation of the Intergovernmental Panel on Climate Change, which is a positive conversion of BOD removal, might be inaccurate for septic tanks with long emptying intervals. Our findings suggest that emptying intervals, sludge depth, and per-capita emission factors reflecting long emptying intervals are potential parameters for accurately estimating CH4 emissions from septic tanks.

Olfactory Information Storage Engages Subcortical and Cortical Brain Regions That Support Valence Determination.

The olfactory bulb (OB) delivers sensory information to the piriform cortex (PC) and other components of the olfactory system. OB-PC synapses have been reported to express short-lasting forms of synaptic plasticity, whereas long-term potentiation (LTP) of the anterior PC (aPC) occurs predominantly by activating inputs from the prefrontal cortex. This suggests that brain regions outside the olfactory system may contribute to olfactory information processing and storage. Here, we compared functional magnetic resonance imaging BOLD responses triggered during 20 or 100 Hz stimulation of the OB. We detected BOLD signal increases in the anterior olfactory nucleus (AON), PC and entorhinal cortex, nucleus accumbens, dorsal striatum, ventral diagonal band of Broca, prelimbic-infralimbic cortex (PrL-IL), dorsal medial prefrontal cortex, and basolateral amygdala. Significantly stronger BOLD responses occurred in the PrL-IL, PC, and AON during 100 Hz compared with 20 Hz OB stimulation. LTP in the aPC was concomitantly induced by 100 Hz stimulation. Furthermore, 100 Hz stimulation triggered significant nuclear immediate early gene expression in aPC, AON, and PrL-IL. The involvement of the PrL-IL in this process is consistent with its putative involvement in modulating behavioral responses to odor experience. Furthermore, these results indicate that OB-mediated information storage by the aPC is embedded in a connectome that supports valence evaluation.

Hippocampal subfield-specific Homer1a expression is triggered by learning-facilitated long-term potentiation and long-term depression at medial perforant path synapses.

Learning about general aspects, or content details, of space results in differentiated neuronal information encoding within the proximodistal axis of the hippocampus. These processes are tightly linked to long-term potentiation (LTP) and long-term depression (LTD). Here, we explored the precise sites of encoding of synaptic plasticity in the hippocampus that are mediated by information throughput from the perforant path. We assessed nuclear Homer1a-expression that was triggered by electrophysiological induction of short and long forms of hippocampal synaptic plasticity, and compared it to Homer1a-expression that was triggered by LTP and LTD enabled by different forms of spatial learning. Plasticity responses were induced by patterned stimulation of the perforant path and were recorded in the dentate gyrus (DG) of freely behaving rats. We used fluorescence in situ hybridization to detect experience-dependent nuclear encoding of Homer1a in proximodistal hippocampal subfields. Induction of neither STP nor STD resulted in immediate early gene (IEG) encoding. Electrophysiological induction of robust LTP, or LTD, resulted in highly significant and widespread induction of nuclear Homer1a in all hippocampal subfields. LTP that was facilitated by novel spatial exploration triggered similar widespread Homer1a-expression. The coupling of synaptic depression with the exploration of a novel configuration of landmarks resulted in localized IEG expression in the proximal CA3 region and the lower (infrapyramidal) blade of the DG. Our findings support that synaptic plasticity induction via perforant path inputs promotes widespread hippocampal information encoding. Furthermore, novel spatial exploration promotes the selection of a hippocampal neuronal network by means of LTP that is distributed in an experience-dependent manner across all hippocampus subfields. This network may be modified during spatial content learning by LTD in specific hippocampal subfields. Thus, long-term plasticity-inducing events result in IEG expression that supports establishment and/or restructuring of neuronal networks that are necessary for long-term information storage.

Greenhouse Gas Emissions from Blackwater Septic Systems.

