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Algal polyunsaturated fatty acids (PUFA), essential for somatic growth and reproduction of aquatic animals, are influenced by ambient environmental conditions, including light and nutrients. Few studies have addressed the extent to which changes in algal PUFA can influence stream herbivore PUFA profiles and the implications for stream food webs. We manipulated subtropical stream periphyton by applying two light levels (open and shaded canopy) and two nutrient regimes (ambient and enriched) to investigate the response of PUFA and somatic growth in stream herbivores. After 6 weeks, the relative content of periphyton PUFA (%) changed distinctly and differed among treatments. Periphyton in the control treatment with open canopy showed a decline in eicosapentaenoic acid (EPA) relative to initial conditions, whereas shading increased EPA and total highly unsaturated FA (HUFA), but decreased α-linolenic acid (ALA), linoleic acid and total C18 PUFA. The interaction of open canopy and added nutrients increased periphyton ALA compared with initial conditions, while the combined effects of shading and added nutrients led to greater total HUFA. FA similarity between stream grazers (the mayfly Austrophlebioides and caddisfly Helicopsyche) and periphyton increased with periphyton HUFA content. In addition, the growth of large instars of both grazers also increased in response to increased periphyton HUFA %. Our findings show that environmental changes, associated with riparian canopy and nutrients, can lead to changes in periphyton PUFA composition that in turn affect growth and PUFA composition in stream grazers.

Current ecoacoustic analysis methods are unsuitable for exploring unknown sound‐types in large acoustic datasets. Ecoacoustic studies can collect considerable quantities of audio with minimal field effort; however, analysing these recordings effectively remains a challenge. Manual annotation is labour‐intensive, acoustic indices only summarise soundscape patterns and machine learning tools like BirdNet enable species‐level identification but are not optimised for non‐terrestrial taxa and cannot explore unknown sound‐types. This creates a clear need for exploratory methods that can efficiently identify unknown sound‐types, particularly in data‐deficient environments. We present a protocol to identify sound‐types in ecoacoustic recordings using beta acoustic indices and nested clustering (a multi‐level method where clusters contain sub‐clusters). Compared to existing methods, our protocol offers a more adaptable framework for identifying sound‐types in unsurveyed or data‐poor environments. It is suitable for large acoustic datasets and does not require advanced computational skills. To our knowledge, this is the first protocol to combine beta acoustic indices with nested clustering to identify sound‐types in ecoacoustic data. Limited evidence exists on how window length (WL) influences beta index calculations, so we tested 11 indices against six WLs and multiple cluster quantities. Our nested clustering approach addressed challenges including background noise, acoustic overlap and data imbalances (e.g. unequal quantities of reoccurring sound‐types). We tested our protocol in a stream soundscape as freshwater ecosystems are underexplored, lack a global underwater sound database and contain many unidentified sounds. We used a systematic testing framework to identify optimal combinations of beta indices and WL for sound‐type clustering. For the studied system, the Kolmogorov–Smirnov index with a 2048 WL produced the highest‐performing results. This combination scored ≥0.75 (normalised, 0–1) on all external validation metrics, a true positive rate of over 90% and identified almost 90% of sound‐types. This work presents a streamlined approach for identifying unknown sound events in large audio datasets using minimal manual effort and demonstrates a novel use‐case for beta indices. We anticipate this method will inspire new applications of beta indices and user‐friendly analysis tools for big data, advancing ecoacoustic analyses alongside technological advancements.

