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Environmental decision support systems (EDSS) are designed to assist natural resource managers and stakeholders to assess problems and select options for change. EDSS that combine community engagement in developing future scenarios with computer‐based land use planning and modelling tools are widely used internationally. However, these EDSS are often not used after the research and development phase. To best understand why the EDSS are not being used in the long term, the end users of the EDSS should be consulted—a perspective that is lacking in the literature. The research reported here presents the perspectives of stakeholders involved in a community climate change adaptation project in western Canada. Evidence from the community suggests that this project was successful in instigating change. However, the EDSS was not used after the project's end. Our findings indicate that, from the end users' perspective, the project could have had much greater and sustained success had there been ongoing engagement and communication with them, particularly in the form of continued support for the use of EDSS after the development project. [ABSTRACT FROM AUTHOR]

Highlights • Woodland was a net C source in dry summers, a net C sink in moist summers. • Dry summer decreased both maximum C flux rate and total hours of net carbon uptake. • Air temperature did not affect the time for NEP rates reaching to the maximum. • Ecosystem water use efficiency (WUE) was higher in moist than dry summers. • Low summer rainfall reduced NEP and WUE in the following autumn. Abstract Biological activity in semi-arid and arid ecosystems is strongly dependent on rainfall, particularly in summer. A period of favourable rainfall can alter ecosystem carbon balance and is likely influence inner-annual variability of the regional and global carbon cycle. The effect of rainfall variability on ecosystem carbon and water fluxes in semi-arid ecosystems, particularly in woody ecosystems has not been adequately investigated. In this study, we used eddy covariance data from four springs (September–November), four summers (December of that year–February of the following year) and three following autumns (March–May) between 2010 and 2013 in a semi-arid woodland of southern Australia to better understand the effect of pre-summer, summer and post-summer rainfall variability on diurnal pattern of carbon flux. In 2010/11 summer, La Niῆa conditions resulted in extensive rainfall, which marked an historic record over the last 100 years. The 2011/12 summer was also moist. In contrast, the two following summers (2012/13 and 2013/14) were dry. Cumulative net ecosystem productivity (NEP) was lower in dry summers than in moist summers, due to lower maximum carbon flux rate and total hours of net carbon uptake. Maximum NEP and gross primary productivity rates on a given day were reached earlier in dry summers, indicating that photosynthetic activity was not suppressed by high temperatures but by water availability. Ecosystem water use efficiency, calculated as the ratio of daily NEP to evapotranspiration, was higher in moist than dry summers. In addition, the effect of summer rain extended into the following autumn. Cumulative NEP and ecosystem water use efficiency in autumn following a dry summer were lower than when following a moist summer. We conclude that summer rainfall has a strong impact on the carbon cycle in semi-arid woodlands due to its direct and carry-over effect. Therefore seasonal rainfall variation is likely to determine inter-annual variability of annual net carbo uptake of this ecosystem. [ABSTRACT FROM AUTHOR]

Semi-arid climate is characterized by long dry periods which are interrupted by rainfall events differing in magnitude. The effect of these rainfall events on ecosystem carbon fluxes has been studied in semi-arid grass and shrublands, but data for woodlands is lacking. In this study net ecosystem productivity (NEP), partitioned ecosystem respiration (Reco) and gross primary productivity (GPP) in a semi-arid eucalyptus woodland were measured using eddy covariance data. Four natural large rainfall events with similar magnitude (35–60 mm), but contrasting previous rainfall patterns (several moderate rainfall events vs. limited or no rainfall) were chosen. NEP, Reco and GPP rates 28 days prior to and 35 days after the three central rainfall events were used. Prior rainfall patterns influenced ecosystem carbon fluxes after the central rainfall event. GPP rates were not affected by the four rainfall events. After four weeks with several medium to large rainfall events, the central rainfall event had little effect on Reco. In contrast, a large rainfall event following four weeks with very little rainfall induced an increase in Reco for about three weeks and thus a decrease in NEP. The strong increase in Reco after the central rainfall event can, at least partly, be explained by an increase in soil respiration upon rewetting. A water addition experiment (30 mm rainfall simulation) conducted in the field following a long dry period (only 4.8 mm rainfall input in 45 days) showed that heterotrophic soil respiration usually decreases rapidly after rewetting. In the sandy soil of the study area, the top 0–5 cm dry within a few days after rainfall, but at 10 cm depth the soil remained moist for several weeks after the large rainfall event that followed a long dry period. Therefore, sustained higher Reco following the large rainfall event could be due to respiration of roots in the moist deeper soil layers. We conclude that the previous rainfall should be considered when interpreting the response of ecosystem C fluxes to rainfall events which could alter ecosystem carbon balance and may potentially affect seasonal or inter-annual variability of ecosystem carbon uptake. [ABSTRACT FROM AUTHOR]

