Our Museum Special Initiative: An Evaluation

Our Museum: Communities and Museums as Active Partners was a Paul Hamlyn Foundation Special Initiative 2012 – 2016. The overall aim was to influence the museum and gallery sector to:* Place community needs, values and active collaboration at the core of museum and gallery work* Involve communities and individuals in decision-making processes* Ensure that museums and galleries play an effective role in developing community skills and the skills of staff in working with communitiesThis was to be done through facilitation of organisational change in specific museums and galleries already committed to active partnership with communities.Our Museum offered a collaborative learning process through which institutions and communities shared experiences and learned from each other as critical friends. Our Museum took place at a difficult and challenging time for both museums and their community partners. Financial austerity led to major cutbacks in public sector expenditure; a search for new business models; growing competition for funding; and organisational uncertainty and staff volatility. At the same time, the debate at the heart of Our Museum widened and intensified: what should the purpose of longestablished cultural institutions be in the 21st century; how do they maintain relevance and resonance in the contemporary world; how can they best serve their communities; can they, and should they, promote cultural democracy

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem\u27s carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those ‘next users’ of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.</p

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Warming reduces net carbon gain and productivity in Medicago sativa and Festuca arundinacea

High temperature stress imposes constraints on the productivity of agricultural systems, such as pastures, and predicted increases in global temperatures are set to exacerbate these limitations. Here, we sought to understand the impact of warmer growth temperature on gas exchange and net primary productivity for two widely cultivated pasture species. We grew a C3 legume, Medicago sativa (lucerne), and a C3 grass, Festuca arundinacea Schreb (tall fescue), in a climate‐ controlled facility exposed to two temperature treatments (ambient: 26 °C, aT; elevated: 30 °C, eT). Soil water was maintained at non‐limiting conditions in both temperature treatments to control for the confounding effects of warming on soil moisture. We found that warming reduced photosynthetic capacity and increased leaf dark respiration (Rdark) in lucerne, while tall fescue showed little physiological change at the leaf level, but increased ecosystem respiration (Reco). Growth temperature had no significant impact on the thermal optimum of photosynthesis (Topt) or water use efficiency in either species. Both species exhibited significant reductions in productivity with warming; lucerne had greater reductions in shoot biomass, while tall fescue had greater reductions in root biomass. Our results highlight the potential for significant declines in pasture productivity associated with even modest increases in average temperature and highlights the need for suitable management strategies and implementation of more heat‐resistant cultivars. Improvements in photosynthetic performance for greater heat tolerance in lucerne, and traits associated with biomass allocation and root performance at higher temperatures in tall fescue, should be the focus for improving high temperature resistance in these plant species

Satellite-observed shifts in C3/C4 abundance in Australian grasslands are associated with rainfall patterns

Species composition is a key determinant of grassland ecosystem function and resilience. Climate change is predicted to alter the distribution of cool season (C3) and warm season (C4) grasses, however, the lack of spatial distributions and temporal variations of grass functional type information severely limits our understanding of climate impacts on grasslands. This study classified C3 and C4 grasses per pixel according to the peak of growing season generated from Enhanced Vegetation Index time series. From 2003 to 2017, the C3-C4 composition of Australian rain-fed grasslands and pastures was mapped at 500 m resolution on an annual basis across a wide geographical range (10°S – 45°S), and revealed extreme inter-annual fluctuations. Over the 15-year period, the satellite-derived ratio of C4 to C3 grasses significantly increased (p 3 and C4 grasses co-dominate. Our climate analysis indicated the inter-annual fluctuations of C4/C3 grass ratios were significantly associated (p 4 grasses and a decrease in the warm/cool season rainfall ratio favors C3 grasses. Our findings reveal spatially-detailed dynamics of grasslands and demonstrate large-scale grassland compositional changes over 15 years. The grass composition maps should help improve ecological forecasting of grass distributions and enable researches on grassland ecosystem responses to climate change that are relevant to both adaptation of rangeland agricultural and fire management practices. Our study should also help predict grass distribution under future climate conditions, and assist in the accurate modelling of global water, carbon, and energy exchanges between the land surface and atmosphere.</p

High safety margins to drought-induced hydraulic failure found in five pasture grasses

