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The Kimberley marine environment in Western Australia is widely recognised for its outstanding natural features, vast and remote sea and landscapes, and Indigenous cultural significance. To ensure that adequate baseline information is available to understand, monitor and manage this remote and relatively understudied region, scientific exploration was undertaken between 2012 and 2018 as part of the Kimberley Marine Research Program (KMRP). Whilst this program generated significant amounts of new knowledge about the region, important research gaps remain, that if answered, should improve the capacity of managers to conserve the region's values more effectively. Here, we apply established participatory horizon scanning methods to draw on the expertise and understanding of 24 scientists and 18 managers (12 natural resource managers and 6 healthy country managers) involved in the KMRP, and assess their most essential remaining research needs for informing management of the region. Through this process, we identify a total of 184 research questions spanning seven themes: (i) habitats, (ii) fauna, (iii) ecological processes, (iv) pressures, (v) management, (vi) oceanography, and (vii) geomorphology. Of the 184 questions that formed the basis of this study, 29% related to the theme of ‘management’, followed by questions relating to ‘fauna’ (21%) and ‘pressures’ (20%). Questions assigned to the theme of ‘habitats’ (13%), ‘ecological processes’ (10%), and ‘oceanography’ (6%) were less common, whilst questions that related to ‘geomorphology’ only constituted 1% of all questions provided by study participants. Subtle differences in the types of questions posed by the scientist and manager groups were also evident, with questions relating to ‘ecological process’ and ‘oceanography’ overwhelmingly provided by scientists; questions in the themes ‘fauna’ and ‘management’ were mainly provided by Healthy Country Managers; and questions posed by natural resource managers were distribu

Coral reefs provide critical ecological and geomorphic (e.g. sediment production for reef-fronted shoreline maintenance) services, which interact in complex and dynamic ways. These services are under threat from climate change, requiring dynamic modelling approaches that predict how reef systems will respond to different future climate scenarios. Carbonate budgets, which estimate net reef calcium carbonate production, provide a comprehensive 'snap-shot' assessment of reef accretionary potential and reef stability. These budgets, however, were not intended to account for the full suite of processes that maintain coral reef services or to provide predictive capacity on longer timescales (decadal to centennial). To respond to the dual challenges of enhancing carbonate budget assessments and advancing their predictive capacity, we applied a novel model elicitation and review method to create a qualitative geo-ecological carbonate reef system model that links geomorphic, ecological and physical processes. Our approach conceptualizes relationships between net carbonate production, sediment transport and landform stability, and rates knowledge confidence to reveal major knowledge gaps and critical future research pathways. The model provides a blueprint for future coral reef research that aims to quantify net carbonate production and sediment dynamics, improving our capacity to predict responses of reefs and reef-fronted shorelines to future climate change.

Canopy-forming macroalgae can construct extensive meadow habitats in tropical seascapes occupied by fishes that span a diversity of taxa, life-history stages and ecological roles. Our synthesis assessed whether these tropical macroalgal habitats have unique fish assemblages, provide fish nurseries and support local fisheries. We also applied a meta-analysis of independent surveys across 23 tropical reef locations in 11 countries to examine how macroalgal canopy condition is related to the abundance of macroalgal-associated fishes. Over 627 fish species were documented in tropical macroalgal meadows, with 218 of these taxa exhibiting higher local abundance within this habitat (cf. nearby coral reef) during at least one life-history stage. Major overlap (40%–43%) in local fish species richness among macroalgal and seagrass or coral reef habitats suggest macroalgal meadows may provide an important habitat refuge. Moreover, the prominence of juvenile fishes suggests macroalgal meadows facilitate the triphasic life cycle of many fishes occupying diverse tropical seascapes. Correlations between macroalgal canopy structure and juvenile abundance suggests macroalgal habitat condition can influence levels of replenishment in tropical fish populations, including the majority of macroalgal-associated fishes that are targeted by commercial, subsistence or recreational fisheries. While many macroalgal-associated fishery species are of minor commercial value, their local importance for food and livelihood security can be substantial (e.g. up to 60% of landings in Kenyan reef fisheries). Given that macroalgal canopy condition can vary substantially with sea temperature, there is a high likelihood that climate change will impact macroalgal-associated fish and fisheries.

