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Describing and classifying a landscape for environmental impact and risk assessment purposes is a non-trivial challenge because this requires region-specific landscape classifications that cater for region-specific impacts. Assessing impacts on ecosystems from the extraction of water resources across large regions requires a causal link between landscape features and their water requirements. We present the rationale and implementation of an ecohydrological classification for regions where coal mine and coal seam gas developments may impact on water. Our classification provides the essential framework for modelling the potential impact of hydrological changes from future coal resource developments at the landscape level. We develop an attribute-based system that provides representations of the ecohydrological entities and their connection to landscape features and make use of existing broad-level classification schemes into an attribute-based system. We incorporate a rule set with prioritisation, which underpins risk modelling and makes the scheme resource efficient, where spatial landscape or ecosystem classification schemes, developed for other purposes, already exist. A consistent rule set and conceptualised landscape processes and functions allow for the combination of diverse data with existing classification schemes. This makes the classification transparent, repeatable and adjustable, should new data become available. We apply the approach in three geographically different regions, with widely disparate information sources, for the classification, and provide a detailed example of its application. We propose that it is widely applicable around the world for linking ecohydrology to environmental impacts. [ABSTRACT FROM AUTHOR]

Describing and classifying a landscape for environmental impact and risk assessment purposes is a non-trivial challenge, as standard landscape classifications that cater for region specific impacts do not exist. Assessing impacts on ecosystems from extraction of water resources across large regions requires linking of landscape features to their water requirements. We present the rationale and implementation of an ecohydrological classification for regions where coal mine and coal seam gas developments may impact on water. Our classification provides the essential framework for modelling the potential impact of hydrological changes from future coal resource developments at the landscape level. We develop an attribute-based system that provides representations of the ecohydrological entities and their connection to landscape features and make use of existing broad-level, classification schemes into an attribute20 based system. We incorporate a rule-set with prioritisation, which underpin risk modelling and make the scheme resource efficient, where spatial landscape or ecosystem classification schemes, developed for other purposes, already exist. - A consistent rule-set and conceptualised landscape processes and functions allow combining diverse data with existing classification schemes. This makes the classification transparent, repeatable, and adjustable, should new data become available. We apply the approach in three geographically different regions, with widely disparate information sources for the classification and provide a detailed example of its application. We propose that it is widely applicable around the world for linking ecohydrology to environmental impacts. [ABSTRACT FROM AUTHOR]

Agroforestry is one nature-based solution that holds significant potential for improving the sustainability and resilience of agricultural systems. Quantifying these benefits is challenging in agroforestry systems, largely due to landscape complexity and the diversity of management approaches. Digital tools designed for agroforestry typically focus on timber and crop production, and not the broader range of benefits usually considered in assessments of ecosystem services and natural capital. The objectives of this review were to identify and evaluate digital tools that quantify natural capital benefits across eight themes applicable to agroforestry systems: timber production and carbon sequestration, agricultural production, microclimate, air quality, water management, biodiversity, pollination, and amenity. We identified and evaluated 63 tools, 9 of which were assessed in further detail using Australia as a case study. No single tool was best suited to quantify benefits across each theme, suggesting that multiple tools or models could be combined to address capability gaps. We find that model complexity, incorporation of spatial processes, accessibility, regional applicability, development speed and interoperability present significant challenges for the tools that were evaluated. We recommend that these challenges be considered as opportunities to develop new, and build upon existing, tools to enhance decision support in agroforestry systems. [ABSTRACT FROM AUTHOR]

Abstract Background The Tissue Microarray (TMA) facilitates high-throughput analysis of hundreds of tissue specimens simultaneously. However, bottlenecks in the storage and manipulation of the data generated from TMA reviews have become apparent. A number of software applications have been developed to assist in image and data management; however no solution currently facilitates the easy online review, scoring and subsequent storage of images and data associated with TMA experimentation. Results This paper describes the design, development and validation of the Virtual Tissue Matrix (VTM). Through an intuitive HTML driven user interface, the VTM provides digital/virtual slide based images of each TMA core and a means to record observations on each TMA spot. Data generated from a TMA review is stored in an associated relational database, which facilitates the use of flexible scoring forms. The system allows multiple users to record their interpretation of each TMA spot for any parameters assessed. Images generated for the VTM were captured using a standard background lighting intensity and corrective algorithms were applied to each image to eliminate any background lighting hue inconsistencies or vignetting. Validation of the VTM involved examination of inter-and intra-observer variability between microscope and digital TMA reviews. Six bladder TMAs were immunohistochemically stained for E-Cadherin, β-Catenin and PhosphoMet and were assessed by two reviewers for the amount of core and tumour present, the amount and intensity of membrane, cytoplasmic and nuclear staining. Conclusion Results show that digital VTM images are representative of the original tissue viewed with a microscope. There were equivalent levels of inter-and intra-observer agreement for five out of the eight parameters assessed. Results also suggest that digital reviews may correct potential problems experienced when reviewing TMAs using a microscope, for example, removal of background lighting variance and tint, and potential disorientation of the reviewer, which may have resulted in the discrepancies evident in the remaining three parameters.