Septic systems are potentially a significant source of greenhouse gases (GHGs). The present study investigated GHGs from the blackwater septic systems that are widely used especially in low- and middle-income countries. Ten blackwater septic tanks in Hanoi, Vietnam, were investigated using the floating chamber method. The average methane and carbon dioxide emission rates measured at the first compartment (65% of total capacity) of the septic tanks were 11.92 and 20.24 g/cap/day, respectively, whereas nitrous oxide emission was negligible. Methane emission rate was significantly correlated with septage oxidation-reduction potential (ORP) (R = -0.67, p = 0.034), chemical oxygen demand mass (R = 0.78, p = 0.007), and biochemical oxygen demand mass (R = 0.78, p = 0.008), whereas it was not significantly correlated with water temperature (R = 0.26, p = 0.47) and dissolved oxygen (R = -0.59, p = 0.075) within the limited range: 30.6-31.7 °C and 0.03-0.34 mg-O2/L. The methane emission rates from septic tanks accumulating septage for >5 years were significantly higher than those at 0-5 years (p = 0.016). These results suggest that lower ORP and higher biodegradable carbon mass, in association with longer septage storage periods are key conditions for methane emissions. To the best of our knowledge, this is the first study to characterize GHG emissions from septic systems.

Novel encoding and updating of positional, or directional, spatial cues are processed by distinct hippocampal subfields: Evidence for parallel information processing and the "what" stream.

The specific roles of hippocampal subfields in spatial information processing and encoding are, as yet, unclear. The parallel map theory postulates that whereas the CA1 processes discrete environmental features (positional cues used to generate a "sketch map"), the dentate gyrus (DG) processes large navigation-relevant landmarks (directional cues used to generate a "bearing map"). Additionally, the two-streams hypothesis suggests that hippocampal subfields engage in differentiated processing of information from the "where" and the "what" streams. We investigated these hypotheses by analyzing the effect of exploration of discrete "positional" features and large "directional" spatial landmarks on hippocampal neuronal activity in rats. As an indicator of neuronal activity we measured the mRNA induction of the immediate early genes (IEGs), Arc and Homer1a. We observed an increase of this IEG mRNA in CA1 neurons of the distal neuronal compartment and in proximal CA3, after novel spatial exploration of discrete positional cues, whereas novel exploration of directional cues led to increases in IEG mRNA in the lower blade of the DG and in proximal CA3. Strikingly, the CA1 did not respond to directional cues and the DG did not respond to positional cues. Our data provide evidence for both the parallel map theory and the two-streams hypothesis and suggest a precise compartmentalization of the encoding and processing of "what" and "where" information occurs within the hippocampal subfields.

Differentiated somatic gene expression is triggered in the dorsal hippocampus and the anterior retrosplenial cortex by hippocampal synaptic plasticity prompted by spatial content learning.

Hippocampal afferent inputs, terminating on proximal and distal subfields of the cornus ammonis (CA), enable the functional discrimination of 'what' (item identity) and 'where' (spatial location) elements of a spatial representation. This kind of information is supported by structures such as the retrosplenial cortex (RSC). Spatial content learning promotes the expression of hippocampal synaptic plasticity, particularly long-term depression (LTD). In the CA1 region, this is specifically facilitated by the learning of item-place features of a spatial environment. Gene-tagging, by means of time-locked fluorescence in situ hybridization (FISH) to detect nuclear expression of immediate early genes, can reveal neuronal populations that engage in experience-dependent information encoding. In the current study, using FISH, we examined if learning-facilitated LTD results in subfield-specific information encoding in the hippocampus and RSC. Rats engaged in novel exploration of small items during stimulation of Schaffer collateral-CA1 synapses. This resulted in LTD (> 24 h). FISH, to detect nuclear expression of Homer1a, revealed that the distal-CA1 and proximal-CA3 subcompartments were particularly activated by this event. By contrast, all elements of the proximodistal cornus ammonis-axis showed equal nuclear Homer1a expression following LTD induction solely by means of afferent stimulation. The RSC exhibited stronger nuclear Homer1a expression in response to learning-facilitated LTD, and to novel item-place experience, compared to LTD induced by sole afferent stimulation in CA1. These results show that both the cornus ammonis and RSC engage in differentiated information encoding of item-place learning that is salient enough, in its own right, to drive the expression of hippocampal LTD. These results also reveal a novel role of the RSC in item-place learning.