Western Australia’s coral reefs have largely escaped the chronic pressures affecting other reefs around the world, but are regularly affected by seasonal storms and cyclones, and increasingly by heat stress and coral bleaching. Reef systems north of 18°S have been impacted by heat stress and coral bleaching during strong El Niño phases and those further south during strong La Niña phases. Cumulative heat stress and the extent of bleaching throughout the northern reefs in 2016 were higher than at any other time on record. To assess the changing regime of disturbance to reef systems across Western Australia (WA), we linked their site-specific exposure to damaging waves and heat stress since 1990 with mean changes in coral cover. Since 2010, there has been a noticeable increase in heat stress and coral bleaching across WA. Over half the reef systems have been severely impacted by coral bleaching since 2010, which was further compounded by cyclones at some reefs. For most (75%) reef systems with long-term data (5–26 yrs), mean coral cover is currently at (or near) the lowest on record and a full recovery is unlikely if disturbances continue to intensify with climate change. However, some reefs have not yet experienced severe bleaching and their coral cover has remained relatively stable or increased in recent years. Additionally, within all reef systems the condition of communities and their exposure to disturbances varied spatially. Identifying the communities least susceptible to future disturbances and linking them through networks of protected areas, based on patterns of larval connectivity, are important research and management priorities in coming years while the causes of climate change are addressed.

In today’s complex, constantly evolving and innovation-supporting manufacturing systems, knowledge plays a vital role in sustainable manufacturing process planning and problem-solving, especially in the case of Computer-Aided Process Innovation (CAPI). To obtain formalized and promising process innovation knowledge under the open innovation paradigm, it is necessary to evaluate candidate knowledge and encourage improvement suggestions based on actual innovation situations. This paper proposes a process innovation-oriented knowledge evaluation approach using Multi-Criteria Decision-Making (MCDM) and fuzzy linguistic computing. Firstly, a comprehensive hierarchy evaluation index system for process innovation knowledge is designed. Secondly, by combining an analytic hierarchy process with fuzzy linguistic computing, a comprehensive criteria weighting determination method is applied to effectively aggregate the evaluation of criteria weights for each criterion and corresponding sub-criteria. Furthermore, fuzzy linguistic evaluations of performance ratings for each criterion and corresponding sub-criteria are calculated. Thus, a process innovation knowledge comprehensive value can be determined. Finally, an illustrative example of knowledge capture, evaluation and knowledge-inspired process problem solving for micro-turbine machining is presented to demonstrate the applicability of the proposed approach. It is expected that our model would lay the foundation for knowledge-driven CAPI in sustainable manufacturing.

Many serious ecosystem consequences of climate change will take decades or even centuries to emerge. Long-term ecological responses to global change are strongly regulated by slow processes, such as changes in species composition, carbon dynamics in soil and by long-lived plants, and accumulation of nutrient capitals. Understanding and predicting these processes require experiments on decadal time scales. But decadal experiments by themselves may not be adequate because many of the slow processes have characteristic time scales much longer than experiments can be maintained. This article promotes a coordinated approach that combines long-term, large-scale global change experiments with process studies and modeling. Long-term global change manipulative experiments, especially in high-priority ecosystems such as tropical forests and high-latitude regions, are essential to maximize information gain concerning future states of the earth system. The long-term experiments should be conducted in tandem with complementary process studies, such as those using model ecosystems, species replacements, laboratory incubations, isotope tracers, and greenhouse facilities. Models are essential to assimilate data from long-term experiments and process studies together with information from long-term observations, surveys, and space-for-time studies along environmental and biological gradients. Future research programs with coordinated long-term experiments, process studies, and modeling have the potential to be the most effective strategy to gain the best information on long-term ecosystem dynamics in response to global change.