The importance of arid and semi-arid ecosystems for global net carbon uptake has recently been highlighted. More information about the drivers of carbon fluxes in these ecosystems is required to advance our understanding of the contribution of dry ecosystems to the global carbon budget. In this study, eddy covariance flux data was used to calculate net ecosystem productivity (NEP), gross primary productivity (GPP) and ecosystem respiration (Reco) in a semi-arid woodland on sandy soil. In January 2014 a wildfire severely damaged the area around the flux tower, burning trees and spinifex and consuming aboveground bark and leaf litter. The flux tower recorded data for one year before the fire (January–December 2013) and more than one year after the fire (May 2014–July 2015). Soil respiration was measured in-situ monthly after the fire (July 2014–June 2015), in burnt and unburnt areas under Eucalyptus tree canopy and inter-canopy representing 25 and 75% of the area, respectively. Before the fire the ecosystem was a net carbon sink, sequestering 81 g C m −2 yr −1 in 2013, but became a carbon source after the fire. Reco and GPP declined by about 35% and 65%, respectively, after the fire. Net carbon uptake resumed 12–15 months after the fire with NEP approaching values similar to those before the fire. Soil respiration was significantly higher under tree canopies (1.5 μmol CO 2 m −2 s −1 ) than in inter-canopy areas (0.9 μmol CO 2 m −2 s −1 ). Soil respiration was mainly driven by soil water content and thus magnitude and distribution of precipitation, but was not influenced by the wildfire. Accounting for differences in area, soil respiration from inter-canopy and under canopy contributed 51 and 32% to total ecosystem respiration. It can be concluded that carbon flux in this semi-arid woodland was strongly influenced by precipitation and wildfire, with net carbon uptake of the ecosystem beginning approximately one year after the fire. [ABSTRACT FROM AUTHOR]

Examines the generation of consanguineous redox families from the conjugal heterobimetallic butadiynediyl complexes. Communication between the iron and rhenium endgroups; Impact of oxidation on the electronic structure; Effect of temperature on the degree of magnetic interaction; Characteristics of nonsymmetrical conjugal systems.

• Recovery of NEP, GPP and Reco four-year post wildfire was investigated. • The woodland was a C source for the first 1.5 years, but a C sink afterwards. • Full recovery of NEP was estimated to be within three years post-fire. • GPP and Reco rates were still low after four years indicating the extended fire impact. • Regrown trees may be more susceptible to rain variability than mature trees. Altered precipitation regimes and increased temperatures can enhance wildfire risk, particularly in semi-arid and arid ecosystems. Since these ecosystems occupy a third of the earth's land area, the immediate loss of carbon and the post fire reduction in carbon sequestration will significantly affect regional and global carbon budgets. However, there are few studies that quantify the recovery of ecosystem carbon production post fire in semi-arid ecosystems. In January 2014, a wildfire caused severe loss and damage to plants in a semi-arid Eucalyptus woodland in South Australia. The carbon flux of the woodland was monitored pre- and post-fire from an in-situ eddy covariance flux tower. Daily net ecosystem production (NEP), ecosystem respiration (Reco) and gross primary production (GPP), together with environmental variables collected in 2012 and 2013 (pre-fire) were used to generate machine learning regression algorithms. Subsequently, the algorithms were used to simulate Reco, GPP and NEP at the same site without fire from the environmental variables, which is referred to as modelled carbon fluxes. Changes in the difference between the modelled fluxes and the actual post-fire measured fluxes were used to investigate the recovery of Reco, GPP and NEP during four years after the fire (April 2014–March 2018). We found that the woodland was a carbon source throughout the first year and in the hot and dry months of the second year, but was a carbon sink in the third and fourth year after the fire. The recovery of NEP to pre-fire levels was estimated to take approximately 35 months (30–43 months at 95% confidence interval). Post fire measured GPP responded more strongly to rainfall events than indicated by the modelled values which suggests that carbon sequestration by new leaf growth is more responsive to rainfall than equivalent mature leaf area of this woodland. After four years, both measured Reco and GPP rates were still lower than modelled rates indicating that the mass of carbon and its turnover in the ecosystem was not yet at pre-fire levels. We conclude that full recovery from fire in this woodland, and likely in similar ecosystems, is strongly influenced by the incident rainfall regime after fire and will take five years or more, especially if total annual rainfall is less than the long term average. [ABSTRACT FROM AUTHOR]