Understanding soundscapes, that is, the totality of sounds within a location, helps to assess nature in a more holistic way, providing a novel approach to investigating ecosystems. To date, very few studies have investigated freshwater soundscapes in their entirety and none across a broad spatial scale. In this study, we recorded 12 freshwater streams in South East Queensland continuously for three days and calculated three acoustic indices for each minute in each stream. We then used principal component analysis of summary statistics for all three acoustic indices to investigate acoustic properties of each stream and spatial variation in their soundscapes. All streams had a unique soundscape with most exhibiting diurnal variation in acoustic patterns. Across these sites, we identified five distinct groups with similar acoustic characteristics. We found that we could use summary statistics of AIs to describe daytimes across streams as well. Most difference in stream soundscapes was observed during the daytime with significant variation in soundscapes both between hours and among sites. Synthesis and Application. We demonstrate how to characterize stream soundscapes by using simple summary statistics of complex acoustic indices. This technique allows simple and rapid investigation of streams with similar acoustic properties and the capacity to characterize them in a holistic and universal way. While we developed this technique for freshwater streams, it is also applicable to terrestrial and marine soundscapes. Understanding soundscapes helps to assess nature in a holistic way and provides a novel approach to investigate ecosystems. In unprecedented spatial and temporal resolution, we recorded 12 freshwater streams in south‐east Queensland for multiple days, calculated three acoustic indices and used a principal component analysis to investigate acoustic properties of each stream. While all streams had a unique soundscape, we could also identified five distinct groups with similar acoustic characteristics across all sites, showing our technique allows a rapid investigation of stream soundscape.

Wetlands are increasingly valuable under climate change in terms of their ecological functions, ecosystem services, and biodiversity. Simultaneously, wetlands are hotspots for anthropogenic activity due to their high soil fertility and water supply, and have been subject to significant modification, degradation, and staggering losses. With climate change having increasing impacts on ecosystems globally, the need for wetland restoration is rapidly growing. Natural regeneration, whereby vegetation is allowed to regrow via propagules already present within the landscape, provides a cost-effective and large-scale approach to restoration for many, but not, all wetlands. This paper emphasises the importance of natural regeneration of wetland ecosystems as an effective restoration approach under climate change. We discuss drivers and barriers of natural regeneration of wetlands under climate change along with implications for management approaches. Drivers of wetland natural regeneration are depicted along with their interactions, displaying a range of abiotic and biotic factors that influence ecosystem change. Key adaption approaches to maintain and promote natural regeneration of wetlands under climate change include integrated land and water management, protecting and promoting key relevant biotic and abiotic processes within landscapes, and reconsidering current exotic species management strategies. Most importantly, however, natural regeneration should be recognised as an important and viable restoration approach under climate change in order to meet restoration demand and promote landscape resilience to changing conditions.

Species distribution models are widely used for stream bioassessment, estimating changes in habitat suitability and identifying conservation priorities. We tested the accuracy of three modelling strategies (single species ensemble, multi-species response and community classification models) to predict fish assemblages at reference stream segments in coastal subtropical Australia. We aimed to evaluate each modelling strategy for consistency of predictor variable selection; determine which strategy is most suitable for stream bioassessment using fish indicators; and appraise which strategies best match other stream management applications. Five models, one single species ensemble, two multi-species response and two community classification models, were calibrated using fish species presence-absence data from 103 reference sites. Models were evaluated for generality and transferability through space and time using four external reference site datasets. Elevation and catchment slope were consistently identified as key correlates of fish assemblage composition among models. The community classification models had high omission error rates and contributed fewer taxa to the 'expected' component of the taxonomic completeness (O/E50) index than the other strategies. This potentially decreases the model sensitivity for site impact assessment. The ensemble model accurately and precisely modelled O/E50 for the training data, but produced biased predictions for the external datasets. The multi-species response models afforded relatively high accuracy and precision coupled with low bias across external datasets and had lower taxa omission rates than the community classification models. They inherently included rare, but predictable species while excluding species that were poorly modelled among all strategies. We suggest that the multi-species response modelling strategy is most suited to bioassessment using freshwater fish assemblages in our study area. At the species level, the ensemble model exhibited high sensitivity without reductions in specificity, relative to the other models. We suggest that this strategy is well suited to other non-bioassessment stream management applications, e.g., identifying priority areas for species conservation.

