School of Agriculture, Food and Ecosystem Sciences - Research Publications

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    The saturated pairwise interaction Gibbs point process as a joint species distribution model
    Flint, I ; Golding, N ; Vesk, P ; Wang, Y ; Xia, A (OXFORD UNIV PRESS, 2022-11)
    Abstract In an effort to effectively model observed patterns in the spatial configuration of individuals of multiple species in nature, we introduce the saturated pairwise interaction Gibbs point process. Its main strength lies in its ability to model both attraction and repulsion within and between species, over different scales. As such, it is particularly well-suited to the study of associations in complex ecosystems. Based on the existing literature, we provide an easy to implement fitting procedure as well as a technique to make inference for the model parameters. We also prove that under certain hypotheses the point process is locally stable, which allows us to use the well-known ‘coupling from the past’ algorithm to draw samples from the model. Different numerical experiments show the robustness of the model. We study three different ecological data sets, demonstrating in each one that our model helps disentangle competing ecological effects on species' distribution.
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    What state of the world are we in? Targeted monitoring to detect transitions in vegetation restoration projects
    Jones, CS ; Thomas, FM ; Michael, DR ; Fraser, H ; Gould, E ; Begley, J ; Wilson, J ; Vesk, PA ; Rumpff, L (WILEY, 2023-01)
    Monitoring vegetation restoration is challenging because monitoring is costly, requires long-term funding, and involves monitoring multiple vegetation variables that are often not linked back to learning about progress toward objectives. There is a clear need for the development of targeted monitoring programs that focus on a reduced set of variables that are tied to specific restoration objectives. In this paper, we present a method to progress the development of a targeted monitoring program, using a pre-existing state-and-transition model. We (1) use field data to validate an expert-derived classification of woodland vegetation states; (2) use these data to identify which variable(s) help differentiate woodland states; and (3) identify the target threshold (for the variable) that signifies if the desired transition has been achieved. The measured vegetation variables from each site in this study were good predictors of the different states. We show that by measuring only a few of these variables, it is possible to assign the vegetation state for a collection of sites, and monitor if and when a transition to another state has occurred. For this ecosystem and state-and-transition models, out of nine vegetation variables considered, the density of immature trees and percentage of exotic understory vegetation cover were the variables most frequently specified as effective to define a threshold or transition. We synthesize findings by presenting a decision tree that provides practical guidance for the development of targeted monitoring strategies for woodland vegetation.
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    Using Remote Sensing to Estimate Understorey Biomass in Semi-Arid Woodlands of South-Eastern Australia
    Riquelme, L ; Duncan, DH ; Rumpff, L ; Vesk, PA (MDPI, 2022-05)
    Monitoring ground layer biomass, and therefore forage availability, is important for managing large, vertebrate herbivore populations for conservation. Remote sensing allows for frequent observations over broad spatial scales, capturing changes in biomass over the landscape and through time. In this study, we explored different satellite-derived vegetation indices (VIs) for their utility in estimating understorey biomass in semi-arid woodlands of south-eastern Australia. Relationships between VIs and understorey biomass data have not been established in these particular semi-arid communities. Managers want to use forage availability to inform cull targets for western grey kangaroos (Macropus fuliginosus), to minimise the risk that browsing poses to regeneration in threatened woodland communities when grass biomass is low. We attempted to develop relationships between VIs and understorey biomass data collected over seven seasons across open and wooded vegetation types. Generalised Linear Mixed Models (GLMMs) were used to describe relationships between understorey biomass and VIs. Total understorey biomass (live and dead, all growth forms) was best described using the Tasselled Cap (TC) greenness index. The combined TC brightness and Modified Soil Adjusted Vegetation Index (MSAVI) ranked best for live understorey biomass (all growth forms), and grass (live and dead) biomass was best described by a combination of TC brightness and greenness indices. Models performed best for grass biomass, explaining 70% of variation in external validation when predicting to the same sites in a new season. However, we found empirical relationships were not transferrable to data collected from new sites. Including other variables (soil moisture, tree cover, and dominant understorey growth form) improved model performance when predicting to new sites. Anticipating a drop in forage availability is critical for the management of grazing pressure for woodland regeneration, however, predicting understorey biomass through space and time is a challenge. Whilst remotely sensed VIs are promising as an easily-available source of vegetation information, additional landscape-scale data are required before they can be considered a cost-efficient method of understorey biomass estimation in this semi-arid landscape.