Intracerebral inoculation of healthy non-transgenic rats with a single aliquot of oligomeric amyloid-ß (1-42) profoundly and progressively alters brain function throughout life.

One of the puzzling aspects of sporadic Alzheimer's disease (AD) is how it commences. Changes in one key brain peptide, amyloid-beta (Aß), accompany disease progression, but whether this comprises a trigger or a consequence of AD is still a topic of debate. It is clear however that the cerebral presence of oligomeric Aß (1-42) is a key factor in early AD-pathogenesis. Furthermore, treatment of rodent brains with oligomeric Aß (1-42) either in vitro or in vivo, acutely impairs hippocampal synaptic plasticity, creating a link between Aß-pathology and learning impairments. Here, we show that a once-off inoculation of the brains of healthy adult rats with oligomeric Aß (1-42) exerts debilitating effects on the long-term viability of the hippocampus, one of the primary targets of AD. Changes are progressive: months after treatment, synaptic plasticity, neuronal firing and spatial learning are impaired and expression of plasticity-related proteins are changed, in the absence of amyloid plaques. Early changes relate to activation of microglia, whereas later changes are associated with a reconstruction of astroglial morphology. These data suggest that a disruption of Aß homeostasis may suffice to trigger an irreversible cascade, underlying progressive loss of hippocampal function, that parallels the early stages of AD.

Estimating ammonium changes in pilot and full-scale constructed wetlands using kinetic model, linear regression, and machine learning.

Constructed wetlands (CWs) are a widely utilized nature-based wastewater treatment method for various effluents. However, their application has been more focused on pilot and full-scale CWs with substantial surface areas and extended operation times, which hold greater relevance in practical scenarios. This study used kinetics, linear regression (LR), and machine learning (ML) models to estimate effluent ammonium in pilot and full-scale CWs. From screening 1476 papers, 24 pilot and full-scale CW studies were selected to extract data containing 15 features and 975 data points. Nine models were fit to this data, revealing that linear models were less effective in capturing CW effluent compared to nonlinear ML algorithms. For training data, the Monod kinetic model predicted the poorest performance with an RMSE of 41.84 mg/L and R2 of 0.34, followed by simple LR (RMSE 24.29 mg/L and R2 0.77) and multiple LR (RMSE 22.63 mg/L and R2 0.80). In contrast, Cubist and Random Forest achieved high performances, with an average RMSE of 12.01 ± 5.38 and an average R2 of 0.93 ± 0.07 for Cubist, and an average RMSE of 15.94 ± 10.69 and an average R2 of 0.91 ± 0.08 for RF. The trained Random Forest performed the best for new data, with an R2 of 0.93 and RMSE of 13.48 mg/L. This ML-based model is a valuable tool for efficiently estimating effluent ammonium concentration in pilot and full-scale CWs, thereby facilitating the design of systems.

Land-based plastic leakage into the aquatic environment from municipal solid waste - Waste flow diagram applied to Tuy Hoa City, Phu Yen, Vietnam.

Plastic mismanagement and its subsequent pollution by rapid economic development and urbanisation pose significant challenges for modern world society. Notwithstanding one of the main sources for macro plastic leakage into the ocean from land, precise assessment of plastic pollution origins from Southeast Asia is yet to be clearly examined. In order to make informed decisions and prioritise areas of improvement it is required to better understand the waste leakage dynamics at the local level. In this work, the Waste Flow Diagram (WFD) was applied to understand the sources and fates of plastics leaking from the solid waste management system for the case of Tuy Hoa City, Phu Yen, Vietnam. The study shows scenarios of leakage into the aquatic environment ranging from 0.8 to 2.7 kg/cap/year, which originates mainly from the collection system. Targeted improvements to this stage of the service could reduce leakages and the overall environmental impacts of mismanaged plastic waste. The results of this study show the necessity and importance of having up to date and reliable data to better inform stakeholders and service planning, facilitating efficient action against plastic pollution. As the first peer-reviewed scientific article critically applying the WFD, this work highlights the steps and challenges of the methodology and critically analyses different methodological pathways.

Integrating data-driven ecological models in an expert-based decision support system for water management in the Du river basin (Vietnam).

