School of Agriculture, Food and Ecosystem Sciences - Research Publications

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    The role of topography and the north Indian monsoon on mean monthly climate interpolation within the Himalayan Kingdom of Bhutan
    Stewart, SB ; Choden, K ; Fedrigo, M ; Roxburgh, SH ; Keenan, RJ ; Nitschke, CR (WILEY, 2017-08)
    ABSTRACT Spatial climate datasets currently available for Bhutan are limited by weather station data availability, spatial resolution or interpolation methodology. This article presents new datasets for monthly maximum temperature, minimum temperature, precipitation and vapour pressure climate normals interpolated for the 1986–2015 reference period using trivariate smoothing splines. The inclusion of standardized day time Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) values as partial spline dependencies reduced cross validated root mean square error (RMSE) for maximum temperature by up to 16.0% and was most effective between March and September. Using both a topographic index of relative elevation and standardized night time MODIS LST values as partial spline dependencies reduced monthly mean minimum temperature RMSE by up to 23.4%. Neither variable was effective for minimum temperature interpolation between June and September. High humidity, extensive cloud cover and heavy precipitation occur during these months, which are likely to suppress the formation of temperature inversions that typically form under clear, calm conditions. These new temperature and precipitation surfaces show distinct differences from the WorldClim and CRU CL 2.0 datasets, which do not use weather stations within Bhutan for calibration. New precipitation surfaces better describe the heavy rainfall experienced in the southern foothills while retaining the effect of orography throughout the central valleys and ranges. The development of vapour pressure surfaces also allow for the calculation of ecologically important variables such as vapour pressure deficit, and may also be useful for solar radiation modelling in the region. The different datasets presented in this article will facilitate ecological and agricultural research in Bhutan and provide high quality surfaces needed for future climate change scenarios.
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    Structural diversity underpins carbon storage in Australian temperate forests
    Aponte, C ; Kasel, S ; Nitschke, CR ; Tanase, MA ; Vickers, H ; Parker, L ; Fedrigo, M ; Kohout, M ; Ruiz-Benito, P ; Zavala, MA ; Bennett, LT ; Hickler, T (WILEY, 2020-05)
    Abstract Aim Forest carbon storage is the result of a multitude of interactions among biotic and abiotic factors. Our aim was to use an integrative approach to elucidate mechanistic relationships of carbon storage with biotic and abiotic factors in the natural forests of temperate Australia, a region that has been overlooked in global analyses of carbon‐biodiversity relations. Location South‐eastern Australia. Time period 2010–2015. Major taxa studied Forest trees in 732 plots. Methods We used the most comprehensive forest inventory database available for south‐eastern Australia and structural equation models to assess carbon‐storage relationships with biotic factors (species or functional diversity, community‐weighted mean (CWM) trait values, structural diversity) and abiotic factors (climate, soil, fire history). To assess the consistency of relationships at different environmental scales, our analyses involved three levels of data aggregation: six forest types, two forest groups (representing different growth environments), and all forests combined. Results Structural diversity was consistently the strongest independent predictor of carbon storage at all levels of data aggregation, whereas relationships with species‐ and functional‐diversity indices were comparatively weak. CWMs of maximum height and wood density were also significant independent predictors of carbon storage in most cases. In comparison, climate, soil, and fire history had only minor and mainly indirect effects via biotic factors on carbon storage. Main conclusions Our results indicate that carbon storage in our temperate forests was underpinned by tree structural diversity (representing efficient utilisation of space) and by CWM trait values (representing selection effects) more so than by tree species richness or functional diversity. Abiotic effects were comparatively weak and mostly indirect via biotic factors irrespective of the environmental range. Our study highlights the importance of managing forests for functionally important species and to maintain and enhance their structural complexity in order to support carbon storage.