Bhutan is recognized for conservation success under its pro‐environmental development philosophy Gross National Happiness (GNH). However, an increase in area coverage alone cannot track the true contribution of protected areas (PAs) to biodiversity conservation. Capturing PA dynamism by tracking PADDD (PA downgrading, downsizing, and degazettement) and gain events can be used as a more comprehensive evaluation method. Based on existing data, we tracked gain events, enacted and proposed PADDD events, proximate causes of PADDD, and gain and PADDD events trends in Bhutan from 1966 to 2016. We also compared PADDD events recorded in www.PADDDtracker.org with the primary data sourced for our study. We discussed the findings in light of four tenets of GNH: good governance, sustainable socioeconomic development, preservation, and promotion of culture, and environmental conservation. We identified 81 gain and 29 PADDD events. All 12 proposed policy downgrading events in 2004 were proximally caused by infrastructure development, while all degazettement (n = 6) in 1993 and all downsizing events (two in 1984 and one in 1993) were proximally caused by conservation planning. Overall the gain and PADDD events were episodic but policy downgrading events occurred only from 2002. Based on our country data, we recorded 4.8 times more PADDD events than was recorded in www.PADDDtracker.org where even some degazetted PAs were not recorded. All gain events and even PADDD events, excluding one enacted and 12 proposed policy downgrading events caused by hydropower projects were aimed to improve conservation thus aligning with tenets of GNH. However, as hydropower is the specific cause for all proposed PADDD, Bhutan should be concerned about PADDD. Our findings provide further evidence for the dynamic nature of PAs, the widespread nature of PADDD and difficulty in detecting it. Furthermore, they also suggest the need to conduct archival case studies to better detect PADDD and PA dynamism.

Most freshwater mussels have larvae (glochidia in Unionidae, Margaritiferidae and Hyriidae) that are parasitic on fishes. This study describes and compares the diversity of glochidia among 17 species of Australasian Hyriidae. Here, scanning electron microscopy was used to illustrate shell morphology, while patterns of diversity in size, shape and morphological characteristics were analysed quantitatively and qualitatively with Principal Component, Linear Discriminant, and Multiple Correspondence Analyses to separate species with varying degrees of discrimination. Results showed shell lengths ranged from 50 to 390 μm. Shape varied, from sub-oval to sub-triangular, bilaterally symmetrical to scalene, and hook morphology varied from unicuspid, bicuspid, tricuspid or complex with varying length and structure. Unique observations of this study include the consistent variation in glochidial release mechanisms among Australian subfamilies and New Zealand genera. Hyridellini species and Echyridella aucklandica (Gray and Dieffenbach, 1843) are released either freely or as “mesoconglutinates” (presumed brood lures), whereas Velesunioninae and Echyridella menziesii (Gray and Dieffenbach, 1843) release glochidia in “amorphous mucous conglutinates”. Hyridellini predominantly occur within perennially flowing rivers of coastal south-eastern Australia with generally low turbidity, whereas the Velesunioninae occur more typically in slower flowing, intermittent waters, many prone to extended periods of high turbidity. Thus, where Hyridellini occur, mesoconglutinates as visual brood lures may be a more efficient mechanism for infesting host fishes than the passive infestation strategy typical of velesunionine species frequenting more turbid waters. Finally, this study presents systematic descriptions of glochidia and a provisional key for identification of Australasian hyriid glochidia, making an important contribution to the current understanding of taxonomy and life history traits, both critical for hyriid conservation.

Managing and restoring faunal diversity across large areas requires an understanding of the roles of connectivity and dispersal in driving community patterns. We sought to determine the influence of connectivity, water regime, water source, geographical location, and dispersal traits on patterns of aquatic invertebrate diversity across a continent-wide arid biome. We compiled data on freshwater invertebrate assemblages from sites spanning the breadth of arid Australia. Univariate analyses (analysis of variance and rarefaction) revealed that alpha and gamma diversity across sites decreased as latitude increased. Multivariate analyses (ordination and analysis of similarity) revealed that community composition had considerable fidelity to geographic regions. Hydrological connectivity was strongly associated with riverine community composition although water rarely flowed (often less than annually). Hydrologically isolated sites (springs and rockholes) supported communities that were markedly dissimilar to hydrologically connected sites, and to each other. We investigated the influence of dispersal on diversity patterns by examining distance decay relationships for each of four dispersal trait groups (obligate aquatic and passive, weak, and strong aerial dispersers) on the basis of geodesic (shortest path) distances between pairs of sites and Mantel tests. We did not detect clear differences between dispersal traits and distance decay relationships at the continental scale, even for the two groups with the lowest dispersal ability (obligate aquatics and passive dispersers). Our results suggest that the loss of hydrological connectivity from water developments in arid lands (for example, the impoundment of intermittent rivers) is likely to affect macroinvertebrates. However, the exact flow mechanisms underlying such changes remain to be determined.