• Decades with more drought years have a potential 25% reduction in average annual profit. • Greater risks to irrigation enterprises may come from large increases in variability of returns and large loss-making years. • Decadal average returns compared across climate change scenarios, consider long run viability under a changing climate. The Interactive Land use Strategic Assessment (ILSA) tool allows irrigators to examine and compare the likely effects of a range uncertain future climates on their individual enterprise along multiple time frames. The scientific basis of the tool is predicated on the influence of the prevailing climate conditions on expected levels of water allocations for irrigation activities under multiple climate scenarios. The model reports both annual returns and ten year average annual expected returns, given probability weighted allocations for a selected decade and climate scenario. Irrigators are able to adjust default farm operational parameters to suit their particular circumstances and examine the expected returns across multiple possible future water availability and market price years. A case study in the Loxton irrigation district of Southern Australia demonstrates the models capability examining the effects climate change, climatic variability, and water trade have on irrigation operations in a manner that is understandable to irrigators. [ABSTRACT FROM AUTHOR]

Abstract Quantifying the water quantity and quality variations resulting from human induced activities is important for policy makers in view of increasing water scarcity and water pollution. Simple models can be robust tools in estimating the runoff from catchments, but do they also sufficiently reflect complex physio-chemical processes required for spatially-explicit simulation of soil-water interactions, and the resulting pollutant responses in catchments? Do these models respond sensitive to the impacts of different land use change representations? These questions are considered by applying the semi-distributed process-based catchment models SWAT and SOURCE to the Sixth Creek catchment in South Australia. Both models used similar data whereas inputs for SOURCE were generated from land-use based Functional Units (FUs), while FUs for SWAT were based on land use, soil and slope combinations. After satisfying calibration of both models for the outlet station of the catchment, the simulated flow by SOURCE produced high goodness of fit metrics, while nutrient loads simulated by SWAT were more realistic. Both models benefitted from using locally available Potential Evapotranspiration data for calibrating the hydrology. Scenarios of intensified land uses by two models showed more credible results for sediment and nutrient loads with the static approach when simulating the linear rather than the non-linear land use changes. The study has shown that informing decisions on the hydrology at catchment scale is well suited to less-complex models, whereas decisions on impact of land use change on water quality in catchments are better suited by models with process descriptions for soil-water interactions. Graphical abstract Unlabelled Image Highlights • The less complex model SOURCE provided a quick and robust estimation of streamflow. • The more complex model SWAT simulated nutrient loads more realistically. • Both models predict plausible trends of flow and pollutants under land use changes. • Static representation of non-linear change causes overestimation of pollution loads. [ABSTRACT FROM AUTHOR]

Sustainable management of drinking water reservoirs requires taking into account the potential effects of their catchments' development. This study is an attempt to estimate the daily patterns of nutrients transport in the catchment – reservoir systems through the application of the ensemble of complementary models SWAT-SALMO. SWAT quantifies flow, nitrate and phosphate loadings originating in catchments before entering downstream reservoirs meanwhile SALMO determines phosphate, nitrate, and chlorophyll-a concentrations within the reservoirs. The study applies to the semi-arid Millbrook catchment-reservoir system that supplies drinking water to north-eastern suburbs of Adelaide, South Australia. The catchment hosts viti- and horticultural land uses. The warm-monomictic, mesotrophic reservoir is artificially aerated in summer. After validating the simulation results for both Millbrook catchment and reservoir, a comprehensive scenario analysis has been conducted to reveal cascading effects of altered management practices, land uses and climate conditions on water quality in the reservoir. Results suggest that the effect on reservoir condition in summer would be severe, most likely resulting in chlorophyll-a concentrations of greater than 40 μg/l if the artificial destratification was not applied from early summer. A 50% curbing of water diversion from an external pipeline to the catchment will slightly limit chlorophyll-a concentrations by 1.22% as an effect of reduced inflow phosphate loads. The simulation of prospective land use scenarios converting 50% of present pasture in the Millbrook catchment into residential and orchards areas indicates an increase of summer chlorophyll-a concentrations by 9.5–107.9%, respectively in the reservoir. Global warming scenarios based on the high emission simulated by SWAT-SALMO did result in earlier growth of chlorophyll-a but overall the effects on water quality in the Millbrook reservoir was not significant. However scenarios combining global warming and land use changes resulted in significant eutrophication effects in the reservoir, especially in the unmanaged condition with stratification in summer. This study has demonstrated that complementary model ensembles like SWAT–SALMO allow to comprehend more realistically cascading effects of distinct catchment processes on internal reservoir's processes, and facilitate integrated management scenarios. [ABSTRACT FROM AUTHOR]