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    Building trait datasets: effect of methodological choice on a study of invasion
    Palma, E ; Vesk, PA ; Catford, JA (SPRINGER, 2022-08)
    Trait-based approaches are commonly used to understand ecological phenomena and processes. Trait data are typically gathered by measuring local specimens, retrieving published records, or a combination of the two. Implications of methodological choices in trait-based ecological studies-including source of data, imputation technique, and species selection criteria-are poorly understood. We ask: do different approaches for dataset-building lead to meaningful differences in trait datasets? If so, do these differences influence findings of a trait-based examination of plant invasiveness, measured as abundance and spread rate? We collected on-site (Victoria, Australia) and off-site (TRY database) height and specific leaf area records for as many species as possible out of 157 exotic herbaceous plants. For each trait, we built six datasets of species-level means using records collected on-site, off-site, on-site and off-site combined, and off-site supplemented via imputation based on phylogeny and/or trait correlations. For both traits, the six datasets were weakly correlated (ρ = 0.31-0.95 for height; ρ = 0.14-0.88 for SLA), reflecting differences in species' trait values from the various estimations. Inconsistencies in species' trait means across datasets did not translate into large differences in trait-invasion relationships. Although we did not find that methodological choices for building trait datasets greatly affected ecological inference about local invasion processes, we nevertheless recommend: (1) using on-site records to answer local-scale ecological questions whenever possible, and (2) transparency around methodological decisions related to selection of study species and estimation of missing trait values.
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    Permanent removal of livestock grazing in riparian systems benefits native vegetation
    Jones, CS ; Duncan, DH ; Rumpff, L ; Robinson, D ; Vesk, PA (ELSEVIER, 2022-01)
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    mixchar: An R Package for the Deconvolution of Thermal Decay Curves
    Windecker, SM ; Vesk, PA ; Trevathan-Tackett, SM ; Golding, N (Ubiquity Press, Ltd., 2021-01-01)
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    Understanding the spatiotemporal dynamics of understorey biomass in semi-arid woodlands of south-eastern Australia
    Riquelme, L ; Rumpff, L ; Duncan, DH ; Vesk, PA (CSIRO PUBLISHING, 2022)
    When managing grazing pressure for conservation, understanding forage dynamics is essential. In south-eastern Australia, ongoing grazing is inhibiting regeneration in several semi-arid woodland communities. Western grey kangaroos (Macropus fuliginosus (Desmarest, 1817)) have been identified as a key component of total grazing pressure. They are thought to switch from grass to lower-quality browse, including tree seedlings, when grass biomass falls below 400 kg ha−1. One static threshold may not adequately capture the spatial and temporal hazard associated with kangaroo grazing, and this study aimed to explore how grassy biomass varies across a case-study landscape. Understorey biomass and species composition data were collected in the field on seven occasions between December 2016 and May 2019. We used Generalised Linear Mixed Models (GLMMs) to describe the influence of environmental and herbivory variables on total (live and dead) understorey, live understorey, and grass (live and dead) biomass. Canopy cover showed the strongest influence on understorey biomass, with more biomass found in open sites than in woodland. Understorey biomass levels were lowest in summer and autumn. Grass biomass, in particular, fell below the 400 kg ha−1 forage-switch threshold in wooded areas during this time. We anticipate that an increased understanding of understorey biomass dynamics will inform managers as to when and where to focus management efforts to promote regeneration and sustained recovery of these semi-arid woodlands. Results of this study suggest that conducting management efforts before the summer/autumn decline in understorey biomass, particularly in woodlands, is critical in reducing the browsing risk to seedlings.
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    Exploring how functional traits modulate species distributions along topographic gradients in Baxian Mountain, North China
    Tang, L ; Morris, WK ; Zhang, M ; Shi, F ; Vesk, PA (NATURE PORTFOLIO, 2022-01-19)
    The associations between functional traits and species distributions across environments have attracted increasing interest from ecologists and can enhance knowledge about how plants respond to the environments. Here, we applied a hierarchical generalized linear model to quantifying the role of functional traits in plant occurrence across topographic gradients. Functional trait data, including specific leaf area, maximum height, seed mass and stem wood density, together with elevation, aspect and slope, were used in the model. In our results, species responses to elevation and aspect were modulated by maximum height and seed mass. Generally, shorter tree species showed positive responses to incremental elevation, while this trend became negative as the maximum height exceeded 22 m. Most trees with heavy seeds (> 1 mg) preferred more southerly aspects where the soil was drier, and those light-seed trees were opposite. In this study, the roles of maximum height and seed mass in determining species distribution along elevation and aspect gradients were highlighted where plants are confronted with low-temperature and soil moisture deficit conditions. This work contributes to the understanding of how traits may be associated with species occurrence along mesoscale environmental gradients.
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    Using data calibration to reconcile outputs from different survey methods in long-term or large-scale studies
    Jones, CS ; Duncan, DH ; Morris, WK ; Robinson, D ; Vesk, PA (SPRINGER, 2022-03)
    Understanding the impact of management interventions on the environment over decadal and longer timeframes is urgently required. Longitudinal or large-scale studies with consistent methods are best practice, but more commonly, small datasets with differing methods are used to achieve larger coverage. Changes in methods and interpretation affect our ability to understand data trends through time or across space, so an ability to understand and adjust for such discrepancies between datasets is important for applied ecologists. Calibration or double sampling is the key to unlocking the value from disparate datasets, allowing us to account for the differences between datasets while acknowledging the uncertainties. We use a case study of livestock grazing impacts on riparian vegetation in southeastern Australia to develop a flexible and powerful approach to this problem. Using double sampling, we estimated changes in vegetation attributes over a 12-year period using a pseudo-quantitative visual method as the starting point, and the same technique plus point-intercept survey for the second round. The disparate nature of the datasets produced uncertain estimates of change over time, but accounting for this uncertainty explicitly is precisely the objective and highlights the need to look more closely at this very common problem in environmental management, as well as the potential benefits of the double sampling approach.
