Surveillance protocols for management of invasive plants: modelling Chilean needle grass (Nassella neesiana) in Australia

Aim: To develop a surveillance support model that enables prediction of areas susceptible to invasion, comparative analysis of surveillance methods and intensity and assessment of eradication feasibility. To apply the model to identify surveillance protocols for generalized invasion scenarios and for evaluating surveillance and control for a context-specific plant invasion. Location: Australia. Methods: We integrate a spatially explicit simulation model, including plant demography and dispersal vectors, within a Geographical Information System. We use the model to identify effective surveillance protocols using simulations of generalized plant life-forms spreading via different dispersal mechanisms in real landscapes. We then parameterize the surveillance support model for Chilean needle grass [CNG; Nassella neesiana (Trin. & Rupr.) Barkworth], a highly invasive tussock grass, which is an eradication target in south-eastern Queensland, Australia. Results: General surveillance protocols that can guide rapid response surveillance were identified; suitable habitat that is susceptible to invasion through particular dispersal syndromes should be targeted for surveillance using an adaptive seek-and-destroy method. The search radius of the adaptive method should be based on maximum expected dispersal distances. Protocols were used to define a surveillance strategy for CNG, but simulations indicated that despite effective and targeted surveillance, eradication is implausible at current intensities. Main conclusions: Several important surveillance protocols emerged and simulations indicated that effectiveness can be increased if they are followed in rapid response surveillance. If sufficient data are available, the surveillance support model should be parameterized to target areas susceptible to invasion and determine whether surveillance is effective and eradication is feasible. We discovered that for CNG, regardless of a carefully designed surveillance strategy, eradication is implausible at current intensities of surveillance and control and these efforts should be doubled if they are to be successful. This is crucial information in the face of environmentally and economically damaging invasive species and large, expensive and potentially ineffective control programmes.

Hierarchical Bayesian modelling of plant pest invasions with human-mediated dispersal

Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

Population genetics of Australian white sharks reveals fine-scale spatial structure, transoceanic dispersal events and low effective population sizes

Despite international protection of white sharks Carcharodon carcharias, important conservation parameters such as abundance, population structure and genetic diversity are largely unknown. The tissue of 97 predominately juvenile white sharks sampled from spatially distant eastern and southwestern Australian coastlines was sequenced for the mitochondrial DNA (mtDNA) control region and genotyped with 6 nuclear-encoded microsatellite loci. MtDNA population structure was found between the eastern and southwestern coasts (F-ST = 0.142, p < 0.0001), implying female reproductive philopatry. This concurs with recent satellite and acoustic tracking findings which suggest the sustained presence of discrete east coast nursery areas. Furthermore, population subdivision was found between the same regions with biparentally inherited micro satellite markers (F-ST = 0.009, p < 0.05), suggesting that males may also exhibit some degree of reproductive philopatry; 5 sharks captured along the east coast had mtDNA haplotypes that resembled western Indian Ocean sharks more closely than Australian/New Zealand sharks, suggesting that transoceanic dispersal, or migration resulting in breeding, may occur sporadically. Our most robust estimate of contemporary genetic effective population size was low and close to thresholds at which adaptive potential may be lost. For a variety of reasons, these contemporary estimates were at least 1, possibly 2, orders of magnitude below our historical effective size estimates. Population decline could expose these genetically isolated populations to detrimental genetic effects. Regional Australian white shark conservation management units should be implemented until genetic population structure, size and diversity can be investigated in more detail.