Environmental management and regional land use planning has become more complex in recent years as growing world population, climate change, carbon markets and government policies for sustainability have emerged. Reforestation and agroforestry options for environmental benefits, carbon sequestration, economic development and biodiversity conservation are now important considerations of land use planners. New information has been collected and regionally-calibrated models have been developed to facilitate better regional land use planning decisions and counter the limitations of currently available models of reforestation productivity and carbon sequestration. Surveys of above-ground biomass of 264 reforestation sites (132 woodlots, 132 environmental plantings) within the agricultural regions of South Australia were conducted, and combined with spatial information on climate and soils, to develop new spatial and temporal models of plant density and above-ground biomass productivity from reforestation. The models can be used to estimate productivity and total carbon sequestration (i.e. above-ground + below-ground biomass) under a continuous range of planting designs (e.g. variable proportions of trees and shrubs or plant densities), timeframes and future climate scenarios. Representative spatial models (1 ha resolution) for 3 reforestation designs (i.e. woodlots, typical environmental planting, biodiverse environmental plantings) × 3 timeframes (i.e. 25, 45, 65 years) × 4 possible climates (i.e. no change, mild, moderate, severe warming and drying) were generated (i.e. 36 scenarios) for use within land use planning tools. [ABSTRACT FROM AUTHOR]

Global evaporation monitoring from Earth observation thermal infrared satellite missions is historically challenged due to the unavailability of any direct measurements of aerodynamic temperature. State‐of‐the‐art one‐source evaporation models use remotely sensed radiometric surface temperature as a substitute for the aerodynamic temperature and apply empirical corrections to accommodate for their inequality. This introduces substantial uncertainty in operational drought mapping over complex landscapes. By employing a non‐parametric model, we show that evaporation can be directly retrieved from thermal satellite data without the need of any empirical correction. Independent evaluation of evaporation in a broad spectrum of biome and aridity yielded statistically significant results when compared with eddy covariance observations. While our simplified model provides a new perspective to advance spatio‐temporal evaporation mapping from any thermal remote sensing mission, the direct retrieval of aerodynamic temperature also generates the highly required insight on the critical role of biophysical interactions in global evaporation research. Plain Language Summary: Water lost by plants through evaporation is strongly linked with the temperature at an unknown height within the canopy. Because this in‐canopy temperature cannot be typically measured by a satellite, the majority of the global evaporation models substitute this with skin temperature, or the near‐surface temperature observed by the satellite sensors. Such methods do not fully capture the physical and biological processes governing the magnitude and variability of plant water use under severe water stress, leading to substantial errors in water cycle monitoring in the dry regions. Here, we show how a simple model that requires no anticipated parameter, provides not only reasonable estimates of evaporation in a variety of dry and wet conditions, but also a better insight into the role of plant water stress and greenness in the difference between the in‐canopy temperature and skin temperature. This model offers an alternative and novel perspective that can be used in images from current and future thermal satellite missions to advance global plant water use mapping for several water management applications and to investigate the highly complex land‐atmosphere interactions and feedback mechanisms. Key Points: Aerodynamic temperature and evaporation well estimated from physical principles and available energy‐water limits in different ecosystemsWater stress and vegetation cover influences the difference between aerodynamic and radiometric temperatures through plant homeostasisNon‐parametric model offers a parameter‐sparse approach describing evaporation, canopy conductance and vapor pressure deficit relationship [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP) plays a critical role in the regulation of photosynthesis, evapotranspiration, and energy fluxes. Significant progress has been made in extracting LSP information over large areas using satellite data, yet LSP retrievals remain a challenge over vast arid and semi-arid ecosystems because of sparse greenness, high variability and the lack of distinct annual patterns; for example, the MODerate Imaging Spectrometer (MODIS) Land Cover Dynamics Product MCD12Q2 that provides LSP metrics globally often failed to provide LSP information in these ecosystems. In this study, we used a modified threshold algorithm to extract LSP timing metrics, including the start, peak, and end of growing seasons, using the 16-day composite Enhanced Vegetation Index (EVI) time series from MODIS data. We applied this regionally customized algorithm across all arid and semi-arid climate regions of Australia (75% of the continental land area) encompassing shrublands, grasslands, savannas, woodlands, and croplands, extracting LSP metrics annually from 2003 to 2018, with up to two (phenology) seasons accounted for in each year. Our algorithm yielded an average of 64.9% successful rate of retrieval (proportion of pixels with retrieved LSP metrics) across 16 years in Arid and Semi-arid AUStralia (AS-AUS), which was a significant increase compared to the 14.5% rate of retrieval yielded in our study area by the global product and the major cause of the different performances between these two approaches was the different EVI amplitude restrictions utilized to avoid spurious peaks (i.e. EVI amplitude ≥ 0.1 used by the global product and peak EVI ≥ time series average EVI used by our algorithm). Gross primary productivity (GPP) measurements at OzFlux eddy covariance (EC) tower sites were used to cross-compare with the presence/absence of growing seasons detected by our algorithm, and 97% of our retrieved seasons matched with those extracted using EC data. Preliminary tests at five OzFlux sites showed that our algorithm was robust to view angle-induced sensitivity of the input data and showed similar performance when using EVI data calculated using MODIS Nadir BRDF-Adjusted Reflectance product. Our retrieved LSP metrics revealed that vegetation growth in arid ecosystems is highly irregular and can occur at any time of the year, more than once in a year, or can skip a year. The proportion of pixels with two growing seasons was found to be correlated with the average annual precipitation of the study area (p < 0.01), providing an estimation approach of LSP via rainfall. Our study improves the detection and measurement of vegetation phenology in arid and semi-arid regions by improving the spatial extend of LSP retrievals, which contributes to studies on LSP variations and dryland ecosystem resilience to climate change. More evaluation is planned for future work to assess and further improve the accuracy of the retrieved LSP metrics. [ABSTRACT FROM AUTHOR]