In this study, classification trees were combined with the Water Framework Directive (WFD)-Explorer, a modular toolbox that supports integrated water management in a river basin to evaluate the impact of different restoration measures on river ecology. First, the WFD-Explorer toolbox analysed the effect of different restoration options on the abiotic river characteristics based on the water and substance balance embedded in the simulation environment. Based on these abiotic characteristics, the biological index Biological Monitoring Working Party for Vietnam was then predicted by classification trees that were trained on biological and abiotic data collected in the Du river basin in northern Vietnam. The ecological status of streams in the basin ranged from nearly pristine headwaters to severely impacted river stretches. Elimination of point sources from ore extraction and decentralised domestic wastewater treatment proved to be the most effective measures to improve the ecological condition of the Du river basin. The combination of the WFD-Explorer results with data-driven models enabled model application in a situation where expert knowledge was lacking. Consequently, this approach appeared promising for decision support in the context of river restoration and conservation management.

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea.

The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and time-consuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for forecasting algal blooms is a feasible and useful method to overcome these problems. This study explores the potential application of optical measures to enhance algal bloom prediction in terms of prediction accuracy and workload reduction, aided by machine learning (ML) models. Compared to absorption-derived parameters, commonly used fluorescence indices such as the fluorescence index (FI), humification index (HIX), biological index (BIX), and protein-like component improved the prediction accuracy. However, the prediction accuracy was decreased when all optical indices were considered for computation due to increased noise and uncertainty in the models. With the exception of chemical oxygen demand (COD), this study successfully replaced biochemical oxygen demand (BOD), dissolved organic carbon (DOC), and nutrients with selected fluorescence indices, demonstrating relatively analogous performance in either training or testing data, with consistent and good coefficient of determination (R2) values of approximately 0.85 and 0.74, respectively. Among all models considered, ensemble learning models consistently outperformed conventional regression models and artificial neural networks (ANNs). However, there was a trade-off between accuracy and computation efficiency among the ensemble learning models (i.e., Stacking and XGBoost) for algal bloom prediction. Our study offers a glimpse of the potential application of spectroscopic measures to improve accuracy and efficiency in algal bloom prediction, but further work should be carried out in other water bodies to further validate our proposed hypothesis.

Microplastics in sediments from urban and suburban rivers: Influence of sediment properties.

Although sediments are considered to be a major sink for microplastics (MP), there is still a relative lack of knowledge on the factors that influence the occurrence and abundance of MP in riverine sediments. The present study investigated the occurrence and distribution of MP in riverine sediments collected at twelve sites representative of different populated and urbanized rivers (To Lich, Nhue and Day Rivers) located in the Red River Delta (RRD, Vietnam, during dry and rainy seasons. MP concentrations ranged from 1600 items kg-1 dw to 94,300 items kg-1dw. Fiber shape dominated and MP were made of polypropylene (PP) and polyethylene (PE) predominantly. An absence of seasonal effect was observed for both fragments and fibers for each rivers. Decreasing MP concentrations trend was evidenced from the To Lich River, to the Nhue River and to the Day River, coupled with a decreasing fiber length and an increasing fragment area in the surface sediment from upstream to downstream. Content of organic matter was correlated to MP concentrations suggesting that, high levels of organic matter could be MP hotspots in urban rivers. Also, high population density as well as in highly residential areas are related to higher MP concentrations in sediments. Finally, a MP high ecological risk (RI: 866 to 4711) was calculated in the RDD.

Application and validation of a biotic ligand model for calculating acute toxicity of lead to Moina dubia in lakes of Hanoi, Vietnam.