Genetic (co)variances between body condition score (BCS), body weight (BW), milk yield, and fertility were estimated using a random regression animal model extended to multivariate analysis. The data analyzed included 81,313 BCS observations, 91,937 BW observations, and 100,458 milk test-day yields from 8725 multiparous Holstein-Friesian cows. A cubic random regression was sufficient to model the changing genetic variances for BCS, BW, and milk across different days in milk. The genetic correlations between BCS and fertility changed little over the lactation; genetic correlations between BCS and interval to first service and between BCS and pregnancy rate to first service varied from -0.47 to -0.31, and from 0.15 to 0.38, respectively. This suggests that maximum genetic gain in fertility from indirect selection on BCS should be based on measurements taken in midlactation when the genetic variance for BCS is largest. Selection for increased BW resulted in shorter intervals to first service, but more services and poorer pregnancy rates; genetic correlations between BW and pregnancy rate to first service varied from -0.52 to -0.45. Genetic selection for higher lactation milk yield alone through selection on increased milk yield in early lactation is likely to have a more deleterious effect on genetic merit for fertility than selection on higher milk yield in late lactation

Genetic (co)variances between body condition score (BCS), body weight (BW), milk production, and fertility-related traits were estimated. The data analyzed included 8591 multiparous Holstein-Friesian cows with records for BCS, BW, milk production, and/or fertility from 78 seasonal calving grass-based farms throughout southern Ireland. Of the cows included in the analysis, 4402 had repeated records across the 2 yr of the study. Genetic correlations between level of BCS at different stages of lactation and total lactation milk production were negative (-0.51 to -0.14). Genetic correlations between BW at different stages of lactation and total lactation milk production were all close to zero but became positive (0.01 to 0.39) after adjusting BW for differences in BCS. Body condition score at different stages of lactation correlated favorably with improved fertility; genetic correlations between BCS and pregnant 63 d after the start of breeding season ranged from 0.29 to 0.42. Both BW at different stages of lactation and milk production tended to exhibit negative genetic correlations with pregnant to first service and pregnant 63 d after the start of the breeding season and positive genetic correlations with number of services and the interval from first service to conception. Selection indexes investigated illustrate the possibility of continued selection for increased milk production without any deleterious effects on fertility or average BCS, albeit, genetic merit for milk production would increase at a slower rate

(Co)variance components for body condition score (BCS), body weight (BW), BCS change, BW change, and milk yield traits were estimated. The data analyzed included 6646 multiparous Holstein-Friesian cows with records for BCS, BW, and(or) milk yield at different stages of lactation from 74 dairy herds throughout Southern Ireland. Heritability estimates for BCS ranged from 0.27 to 0.37, while those for BCS change ranged from 0.02 to 0.10. Heritability estimates for BW records varied from 0.39 to 0.50, while heritabilities for BW change were similar to those observed for BCS change (0.03 to 0.09). The genetic correlations between BCS and BW at the same days in milk deviated little from 0.50, and the genetic correlations between BCS change and BW change over the same period ranged from 0.42 to 0.55. BCS and BW directly postpartum were both phenotypically and genetically negatively correlated with both BW change and BCS change in early lactation. The genetic correlations between BCS and milk yield were negative. The results of the present study show that animals that lose most BCS in early lactation tend to gain most BCS in late lactation, a trend also exhibited by BW.

Highway minitunnels, also referred to as limited facility tunnels, are small-diameter structures accessible only to light vehicles and with a typical headroom of 2.6 m. They may be used to segregate road users so as to maximise surface space for pedestrians and cyclists, to alleviate congestion hot-spots, to by-pass complex junctions or to improve interchange facilities for transferring from cars to public transport. Research to develop design guidelines has addressed a range of specific issues: possible construction methods, operational issues such as signs, and safety issues such as access for emergency services. A full-scale vehicle simulator has been used to examine the responses of drivers to a range of virtual minitunnels., Highway minitunnels, also referred to as limited facility tunnels, are small-diameter structures accessible only to light vehicles and with a typical headroom of 2.6 m. They may be used to segregate road users so as to maximise surface space for pedestrians and cyclists, to alleviate congestion hot-spots, to by-pass complex junctions or to improve interchange facilities for transferring from cars to public transport. Research to develop design guidelines has addressed a range of specific issues: possible construction methods, operational issues such as signs, and safety issues such as access for emergency services. A full-scale vehicle simulator has been used to examine the responses of drivers to a range of virtual minitunnels.