Abstract: We report in this communication the synthesis and characterization of two Fe/Re heterodinuclear complexes 3 n of formula (η5-C5Me5)Re(NO)(PPh3)(Clic> n (η2-dppe)Fe(η5-C5Me5) (n =3, 4) as well as the hexacarbonyl dicobalt adduct (4) of the hexatriynediyl complex 33 . We show by cyclic voltammetry that the “electronic communication” between the organometallic endgroups and thereby the thermodynamic stability of the corresponding mixed-valent (MV) parent 3 n + is strongly influenced by bridge extension or by complexation of the [Co2(CO)6] fragment. In the case of the hexatriynediyl complex, the MV complex 33 + or 4 can be isolated by performing the chemical oxidation of 33 at low temperature. Spectroscopic studies of this compound and of other stable oxidized redox congeners should now help us to unravel how bridge extension modifies the electronic communication between the different redox-active endgroups in this family of unsymmetrically-substituted polyynediyl compounds. [Copyright &y& Elsevier]

Irrigation development induces considerable environmental change, but the expectation has been in the past that the economic and social benefits would be greater than the environmental costs. However, public attitudes change over time from acceptance of development and exploitation to greater concern regarding environmental issues and sustainability. Recently, the irrigation industry has found it difficult to communicate to the wider populace the regional benefits of irrigation and the current activities and investment undertaken to address the environmental sustainability concerns. To address this, irrigation water supply businesses are investigating using a broader reporting structure that includes financial, environmental, and social and cultural elements. This triple bottom line, holistic approach should provide a more balanced view of water use with socio-economic benefits and environmental consequences demonstrated. It is anticipated that this approach embedded in the newly developed Irrigation Sustainability Assessment Framework will lead to a more transparent and informed debate on the sustainable use of resources between all parties. [ABSTRACT FROM AUTHOR]

Summary: The ratio of leaf intercellular to ambient CO2 (χ) is modulated by stomatal conductance (gs). These quantities link carbon (C) assimilation with transpiration, and along with photosynthetic capacities (Vcmax and Jmax) are required to model terrestrial C uptake. We use optimization criteria based on the growth environment to generate predicted values of photosynthetic and water‐use efficiency traits and test these against a unique dataset.Leaf gas‐exchange parameters and carbon isotope discrimination were analysed in relation to local climate across a continental network of study sites. Sun‐exposed leaves of 50 species at seven sites were measured in contrasting seasons.Values of χ predicted from growth temperature and vapour pressure deficit were closely correlated to ratios derived from C isotope (δ13C) measurements. Correlations were stronger in the growing season. Predicted values of photosynthetic traits, including carboxylation capacity (Vcmax), derived from δ13C, growth temperature and solar radiation, showed meaningful agreement with inferred values derived from gas‐exchange measurements. Between‐site differences in water‐use efficiency were, however, only weakly linked to the plant's growth environment and did not show seasonal variation.These results support the general hypothesis that many key parameters required by Earth system models are adaptive and predictable from plants' growth environments. [ABSTRACT FROM AUTHOR]

Abstract: Plant species show considerable leaf trait variability that should be accounted for in dynamic global vegetation models (DGVMs). In particular, differences in the acclimation of leaf traits during periods more and less favourable to growth have rarely been examined. We conducted a field study of leaf trait variation at seven sites spanning a range of climates and latitudes across the Australian continent; 80 native plant species were included. We measured key traits associated with leaf structure, chemistry and metabolism during the favourable and unfavourable growing seasons. Leaf traits differed widely in the degree of seasonal variation displayed. Leaf mass per unit area (Ma) showed none. At the other extreme, seasonal variation accounted for nearly a third of total variability in dark respiration (Rdark). At the non‐tropical sites, carboxylation capacity (Vcmax) at the prevailing growth temperature was typically higher in summer than in winter. When Vcmax was normalized to a common reference temperature (25°C), however, the opposite pattern was observed for about 30% of the species. This suggests that metabolic acclimation is possible, but far from universal. Intraspecific variation—combining measurements of individual plants repeated at contrasting seasons, different leaves from the same individual, and multiple conspecific plants at a given site—dominated total variation for leaf metabolic traits Vcmax and Rdark. By contrast, site location was the major source of variation (53%) for Ma. Interspecific trait variation ranged from only 13% of total variation for Vcmax up to 43% for nitrogen content per unit leaf area. These findings do not support a common practice in DGVMs of assigning fixed leaf trait values to plant functional types. Trait‐based models should allow for interspecific differences, together with spatial and temporal plasticity in leaf structural, chemical and metabolic traits. A plain language summary is available for this article. [ABSTRACT FROM AUTHOR]