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    AusTraits, a curated plant trait database for the Australian flora
    Falster, D ; Gallagher, R ; Wenk, EH ; Wright, IJ ; Indiarto, D ; Andrew, SC ; Baxter, C ; Lawson, J ; Allen, S ; Fuchs, A ; Monro, A ; Kar, F ; Adams, MA ; Ahrens, CW ; Alfonzetti, M ; Angevin, T ; Apgaua, DMG ; Arndt, S ; Atkin, OK ; Atkinson, J ; Auld, T ; Baker, A ; von Balthazar, M ; Bean, A ; Blackman, CJ ; Bloomfeld, K ; Bowman, DMJS ; Bragg, J ; Brodribb, TJ ; Buckton, G ; Burrows, G ; Caldwell, E ; Camac, J ; Carpenter, R ; Catford, J ; Cawthray, GR ; Cernusak, LA ; Chandler, G ; Chapman, AR ; Cheal, D ; Cheesman, AW ; Chen, S-C ; Choat, B ; Clinton, B ; Clode, PL ; Coleman, H ; Cornwell, WK ; Cosgrove, M ; Crisp, M ; Cross, E ; Crous, KY ; Cunningham, S ; Curran, T ; Curtis, E ; Daws, M ; DeGabriel, JL ; Denton, MD ; Dong, N ; Du, P ; Duan, H ; Duncan, DH ; Duncan, RP ; Duretto, M ; Dwyer, JM ; Edwards, C ; Esperon-Rodriguez, M ; Evans, JR ; Everingham, SE ; Farrell, C ; Firn, J ; Fonseca, CR ; French, BJ ; Frood, D ; Funk, JL ; Geange, SR ; Ghannoum, O ; Gleason, SM ; Gosper, CR ; Gray, E ; Groom, PK ; Grootemaat, S ; Gross, C ; Guerin, G ; Guja, L ; Hahs, AK ; Harrison, MT ; Hayes, PE ; Henery, M ; Hochuli, D ; Howell, J ; Huang, G ; Hughes, L ; Huisman, J ; Ilic, J ; Jagdish, A ; Jin, D ; Jordan, G ; Jurado, E ; Kanowski, J ; Kasel, S ; Kellermann, J ; Kenny, B ; Kohout, M ; Kooyman, RM ; Kotowska, MM ; Lai, HR ; Laliberte, E ; Lambers, H ; Lamont, BB ; Lanfear, R ; van Langevelde, F ; Laughlin, DC ; Laugier-kitchener, B-A ; Laurance, S ; Lehmann, CER ; Leigh, A ; Leishman, MR ; Lenz, T ; Lepschi, B ; Lewis, JD ; Lim, F ; Liu, U ; Lord, J ; Lusk, CH ; Macinnis-Ng, C ; McPherson, H ; Magallon, S ; Manea, A ; Lopez-Martinez, A ; Mayfeld, M ; McCarthy, JK ; Meers, T ; van der Merwe, M ; Metcalfe, DJ ; Milberg, P ; Mokany, K ; Moles, AT ; Moore, BD ; Moore, N ; Morgan, JW ; Morris, W ; Muir, A ; Munroe, S ; Nicholson, A ; Nicolle, D ; Nicotra, AB ; Niinemets, U ; North, T ; O'Reilly-Nugent, A ; O'Sullivan, OS ; Oberle, B ; Onoda, Y ; Ooi, MKJ ; Osborne, CP ; Paczkowska, G ; Pekin, B ; Pereira, CG ; Pickering, C ; Pickup, M ; Pollock, LJ ; Poot, P ; Powell, JR ; Power, S ; Prentice, IC ; Prior, L ; Prober, SM ; Read, J ; Reynolds, V ; Richards, AE ; Richardson, B ; Roderick, ML ; Rosell, JA ; Rossetto, M ; Rye, B ; Rymer, PD ; Sams, M ; Sanson, G ; Sauquet, H ; Schmidt, S ; Schoenenberger, J ; Schulze, E-D ; Sendall, K ; Sinclair, S ; Smith, B ; Smith, R ; Soper, F ; Sparrow, B ; Standish, RJ ; Staples, TL ; Stephens, R ; Szota, C ; Taseski, G ; Tasker, E ; Thomas, F ; Tissue, DT ; Tjoelker, MG ; Tng, DYP ; de Tombeur, F ; Tomlinson, K ; Turner, NC ; Veneklaas, EJ ; Venn, S ; Vesk, P ; Vlasveld, C ; Vorontsova, MS ; Warren, CA ; Warwick, N ; Weerasinghe, LK ; Wells, J ; Westoby, M ; White, M ; Williams, NSG ; Wills, J ; Wilson, PG ; Yates, C ; Zanne, AE ; Zemunik, G ; Zieminska, K (NATURE PORTFOLIO, 2021-09-30)
    We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.