Determining the relationship between reductions in stomatal conductance (gs) and leaf water transport during dehydration is key to understanding plant drought responses. While numerous studies have analysed the hydraulic function of woody species, minimal research has been conducted on grasses. Here, we sought to characterize hydraulic vulnerability in five widely-occurring pasture grasses (including both C3 and C4 grasses) and determine whether reductions in gs and leaf hydraulic conductance (Kleaf) during dehydration could be attributed to xylem embolism. Using the optical vulnerability (OV) technique, we found that all species were highly resistant to xylem embolism when compared to other herbaceous angiosperms, with 50% xylem embolism (PX50) occurring at xylem pressures ranging from −4.4 to −6.1 MPa. We observed similar reductions in gs and Kleaf under mild water stress for all species, occurring well before PX50. The onset of xylem embolism (PX12) occurred consistently after stomatal closure and 90% reduction of Kleaf. Our results suggest that factors other than xylem embolism are responsible for the majority of reductions in gs and Kleaf during drought and reductions in the productivity of pasture species under moderate drought may not be driven by embolism

Green-up and brown-down : modelling grassland foliage phenology responses to soil moisture availability

Grassland responses to rainfall are characterised by leaf phenology, with greening and browning being highly sensitive to soil moisture. However, this process is represented overly simplistically in most vegetation models, limiting their capacity to predict grassland responses to global change factors. We derive functions representing grassland phenological responses to soil water content (SWC), by fitting an empirical model to greenness data. Data were obtained from fixed cameras (phenocams) monitoring phenology at several grassland experiments in Sydney, Australia. The data-model synthesis showed that the sensitivity of growth to SWC exhibited a concave-down response in most species. For senescence, we found a strong nonlinear increase in senescence rate with declining SWC. Both findings contradict common assumptions of growth and senescence in vegetation models. Incorporating nonlinear responses in the empirical model reduced the error in cover predictions by 7%. Model evaluation against data from drought treatments indicated that differential sensitivity of phenology to SWC helps explain differences among species’ responses to variable rainfall. Our work provides a new methodology, and new evidence, to support the development of improved representations of grassland phenology for vegetation models

Stomatal and non-stomatal limitations of photosynthesis for four tree species under drought : a comparison of model formulations

Drought strongly influences terrestrial C cycling via its effects on plant H2O and CO2 exchange. However, the treatment of photosynthetic physiology under drought by many ecosystem and earth system models remains poorly constrained by data. We measured the drought response of four tree species and evaluated alternative model formulations for drought effects on photosynthesis (A). We implemented a series of soil drying and rewetting events (i.e. multiple droughts) with four contrasting tree species in large pots (75 L) placed in the field under rainout shelters. We measured leaf-level gas exchange, predawn and midday leaf water potential (Ψpd and Ψmd), and leaf isotopic composition (δ13C) and calculated discrimination relative to the atmosphere (Δ). We then evaluated eight modeling frameworks that simulate the effects of drought in different ways. With moderate reductions in volumetric soil water content (θ), all species reduced stomatal conductance (gs), leading to an equivalent increase in water use efficiency across species inferred from both leaf gas exchange and Δ, despite a small reduction in photosynthetic capacity. With severe reductions in θ, all species strongly reduced gs along with a coincident reduction in photosynthetic capacity, illustrating the joint importance of stomatal and non-stomatal limitations of photosynthesis under strong drought conditions. Simple empirical models as well as complex mechanistic model formulations were equally successful at capturing the measured variation in A and gs, as long as the predictor variables were available from direct measurements (θ, Ψpd, and Ψmd). However, models based on leaf water potential face an additional challenge, as we found that Ψpd was substantially different from Ψsoil predicted by standard approaches based on θ. Modeling frameworks that combine gas exchange and hydraulic traits have the advantage of mechanistic realism, but sacrificed parsimony without an improvement in predictive power in this comparison. Model choice depends on the desired balance between simple empiricism and mechanistic realism. We suggest that empirical models implementing stomatal and non-stomatal limitations based on θ are highly predictive simple models. Mechanistic models that incorporate hydraulic traits have excellent potential, but several challenges currently limit their widespread implementation