Mediterranean catchments experience already high seasonal variability alternating between dry and wet periods, and are more vulnerable to future climate and land use changes. Quantification of catchment response under future changes is particularly crucial for better water resources management. This study assessed the combined effects of future climate and land use changes on water yield, total nitrogen (TN) and total phosphorus (TP) loads of the Mediterranean Onkaparinga catchment in South Australia by means of the eco-hydrological model SWAT. Six different global climate models (GCMs) under two representative concentration pathways (RCPs) and a hypothetical land use change were used for future simulations. The climate models suggested a high degree of uncertainty, varying seasonally, in both flow and nutrient loads; however, a decreasing trend was observed. Average monthly TN and TP load decreased up to − 55% and − 56% respectively and were found to be dependent on flow magnitude. The annual and seasonal water yield and nutrient loads may only slightly be affected by envisaged land uses, but significantly altered by intermediate and high emission scenarios, predominantly during the spring season. The combined scenarios indicated the possibility of declining flow in future but nutrient enrichment in summer months, originating mainly from the land use scenario, that may elevate the risk of algal blooms in downstream drinking water reservoir. Hence, careful planning of future water resources in a Mediterranean catchment requires the assessment of combined effects of multiple climate models and land use scenarios on both water quantity and quality. [ABSTRACT FROM AUTHOR]

The economics of establishing perennial species as renewable energy feedstocks has been widely investigated as a climate change adapted diversification option for landholders, primarily using net present value (NPV) analysis. NPV does not account for key uncertainties likely to influence relevant landholder decision making. While real options analysis (ROA) is an alternative method that accounts for the uncertainty over future conditions and the large upfront irreversible investment involved in establishing perennials, there have been limited applications of ROA to evaluating land use change decision economics and even fewer applications considering climate change risks. Further, while the influence of spatially varying climate risk on biomass conversion economic has been widely evaluated using NPV methods, effects of spatial variability and climate on land use change have been scarcely assessed with ROA. In this study we applied a simulation-based ROA model to evaluate a landholder's decision to convert land from agriculture to biomass. This spatially explicit model considers price and yield risks under baseline climate and two climate change scenarios over a geographically diverse farming region. We found that underlying variability in primary productivity across the study area had a substantial effect on conversion thresholds required to trigger land use change when compared to results from NPV analysis. Areas traditionally thought of as being quite similar in average productive capacity can display large differences in response to the inclusion of production and price risks. The effects of climate change, broadly reduced returns required for land use change to biomass in low and medium rainfall zones and increased them in higher rainfall areas. Additionally, the risks posed by climate change can further exacerbate the tendency for NPV methods to underestimate true conversion thresholds. Our results show that even under severe drying and warming where crop yield variability is more affected than perennial biomass plantings, comparatively little of the study area is economically viable for conversion to biomass under $200/DM t, and it is not until prices exceed $200/DM t that significant areas become profitable for biomass plantings. We conclude that for biomass to become a valuable diversification option the synchronisation of products and services derived from biomass and the development of markets is vital. [ABSTRACT FROM AUTHOR]

Ecosystem monitoring networks aim to collect data on physical, chemical and biological systems and their interactions that shape the biosphere. Here we introduce the Australian SuperSite Network that, along with complementary facilities of Australia's Terrestrial Ecosystem Research Network (TERN), delivers field infrastructure and diverse, ecosystem-related datasets for use by researchers, educators and policy makers. The SuperSite Network uses infrastructure replicated across research sites in different biomes, to allow comparisons across ecosystems and improve scalability of findings to regional, continental and global scales. This conforms with the approaches of other ecosystem monitoring networks such as Critical Zone Observatories, the U.S. National Ecological Observatory Network; Analysis and Experimentation on Ecosystems, Europe; Chinese Ecosystem Research Network; International Long Term Ecological Research network and the United States Long Term Ecological Research Network. The Australian SuperSite Network currently involves 10 SuperSites across a diverse range of biomes, including tropical rainforest, grassland and savanna; wet and dry sclerophyll forest and woodland; and semi-arid grassland, woodland and savanna. The focus of the SuperSite Network is on using vegetation, faunal and biophysical monitoring to develop a process-based understanding of ecosystem function and change in Australian biomes; and to link this with data streams provided by the series of flux towers across the network. The Australian SuperSite Network is also intended to support a range of auxiliary researchers who contribute to the growing body of knowledge within and across the SuperSite Network, public outreach and education to promote environmental awareness and the role of ecosystem monitoring in the management of Australian environments. [ABSTRACT FROM AUTHOR]

