Mitochondrial control region diversity of the houbara bustard Chlamydotis undulata complex and genetic structure along the Atlantic seaboard of North Africa

The houbara bustard, Chlamydotis undulata, is a declining cryptic desert bird whose range extends from North Africa to Central Asia. Three subspecies are currently recognized by geographical distribution and morphology: C.u.fuertaventurae, C.u.undulata and C.u.macqueenii. We have sequenced 854 bp of mitochondrial control region from 73 birds to describe their population genetic structure with a particular sampling focus on the connectivity between C.u.fuertaventurae and C.u.undulata along the Atlantic seaboard of North Africa. Nucleotide and haplotypic diversity varied among the subspecies being highest in C.u.undulata, lowest in C.u.fuertaventurae and intermediate in C.u.macqueenii. C.u.fuertaventurae and C.u.undulata are paraphyletic and an average nucleotide divergence of 2.08% splits the later from C.u.macqueenii. We estimate that C.u.fuertaventurae and C.u.undulata split from C.u.macqueenii approximately 430 000 years ago. C.u.fuertaventurae and C.u.undulata are weakly differentiated (F-ST = 0.27, N-m = 1.3), indicative of a recent shared history. Archaeological evidence indicates that houbara bustards have been present on the Canary Islands for 130-170 000 years. However, our genetic data point to a more recent separation of C.u.fuertaventurae and C.u.undulata at around 20-25 000 years. Concordant archaeological, climatic opportunities for colonization and genetic data point to a scenario of: (i) initial colonization of the Canary Islands about 130 000 years ago; (ii) a period of secondary contact 19-30 000 years ago homogenizing any pre-existing genetic structure followed by; (iii) a period of relative isolation that persists today.

Predicting population dynamics of weed biological control agents: science or gazing into crystal balls?

Various factors can influence the population dynamics of phytophages post introduction, of which climate is fundamental. Here we present an approach, using a mechanistic modelling package (CLIMEX), that at least enables one to make predictions of likely dynamics based on climate alone. As biological control programs will have minimal funding for basic work (particularly on population dynamics), we show how predictions can be made using a species geographical distribution, relative abundance across its range, seasonal phenology and laboratory rearing data. Many of these data sets are more likely to be available than long-term population data, and some can be incorporated into the exploratory phase of a biocontrol program. Although models are likely to be more robust the more information is available, useful models can be developed using information on species distribution alone. The fitted model estimates a species average response to climate, and can be used to predict likely geographical distribution if introduced, where the agent is likely to be more abundant (i.e. good locations) and more importantly for interpretation of release success, the likely variation in abundance over time due to intra- and inter-year climate variability. The latter will be useful in predicting both the seasonal and long-term impacts of the potential biocontrol agent on the target weed. We believe this tool may not only aid in the agent selection process, but also in the design of release strategies, and for interpretation of post-introduction dynamics and impacts. More importantly we are making testable predictions. If biological control is to become more of a science making and testing such hypothesis will be a key component.

Is the distribution of Fiji leaf gall in Australian sugarcane explained by variation in the vector Perkinsiella saccharicida?

Fiji leaf gall (FLG) is an important virally induced disease in Australian sugarcane. It is confined to southern canegrowing areas, despite its vector, the delphacid planthopper Perkinsiella saccharicida, occurring in all canegrowing areas of Queensland and New South Wales. This disparity between distributions could be a result of successful containment of the disease through quarantine and/or geographical barriers, or because northern Queensland populations of Perkinsiella may be poorer vectors of the disease. These hypotheses were first tested by investigating variation in the ITS2 region of the rDNA fragment among eastern Australian and overseas populations of Perkinsiella. The ITS2 sequences of the Western Australian P. thompsoni and the Fijian P. vitiensis were distinguishable from those of P. saccharicida and there was no significant variation among the 26P. saccharicida populations. Reciprocal crosses of a northern Queensland and a southern Queensland population of P. saccharicida were fertile, so they may well be conspecific. Single vector transmission experiments showed that a population of P. saccharicida from northern Queensland had a higher vector competency than either of two southern Queensland populations. The frequency of virus acquisition in the vector populations was demonstrated to be important in the vector competency of the planthopper. The proportion of infected vectors that transmitted the virus to plants was not significantly different among the populations tested. This study shows that the absence of FLG from northern Queensland is not due to a lack of vector competency of the northern population of P. saccharicida.

The genetic structure of Australasian green turtles (Chelonia mydas): exploring the geographical scale of genetic exchange

Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Phi = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.