Management of resources is often a large-scale task addressed using many small-scale interventions. The range of scales at which organisms respond to those interventions, along with the many outcomes which management aims to achieve can make determining the success of management complex. Environmental flow is an example of management where there is a recognized need for managers to demonstrate the impact of their actions by integrating different types of environmental responses. Here, we aim to support decision making in environmental management via the development of a new modelling framework (eFlowEval). It has the capacity to capture best-available knowledge, to scale it in space and time, explore interactions among species, compare scenarios, and account for uncertainty. Thus, it provides a basis for including multiple target groups in a common system. The framework is readily updatable as new information becomes available and can identify where data are insufficient to be scientifically robust.We demonstrate the eFlowEval framework using three very different environmental responses: 1) metabolism, which is a measure of the energy produced and then used in an ecosystem, 2) favorability for a bird species of interest (royal spoonbill Platalea regia), and 3) competing wetland plants (Centipeda cunninghamii and lippia Phyla canescens). These demonstrations illustrate the capability of the eFlowEval framework but the specific outputs shown here should not be used to assess environmental responses to management. Using these demonstrations, we illustrate the capacity of the eFlowEval framework to provide assessments across a range of scales (local to landscape) and from short time frames (weeks to months) to multi-year assessments. Further, we illustrate the ability to: i) scale responses from local to basin scales, ii) vary driver-response model types, iii) represent uncertainty, iv) compare scenarios, v) accommodate variable parameter values at different locations, and vi) incorporate spatial and temporal dependencies and dependencies among species. We also illustrate the framework's ability to capture inter- and intraspecific interactions and their impact in space and time.The eFlowEval framework extends the capacity of the component response models to provide novel modeling capabilities for management at scale. It allows for interactions among species or processes to be incorporated, as well as in space and time. A large degree of flexibility is offered by the framework, in terms of driver-response model types, input data, and aggregation methods. Thus, the eFlowEval framework provides a mechanism to enhance the transparency of environmental watering decision making, capture institutional knowledge, enhance adaptive management and undertake evaluation of the impact of environmental watering at a range of spatial and temporal scales.

Biotracers are commonly used in food-web studies to estimate consumer diets. Increasingly, multiple biotracer types are combined to provide more nuanced pictures of consumer resource use, unravel more complex diet mixtures, and improve the discriminatory power of mixing models. However, few studies compare different biotracer types, including the impact of tracer selection choices, and few methods exist for combining multiple types into a single analysis. We processed three biotracer types (stable isotopes, fatty acids, and amino acids) from the same samples to determine how common galaxias (Galaxias maculatus) and flathead gudgeon (Philypnodon grandiceps) utilize different basal resources (algae, macrophytes, and detritus) using Bayesian mixing models. We then combined subsets of different biotracer types by either combining them directly into one model using generalist priors (all possible two and three biotracer type combinations) or informative priors based on other biotracer types. We compared our mixing model results with independent food webs constructed from gut contents to assess accuracy. We found fatty acids gave the most accurate diet estimates, amino acid models were the least accurate, and stable isotope models did not converge. Model precision tended to increase with the number of individual tracers included (with exceptions). Adding biotracer types that produced similar diet estimates in their respective models tightened the posterior probability distributions of combined models, while adding ones that disagreed expanded those distributions, as expected. However, tracer selection and the combination of tracer sets must be carefully considered, as they can dramatically affect model accuracy. We also demonstrate the utility of a complementary method that combines information from multiple biotracers using informative priors based on other biotracer types. Overall, our work shows that choices made when constructing mixing models can greatly influence resultant diet estimates, and we provide heuristics for making those choices, so they are most appropriate for an individual study's objectives and available data.

Methane production by livestock is a substantial component of greenhouse gas emissions worldwide. The marine red algae, Asparagopsis taxiformis, has been identified as a possible supplement in livestock feeds due to its potent inhibition of methane production but currently is unable to be produced at scale. Finding additional taxa that inhibit methane production is therefore desirable. Here we provide foundational evidence of methanogenesis-inhibiting properties in Australian freshwater plants and algae, reviewing candidate species and testing species' chemical composition and efficacy in vitro. Candidate plant species and naturally-occurring algal mixes were collected and assessed for ability to reduce methane in batch testing and characterised for biochemical composition, lipids and fatty acids, minerals and DNA. We identified three algal mixes and one plant (Montia australasica) with potential to reduce methane yield in in vitro batch assay trials. All three algal mixes contained Spirogyra, although additional testing would be needed to confirm this alga was responsible for the observed activity. For the two samples that underwent multiple dose testing, Algal mix 1 (predominantly Spirogyra maxima) and M. australasica, there seems to be an optimum dose but sources, harvesting and storage conditions potentially determine their methanogenesis-inhibiting activity. Based on their compositions, fatty acids are likely to be acting to reduce methane in Algal mix 1 while M. australasica likely contains substantial amounts of the flavonoids apigenin and kaempferol, which are associated with methane reduction. Based on their mineral composition, the samples tested would be safe for livestock consumption at an inclusion rate of 20%. Thus, we identified multiple Australian species that have potential to be used as a feed supplement to reduce methane yield in livestock which may be suitable for individual farmers to grow and feed, reducing complexities of supply associated with marine alternatives and suggesting avenues for investigation for similar species elsewhere.