Alterations to the natural flow regime affect the structure and function of rivers and wetlands and contribute to loss of biodiversity worldwide. Although the effects of flow regulation have been relatively well studied, a lack of synthesis of the ecological consequences of low flows and droughts impedes research progress and our grasp of the mechanistic effects of human-induced water reductions on riverine ecosystems. We identified 6 ecologically relevant hydrological attributes of low flow (antecedent conditions, duration, magnitude, timing and seasonality, rate of change, and frequency) that act within the temporal hierarchy of the flow regime and a spatial context. We synthesized the literature to propose 4 principles that outline the mechanistic links between these low-flow attributes and the processes and patterns within riverine ecosystems. First, low flows control the extent of physical aquatic habitat, thereby affecting the composition of biota, trophic structure, and carrying capacity. Second, low flows mediate changes in habitat conditions and water quality, which in turn, drive patterns of distribution and recruitment of biota. Third, low flows affect sources and exchange of material and energy in riverine ecosystems, thereby affecting ecosystem production and biotic composition. Last, low flows restrict connectivity and diversity of habitat, thereby increasing the importance of refugia and driving multiscale patterns in biotic diversity. These principles do not operate in isolation, and many of the ecological pathways that are affected by low flows are likely to overlap or occur simultaneously, potentially resulting in synergistic and complex effects. Last, we outlined major human-induced threats to low-flow hydrology and how they act upon the ecologically relevant hydrological attributes of low flow to affect potential changes in riverine ecosystem integrity. The mechanistic links described in this synthesis can be used to develop and test hypotheses of low-flow hydrological–ecological response relationships in a cause–effect framework that will have value for both research and river flow management. Continued experimental research and ongoing consolidation of ecological information will improve our understanding and ability to predict consequences of low-flow alteration on river, floodplain, and estuarine ecosystems.

Understanding the determinants of species' distributions and abundances is a central theme in ecology. The development of statistical models to achieve this has a long history and the notion that the model should closely reflect underlying scientific understanding has encouraged ecologists to adopt complex statistical methods as they arise. In this paper we describe a Bayesian hierarchical model that reflects a conceptual ecological model of multi-scaled environmental determinants of riverine fish species' distributions and abundances. We illustrate this with distribution and abundance data of a small-bodied fish species, the Empire gudgeon Hypseleotris galii, in the Mary and Albert Rivers, Queensland, Australia. Specifically, the model sought to address; 1) the extent that landscape-scale abiotic variables can explain the species' distribution compared to local-scale variables, 2) how local-scale abiotic variables can explain species' abundances, and 3) how are these local-scale relationships mediated by landscape-scale variables. Overall, the model accounted for around 60% of variation in the distribution and abundance of H. galii. The findings show that the landscape-scale variables explain much of the distribution of the species; however, there was considerable improvement in estimating the species' distribution with the addition of local-scale variables. There were many strong relationships between abundance and local-scale abiotic variables; however, several of these relationships were mediated by some of the landscape-scale variables. The extent of spatial autocorrelation in the data was relatively low compared to the distances among sampling reaches. Our findings exemplify that Bayesian statistical modelling provides a robust framework for statistical modelling that reflects our ecological understanding. This allows ecologists to address a range of ecological questions with a single unified probability model rather than a series of disconnected analyses.