Distributed catchment models such as SWAT (Soil and Water Assessment Tool) are widely used to assess catchment characteristics and facilitate informed decisions for safeguarding water quantity and quality. This study applied SWAT to simulate monthly stream flow and loadings of total suspended sediment (TSS), total nitrogen (TN) and total phosphorus (TP) for five monitoring stations within the Onkaparinga catchment, and tested the models’ performance based on single-site or multi-site calibration. The results showed that multi-site calibration did not improve simulations of flow and sediments compared to single-site calibration. However, simulation results for TN and TP loads improved in both rural and urban sub-catchments of this catchment. Uncertainty analysis revealed that there is high uncertainty in model simulation of TSS by both strategies. The study has demonstrated: (1) the capability of SWAT to simulate realistically the extreme flow conditions of the semi-arid Onkaparinga catchment; (2) the benefit of local monitoring data for more realistic simulations of nutrient loads by means of the multi-site calibration of SWAT as pre-requisite for scenario analysis of spatially-explicit management options. [ABSTRACT FROM AUTHOR]

Discounted cash flow analysis, including net present value is an established way to value land use and management investments which accounts for the time-value of money. However, it provides a static view and assumes passive commitment to an investment strategy when real world land use and management investment decisions are characterised by uncertainty, irreversibility, change, and adaptation. Real options analysis has been proposed as a better valuation method under uncertainty and where the opportunity exists to delay investment decisions, pending more information. We briefly review the use of discounted cash flow methods in land use and management and discuss their benefits and limitations. We then provide an overview of real options analysis, describe the main analytical methods, and summarize its application to land use investment decisions. Real options analysis is largely underutilized in evaluating land use decisions, despite uncertainty in policy and economic drivers, the irreversibility and sunk costs involved. New simulation methods offer the potential for overcoming current technical challenges to implementation as demonstrated with a real options simulation model used to evaluate an agricultural land use decision in South Australia. We conclude that considering option values in future policy design will provide a more realistic assessment of landholder investment decision making and provide insights for improved policy performance. [ABSTRACT FROM AUTHOR]

Climate change may shrink and/or shift plant species ranges thereby increasing their vulnerability and requiring targeted conservation to facilitate adaptation. We quantified the vulnerability to climate change of plant species based on exposure, sensitivity and adaptive capacity and assessed the effects of including these components in complementarity-based spatial conservation prioritisation. We modelled the vulnerability of 584 native plant species under three climate change scenarios in an 11.9 million hectare fragmented agricultural region in southern Australia. We represented exposure as species' geographical range under each climate change scenario as quantified using species distribution models. We calculated sensitivity as a function of the impact of climate change on species' geographical ranges. Using a dispersal kernel, we quantified adaptive capacity as species' ability to migrate to new geographical ranges under each climate change scenario. Using Zonation, we assessed the impact of individual components of vulnerability (exposure, sensitivity and adaptive capacity) on spatial conservation priorities and levels of species representation in priority areas under each climate change scenario. The full vulnerability framework proved an effective basis for identifying spatial conservation priorities under climate change. Including different dimensions of vulnerability had significant implications for spatial conservation priorities. Incorporating adaptive capacity increased the level of representation of most species. However, prioritising sensitive species reduced the representation of other species. We conclude that whilst taking an integrated approach to mitigating species vulnerability to climate change can ensure sensitive species are well-represented in a conservation network, this can come at the cost of reduced representation of other species. Conservation planning decisions aimed at reducing species vulnerability to climate change need to be made in full cognisance of the sensitivity of spatial conservation priorities to individual components of vulnerability, and the trade-offs associated with focussing on sensitive species. [ABSTRACT FROM AUTHOR]

Abstract: Environmental targets are often used in planning for sustainable agricultural landscapes but their impacts are rarely known. In this paper we introduce landscape futures analysis as a method which combines linear programming optimisation with scenario analysis in quantifying the environmental, economic, and social impacts associated with achieving environmental targets, on a landscape scale. We applied the technique in the Lower Murray in southern Australia. Landscape futures models were used to identify specific geographic locations in the landscape for six natural resource management (NRM) actions such that regional environmental targets are achieved. The six potential NRM actions that may be undertaken to achieve environmental targets include remnant vegetation management, ecological restoration, conservation farming, deep-rooted perennials, and the production of biomass and biofuels feedstock for renewable energy generation. We developed landscape futures under four alternative spatial prioritisation policy options and four future climate and commodity price scenarios. The impacts of each landscape future were calculated across a range of environmental, economic, and social indicators. The external drivers, climate change and commodity prices, and internal decisions such as policy options for spatially prioritising NRM actions, both have a strong influence on the costs and benefits of achieving environmental targets. Illustrative results for the cleared agricultural areas in the Mallee region indicate that whilst achieving targets can have substantial environmental benefits, it requires large areas of land use and land management change, and is likely to be costly (up to $348.5 M per year) with flow-on impacts on the regional economy and communities. Environmental targets can be achieved more cost-effectively through spatial planning. Costs can be further reduced if markets are established for carbon, biomass, and biofuels to enable landholders to generate income from undertaking NRM. Landscape futures analysis is an effective tool for supporting the strategic regional NRM policy and planning decisions of how best to set and achieve environmental targets. [Copyright &y& Elsevier]