It is increasingly being recognized that biotic ligand models (BLMs) can successfully predict the toxicity of divalent metals toward aquatic biota applied to temperate freshwater ecosystems. However, studies on the eutrophic lakes in tropical regions toward native tropical organisms, including Moina, are relatively limited. In this study, Moina dubia, the native organism of the Hanoi eutrophic urban lakes, were used in toxicological studies of lead (Pb); 24-h EC50 value of Pb was 523.19 µg/L under optimal living conditions for M. dubia in the laboratory. The constant binding of Pb2+ on M. dubia surface sites (log KPbBL = 2.38) was significantly low. Other stability constants were obtained under experiments as logKCaBL = 2.48, logKMgBL = 2.80, logKNaBL = 2.35, logKKBL = 2.49, and logKHBL = 3.026. A BLM was developed to calculate the acute toxicity (EC50-24 h) of lead on M. dubia based on the condition of the urban lakes of Hanoi. Validation with toxicity data in synthetic medium showed a coefficient determination of 79.16% and a mean absolute percentage error (MAPE) of 10.2%, while the validation with the toxicity data with natural water medium from 11 Hanoi lakes showed a coefficient determination of 73.7% and a MAPE of 13.66%. The BLM worked well with water at a pH of 7.0 to 8.0, but failed with water at a pH above 8.0. Eutrophic conditions proved to have a significant effect on the toxicity of lead on local zooplankton.

Reversible and irreversible transgenerational effects of metal exposure on nine generations of a tropical micro-crustacean.

Micro-crustaceans are important grazers that control the algal blooms in eutrophic lakes. However, we know little about how these key species may be affected by long-term exposure to contaminants and when the transgenerational effects are reversible and irreversible. To address this, we investigated the effects of lead (Pb, 100 µg L-1) exposure on morphology and reproduction of Moina dubia for nine consecutive generations (F1-F9) in three treatments: control, Pb, and pPb (M. dubia from Pb-exposed parents returned to the control condition). In F1-F2, Pb did not affect morphology, and reproduction of M. dubia. In all later generations, Pb-exposed M. dubia had a smaller body and shorter antennae than those in control. In F3-F6, pPb-exposed animals showed no differences in body size and antennae compared to the control, suggesting recoverable effects. In F7-F9, the body size and antennae of pPb-exposed animals did not differ compared to Pb-exposed ones, and both were smaller than the control animals, suggesting irreversible effects. Pb exposure reduced the brood size, number of broods and total neonates per female in F3-F9, yet the reproduction could recover in pPb treatment until F7. No recovery of the brood size and number of broods per female was observed in pPb-exposed animals in the F8-F9. Our study suggests that long-term exposure to metals, here Pb, may cause irreversible impairments in morphology and reproduction of tropical urban micro-crustaceans that may lower the top-down control on algal blooms and functioning of eutrophic urban lakes.

The Perirhinal Cortex Engages in Area and Layer-Specific Encoding of Item Dimensions.

The perirhinal cortex (PRC), subdivided into areas 35 and 36, belongs to the parahippocampal regions that provide polysensory input to the hippocampus. Efferent and afferent connections along its rostro-caudal axis, and of areas 35 and 36, are extremely diverse. Correspondingly functional tasks in which the PRC participates are manifold. The PRC engages, for example, in sensory information processing, object recognition, and attentional processes. It was previously reported that layer II of the caudal area 35 may be critically involved in the encoding of large-scale objects. In the present study we aimed to disambiguate the roles of the different PRC layers, along with areas 35 and 36, and the rostro-caudal compartments of the PRC, in processing information about objects of different dimensions. Here, we compared effects on information encoding triggered by learning about subtle and discretely visible (microscale) object information and overt, highly visible landmark (macroscale) information. To this end, nuclear expression of the immediate early gene Arc was evaluated using fluorescence in situ hybridization. Increased nuclear Arc expression occurred in layers III and V-VI of the middle and caudal parts of area 35 in response to both novel microscale and macroscale object exposure. By contrast, a significant increase in Arc expression occurred in area 36 only in response to microscale objects. These results indicate that area 36 is specifically involved in the encoding of small and less prominently visible items. In contrast, area 35 engages globally (layer III to VI) in the encoding of object information independent of item dimensions.

Application of Machine Learning for eutrophication analysis and algal bloom prediction in an urban river: A 10-year study of the Han River, South Korea.