Disease can be a powerful driver of population and community dynamics, as well as evolutionary processes. Disease is also emerging at increasing rates, resulting in massive impacts on populations, communities, and ecosystems. However, assessing these impacts requires foundational knowledge of disease agents and hosts, which is often lacking, particularly in aquatic insects. We describe a recent disease outbreak in caddisflies, suggesting potential consequences for population and community dynamics of the host. We use a series of complementary studies to develop a cohesive foundation of information about this disease, including identification using genomic methods, observational prevalence studies, laboratory experiments to establish transmissibility and fitness consequences, and laboratory and field investigations to infer transmission mechanisms. We identified the infection as being caused by the oomycete Saprolegnia-the first time this parasite has been noted in insect eggs. Prevalence surveys found high prevalence (up to 36%) with variation across space, time, and host species. We demonstrated increasing egg mortality with increasing infection within an egg mass (every 10% increase in infection rate doubles odds of mortality), thereby confirming disease. We established transmissibility and show that transmission occurs through both direct contact with infected egg masses and from background sources, which probably interact to create complex patterns of disease. Taken together, our findings show that conditions necessary for population and community consequences are present. Specifically, increased mortality rates almost certainly occurred during the outbreak, yielding lower larval numbers and potentially altering community interactions. Transmission by contact between egg masses combined with observed species-specific prevalence suggest shifts in the relative performance of different species because of interactions between host and parasite life histories. Outside extreme examples such as chytrid fungus, disease has traditionally received less interest than resource competition or predation in community ecology, although disease ecology is advancing rapidly. One major hurdle is a lack of foundational knowledge characterising disease processes in natural communities, particularly in aquatic insects. Our findings highlight the importance of investigating diseases in insect eggs and provide the foundation for further investigations of how these processes play out at the population and community scale.

2019 Annual Forum presentation - overview of the research delivered over the five year EWKR project

Environmental watering is frequently used to achieve specific ecological objectives, such as triggering spawning or seed germination. These short-term objectives are often met, but longer-term objectives, such as population growth, may not be, especially where multiple hydrological and non-hydrological factors influence success. We propose a framework to identify these factors in space and time. Our framework steps users through identifying possible inhibiting (strictures) and supporting (promoters) factors, and placing these factors in their spatial and temporal context. This allows users to identify potential limiting factors that may require additional intervention, or render the original watering action unsustainable. We illustrate the framework with examples of a floodplain tree (black box, Eucalyptus largiflorens), colonial nesting waterbird (royal spoonbill, Platalea regia) and large-bodied migratory fish (golden perch, Macquaria ambigua). The framework explores strictures and promoters for major life-history stages, emphasising the need to support and protect all stages if objectives include population maintenance or growth. In this way, the framework can document existing mental models and can be used as the basis of a risk portfolio, a prioritisation tool or future quantitative models. Thus, the framework enables individual management actions to be better grounded in a broader context, increasing the likelihood of achieving long-term ecological objectives.

Oviposition substrata are a crucial resource for many stream-dwelling insects and may have a strong effect on population densities. From February to March 2010, we conducted a large-scale experiment manipulating the density of oviposition substrata available to two taxa, Cheumatopsyche spp. and Ecnomus spp. in Hughes Creek (south-east Australia). These caddisflies oviposit on hard surfaces underwater. Hughes Creek has a sandy bed, and females rely predominantly on bark and wood as oviposition substrata. Bark density was manipulated in 25-m-long sites, creating a range of bark surface areas (SAs) spanning an order of magnitude, with appropriate controls. Estimates of the number of egg masses and bark SAs were obtained 22 and 55days after the experiment commenced in each site. To characterise taxon-specific oviposition site preferences and test whether preferences were dependent on overall bark availability, the conditions (velocity and emergence) of individual substrata were manipulated within sites. Egg masses were enumerated at approximately weekly intervals for 7weeks. We found a strong relationship between the SA of bark at sites and the number of masses of Ecnomus spp., demonstrating that oviposition is limited by substrata availability. In contrast, the number of Cheumatopsyche spp. egg masses was not related to the total amount of bark available. Ecnomus spp. showed a weak preference for emergent compared to submerged bark, but did not respond to water velocity. Cheumatopsyche laid eggs predominantly in fast flows, regardless of bark emergence, which may explain the lack of a site-level response because only a small proportion of bark occurred in fast flows even when bark was plentiful. Our results suggest that the strength of oviposition preferences may depend on overall background densities of substrata. Oviposition preferences and substrata availability interact to set the initial distribution (and density) of the next generation. Our study has wide implications for the management of streams with soft sediment beds, where bark and wood inputs from riparian vegetation provide not only food and habitat for larvae but also oviposition substrata that are critical to successful recruitment for some taxa.