Aerodynamic resistance (hereafter r a) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of r a plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r a with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates. The present study investigates the influence of r a and its relation to LST uncertainties on the performance of three structurally different SEB models. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE , the energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST , LAI, and in-situ meteorological datasets were evaluated against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019. Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underestimation of H. Overestimation of LE was associated with discrepancies in r a retrievals under conditions of high atmospheric instability, during which uncertainties in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive difference in LST coincided with low r a (high wind speeds) and caused a slight underestimation of LE at the water-limited sites. The impact of r a on the LE residual error was found to be of the same magnitude as the influence of LST uncertainties in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for the mesic forest ecosystems indicated minor dependency on r a for modelling LE (VIP < 0.4), which was due to a higher roughness length and lower LST resulting in the dominance of mechanically generated turbulence, thereby diminishing the importance of buoyancy production for the determination of r a. • Modelled latent heat flux is uncertain under drought due to aerodynamic resistance. • Overestimation of aerodynamic resistance at water-limited sites for low wind speed. • Stability links aerodynamic resistance with surface temperature and sensible heat. • Novel formulations for aerodynamic resistance are needed to model latent heat flux. [ABSTRACT FROM AUTHOR]

Surface albedo is a fundamental radiative parameter as it controls the Earth's energy budget and directly affects the Earth's climate. Satellite observations have long been used to capture the temporal and spatial variations of surface albedo because of their continuous global coverage. However, space-based albedo products are often affected by errors in the atmospheric correction, multi-angular bi-directional reflectance distribution function (BRDF) modelling, as well as spectral conversions. To validate space-based albedo products, an in situ tower albedometer is often used to provide continuous "ground truth" measurements of surface albedo over an extended area. Since space-based albedo and tower-measured albedo are produced at different spatial scales, they can be directly compared only for specific homogeneous land surfaces. However, most land surfaces are inherently heterogeneous with surface properties that vary over a wide range of spatial scales. In this work, tower-measured albedo products, including both directional hemispherical reflectance (DHR) and bi-hemispherical reflectance (BHR), are upscaled to coarse satellite spatial resolutions using a new method. This strategy uses high-resolution satellite derived surface albedos to fill the gaps between the albedometer's field-of-view (FoV) and coarse satellite scales. The high-resolution surface albedo is generated from a combination of surface reflectance retrieved from high-resolution Earth Observation (HR-EO) data and moderate resolution imaging spectroradiometer (MODIS) BRDF climatology over a larger area. We implemented a recently developed atmospheric correction method, the Sensor Invariant Atmospheric Correction (SIAC), to retrieve surface reflectance from HR-EO (e.g., Sentinel-2 and Landsat-8) top-of-atmosphere (TOA) reflectance measurements. This SIAC processing provides an estimated uncertainty for the retrieved surface spectral reflectance at the HR-EO pixel level and shows excellent agreement with the standard Landsat 8 Surface Reflectance Code (LaSRC) in retrieving Landsat-8 surface reflectance. Atmospheric correction of Sentinel-2 data is vastly improved by SIAC when compared against the use of in situ AErosol RObotic NETwork (AERONET) data. Based on this, we can trace the uncertainty of tower-measured albedo during its propagation through high-resolution EO measurements up to coarse satellite scales. These upscaled albedo products can then be compared with space-based albedo products over heterogeneous land surfaces. In this study, both tower-measured albedo and upscaled albedo products are examined at Ground Based Observation for Validation (GbOV) stations (https://land.copernicus.eu/global/gbov/), and used to compare with satellite observations, including Copernicus Global Land Service (CGLS) based on ProbaV and VEGETATION 2 data, MODIS and multi-angle imaging spectroradiometer (MISR). [ABSTRACT FROM AUTHOR]

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010-11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010-11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010-11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011-12, and was nearly eliminated in 2012-13 (0.08 Pg). We further report evidence of an earlier 2000-01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle. [ABSTRACT FROM AUTHOR]

A correction to the article regarding the affiliation for David M. Summers that was published in the 2012 issue is presented.