The increasing release of nutrients to aquatic environments has led to great concern regarding eutrophication and the risk of unwanted algal blooms. Based on observational data of 20 water quality parameters measured on a monthly basis at 40 stations from 2011 to 2020, this study applied different Machine Learning (ML) algorithms to suggest the best option for algal bloom prediction in the Han River, a large river in South Korea. Eight different ML algorithms were categorized into several groups of statistical learning, regression family, and deep learning, and were then compared for their suitability to predict the chlorophyll-derived trophic index (TSI-Chla). ML algorithms helped identify the most important water quality parameters contributing to algal bloom prediction. The ML results confirmed that eutrophication and algal proliferation were governed by the complex interplay between nutrients (nitrogen and phosphorus), organic contaminants, and environmental factors. Of the models tested, the adaptive neuro-fuzzy inference system (ANFIS) exhibited the best performance owing to its consistent and outperforming prediction both quantitatively (i.e., via regression) and qualitatively (i.e., via classification), which was evidenced by the lowest value of mean absolute error (MAE) of 0.09, and the highest F1-score, Recall and Precision of 0.97, 0.98 and 0.96, respectively. In a further step, a representative web application was constructed to assist common users to predict the trophic status of the Han River. This study demonstrated that ML techniques are not only promising for highly accurate water quality modeling of urban rivers, but also reduce time and labor intensity for experiments, which decreases the number of monitored water quality parameters, providing further insights into the driving factors of water quality deterioration. They ultimately help devise proactive strategies for sustainable water management.

Involvement of the Postrhinal and Perirhinal Cortices in Microscale and Macroscale Visuospatial Information Encoding.

Whereas the postrhinal cortex (POR) is a critical center for the integration of egocentric and allocentric spatial information, the perirhinal cortex (PRC) plays an important role in the encoding of objects that supports spatial learning. The POR and PRC send afferents to the hippocampus, a structure that builds complex associative memories from the spatial experience. Hippocampal encoding of item-place experience is accompanied by the nuclear expression of immediate early gene (IEGs). Subfields of the Cornus ammonius and subregions of the hippocampus exhibit differentiated and distinct encoding responses, depending on whether the spatial location and relationships of large highly visible items (macroscale encoding) or small partially concealed items (microscale encoding), is learned. But to what extent the PRC and POR support hippocampal processing of different kinds of item-place representations is unclear. Using fluorescence in situ hybridization (FISH), we examined the effect of macroscale (overt, landmark) and microscale (subtle, discrete) item-place learning on the nuclear expression of the IEG, Arc. We observed an increase in Arc mRNA in the caudal part of PRC area 35 and the caudal part of the POR after macroscale, but not microscale item-place learning. The caudal part of PRC area 36, the rostral and middle parts of PRC areas 35 and 36, as well as the middle part of the POR responded to neither type of item. These results suggest that macroscale items may contain a strong identity component that is processed by specific compartments of the PRC and POR. In contrast small, microscale items are not encoded by the POR or PRC, indicating that item dimensions may play a role in the involvement of these structures in item processing.

Comparison of the abiotic preferences of macroinvertebrates in tropical river basins.

We assessed and compared abiotic preferences of aquatic macroinvertebrates in three river basins located in Ecuador, Ethiopia and Vietnam. Upon using logistic regression models we analyzed the relationship between the probability of occurrence of five macroinvertebrate families, ranging from pollution tolerant to pollution sensitive, (Chironomidae, Baetidae, Hydroptilidae, Libellulidae and Leptophlebiidae) and physical-chemical water quality conditions. Within the investigated physical-chemical ranges, nine out of twenty-five interaction effects were significant. Our analyses suggested river basin dependent associations between the macroinvertebrate families and the corresponding physical-chemical conditions. It was found that pollution tolerant families showed no clear abiotic preference and occurred at most sampling locations, i.e. Chironomidae were present in 91%, 84% and 93% of the samples taken in Ecuador, Ethiopia and Vietnam. Pollution sensitive families were strongly associated with dissolved oxygen and stream velocity, e.g. Leptophlebiidae were only present in 48%, 2% and 18% of the samples in Ecuador, Ethiopia and Vietnam. Despite some limitations in the study design, we concluded that associations between macroinvertebrates and abiotic conditions can be river basin-specific and hence are not automatically transferable across river basins in the tropics.