Highlights • Over 2000 measurements of plant belowground biomass were compiled. • Accurate generic allometric models could be developed. • These models were validated across stands where whole-plot excavation data were available. • Gains in prediction efficiencies using species-specific models were negligible. Abstract Accurate quantification of below-ground biomass (BGB) of woody vegetation is critical to understanding ecosystem function and potential for climate change mitigation from sequestration of biomass carbon. We compiled 2054 measurements of planted and natural individual tree and shrub biomass from across different regions of Australia (arid shrublands to tropical rainforests) to develop allometric models for prediction of BGB. We found that the relationship between BGB and stem diameter was generic, with a simple power-law model having a BGB prediction efficiency of 72–93% for four broad plant functional types: (i) shrubs and Acacia trees, (ii) multi-stemmed mallee eucalypts, (iii) other trees of relatively high wood density, and; (iv) a species of relatively low wood density, Pinus radiata D. Don. There was little improvement in accuracy of model prediction by including variables (e.g. climatic characteristics, stand age or management) in addition to stem diameter alone. We further assessed the generality of the plant functional type models across 11 contrasting stands where data from whole-plot excavation of BGB were available. The efficiency of model prediction of stand-based BGB was 93%, with a mean absolute prediction error of only 6.5%, and with no improvements in validation results when species-specific models were applied. Given the high prediction performance of the generalised models, we suggest that additional costs associated with the development of new species-specific models for estimating BGB are only warranted when gains in accuracy of stand-based predictions are justifiable, such as for a high-biomass stand comprising only one or two dominant species. However, generic models based on plant functional type should not be applied where stands are dominated by species that are unusual in their morphology and unlikely to conform to the generalised plant functional group models. [ABSTRACT FROM AUTHOR]

Abstract: Elevated atmospheric CO2 concentration (eCa) might reduce forest water‐use, due to decreased transpiration, following partial stomatal closure, thus enhancing water‐use efficiency and productivity at low water availability. If evapotranspiration (Et) is reduced, it may subsequently increase soil water storage (ΔS) or surface runoff (R) and drainage (Dg), although these could be offset or even reversed by changes in vegetation structure, mainly increased leaf area index (L). To understand the effect of eCa in a water‐limited ecosystem, we tested whether 2 years of eCa (~40% increase) affected the hydrological partitioning in a mature water‐limited Eucalyptus woodland exposed to Free‐Air CO2 Enrichment (FACE). This timeframe allowed us to evaluate whether physiological effects of eCa reduced stand water‐use irrespective of L, which was unaffected by eCa in this timeframe. We hypothesized that eCa would reduce tree‐canopy transpiration (Etree), but excess water from reduced Etree would be lost via increased soil evaporation and understory transpiration (Efloor) with no increase in ΔS, R or Dg. We computed Et, ΔS, R and Dg from measurements of sapflow velocity, L, soil water content (θ), understory micrometeorology, throughfall and stemflow. We found that eCa did not affect Etree, Efloor, ΔS or θ at any depth (to 4.5 m) over the experimental period. We closed the water balance for dry seasons with no differences in the partitioning to R and Dg between Ca levels. Soil temperature and θ were the main drivers of Efloor while vapour pressure deficit‐controlled Etree, though eCa did not significantly affect any of these relationships. Our results suggest that in the short‐term, eCa does not significantly affect ecosystem water‐use at this site. We conclude that water‐savings under eCa mediated by either direct effects on plant transpiration or by indirect effects via changes in L or soil moisture availability are unlikely in water‐limited mature eucalypt woodlands. [ABSTRACT FROM AUTHOR]