Inferring habitat suitability and spread patterns from large‐scale distributions of an exotic invasive pasture grass in north Australia

Abstract

Summary1. The understanding of large-scale patterns in expanding populations of alien invasive plants can be used to infer the environmental limiting factors, habitat heterogeneity and, ultimately, the range expansion potential of invasive plants. 2. We used multivariate analysis and a novel quantile regression technique accounting for spatial autocorrelation to compare and contrast factors influencing the abundance and distribution of the African grass Andropogon gayanus (gamba grass) at two large-scale invasion sites in the tropical savanna region of Australia. We collected data using aerial and ground surveys and tested for limiting factors using three landscape-scale indices related to soil quality, soil moisture and invasion history. 3. In one site, gamba grass was principally colonising drainage lines and riparian areas. Occupation of these areas was limited in proportion to the distance from the original gamba grass source. In the second site, gamba grass abundance was independent of distance from the original source and was well established in all vegetation communities, although abundance was also limited in higher elevation sites away from drainage lines. 4. Comparisons between these sites with different patterns of invasion enabled the estimation of both the invasion pathways and range expansion potential of gamba grass. Our results indicated that gamba grass spreads from riparian communities to invade upland sites and has the potential to invade 70% of north Australia's upland savanna communities. 5. Aerial surveys comprehensively assessed patterns over a larger area than ground surveys and were much more economical. 6. Synthesis and applications. Large-scale surveys across multiple sites are critical to understanding the dynamics of recent alien species invasions where little is known about the pattern and potential range of spread. The application of quantile regression and aerial surveys shows promise as aerial surveys are efficient at capturing a large amount of data. The novel quantile regression technique we demonstrate here can account for both spatial autocorrelation and noisy ecological data from aerial surveys while returning robust results. We were thus able to demonstrate widespread colonisation of creek lines by gamba grass and recommend that management focuses on detection and eradication along drainage lines in addition to the present focus on transport corridors.

Adding Fuel to the Fire: The Impacts of Non-Native Grass Invasion on Fire Management at a Regional Scale

“…The rapid rate of spread of A. gayanus and its ability to invade the broad range of savanna habitats [26], [37] suggests that this species could result in major fire and weed management issues across a vast region of northern Australia. The Kent cultivar of A. gayanus was released relatively recently, having been promoted in the 1980's as an improved pasture species.…”

“…This cultivar ‘Kent’ was released in 1978 [15], planted in paddocks within the study area in the mid-1980s and spread was noticed from these paddocks to adjacent areas in the 1990s [26]. A. gayanus grows to 4 m tall and is physiologically active for longer into the dry season than the native grasses [18].…”

“…To determine the extent of A. gayanus cover at a regional scale, we undertook transect-based aerial surveys which are described in detail in Petty et al (2012) [26]. In brief, helicopter surveys were undertaken between April and June 2009, when A. gayanus is most visually obvious in the landscape.…”

“…A total of 109 helicopter-surveyed quadrats (175×250 m) were ground-truthed in September 2009. The accuracy of the survey was high (weighted Cohen's Kappa = 0.66; a completely random association has a score = 0 while complete agreement has a score = 1) [28]–[30]), with most of the error coming from individual or isolated clumps of plants that were undetected in the aerial survey [26]. The total area falling within each cover category was determined within two zones, one with the radius of 10 km and the other with a radius of 20 km around the township of Batchelor (13°0387′S; 131°0721′E), the centre of the main infestation area (Fig.…”

Unassisted invasions: understanding and responding to Australia’s high-impact environmental grass weeds

“…Buffel grass is the main threat: modelling suggests that~68% of mainland Australia is vulnerable to invasion (Lawson et al 2004), across a broad range of habitats (Clarke et al 2005;Martin et al 2015). Gamba grass is expected to have the potential to invade 70% of Australian upland savanna communities (Petty et al 2012). However, disturbance requirements are generally not considered in species distribution modelling which can therefore result in weed potential being seriously overestimated (Murray et al 2012): some habitats may be susceptible to invasion in the absence of anthropogenic disturbance, whereas others may require disturbance before invasion can occur.…”