A participatory systems approach to understanding climate adaptation needs

Emerging literature on climate adaptation suggests the need for effective ways of engaging or activating communities and supporting community roles, coupled with whole-of-system approaches to understanding climate change and adaptation needs. We have developed and evaluated a participatory approach to elicit community and stakeholder understanding of climate change adaptation needs, and connect diverse community members and local office bearers towards potential action. The approach was trialed in a series of connected social-ecological systems along a transect from a rural area to the coast and islands of ecologically sensitive Moreton Bay in Queensland, Australia. We conducted ‘climate roundtables’ in each of three areas along the transect, then a fourth roundtable reviewed and extended the results to the region as a whole. Influence diagrams produced through the process show how each climate variable forecast to affect this region (heat, storm, flood, sea-level rise, fire, drought) affects the natural environment, infrastructure, economic and social behaviour patterns, and psychosocial responses, and how sets of people, species and ecosystems are affected, and act, differentially. The participatory process proved effective as a way of building local empathy, a local knowledge base and empowering participants to join towards future climate adaptation action. Key principles are highlighted to assist in adapting the process for use elsewhere.

Assessment of prey overlap between a native (Polistes humilis) and an introduced (Vespula germanica) social wasp using morphology and phylogenetic analyses of 16S rDNA

In newly invaded communities, interspecific competition is thought to play an important role in determining the success of the invader and its impact on the native community. In southern Australia, the native Polistes humilis was the predominant social wasp prior to the arrival of the exotic Vespula germanica (Hymenoptera: Vespidae). Both species forage for similar resources (water, pulp, carbohydrate and protein prey), and concerns have arisen about potential competition between them. The aim of this study was to identify the protein foods that these wasps feed on. As many prey items are masticated by these wasps to the degree that they cannot be identified using conventional means, morphological identification was complemented by sequencing fragments of the mitochondrial 16S rRNA gene. GenBank searches using blast and phylogenetic analyses were used to identify prey items to at least order level. The results were used to construct complete prey inventories for the two species. These indicate that while P. humilis is restricted to feeding on lepidopteran larvae, V. germanica collects a variety of prey of invertebrate and vertebrate origin. Calculated values of prey overlap between the two species are used to discuss the implications of V. germanica impacting on P. humilis. Results obtained are compared to those gained by solely 'conventional' methods, and the advantages of using DNA-based taxonomy in ecological studies are emphasized.

The short-term effects of a routine poisoning campaign on the movements and detectability of a social top-predator

Top-predators can be important components of resilient ecosystems, but they are still controlled in many places to mitigate a variety of economic, environmental and/or social impacts. Lethal control is often achieved through the broad-scale application of poisoned baits. Understanding the direct and indirect effects of such lethal control on subsequent movements and behaviour of survivors is an important pre-requisite for interpreting the efficacy and ecological outcomes of top-predator control. In this study, we use GPS tracking collars to investigate the fine-scale and short-term movements of dingoes (Canis lupus dingo and other wild dogs) in response to a routine poison-baiting program as an example of how a common, social top-predator can respond (behaviourally) to moderate levels of population reduction. We found no consistent control-induced differences in home range size or location, daily distance travelled, speed of travel, temporal activity patterns or road/trail usage for the seven surviving dingoes we monitored immediately before and after a typical lethal control event. These data suggest that the spatial behaviour of surviving dingoes was not altered in ways likely to affect their detectability, and if control-induced changes in dingoes' ecological function did occur, these may not be related to altered spatial behaviour or movement patterns.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected. (C) 2013 Elsevier B.V. All rights reserved.

Selecting and assessing social objectives for Australian fisheries management

This paper details Australian research that developed tools to assist fisheries managers and government agencies in engaging with the social dimension of industry and community welfare in fisheries management. These tools are in the form of objectives and indicators. These highlight the social dimensions and the effects of management plans and policy implementation on fishing industries and associated communities, while also taking into account the primacy of ecological imperatives. The deployment of these objectives and indicators initially provides a benchmark and, over the life of a management plan, can subsequently be used to identify trends in effects on a variety of social and economic elements that may be objectives in the management of a fishery. It is acknowledged that the degree to which factors can be monitored will be dependent upon resources of management agencies, however these frameworks provide a method for effectively monitoring and measuring change in the social dimension of fisheries management.Essentially, the work discussed in this paper provides fisheries management with the means to both track and begin to understand the effects of government policy and management plans on the social dimension of the fishing industry and its associated communities. Such tools allow the consideration of these elements, within an evidence base, into policy arrangements, and consequently provide an invaluable contribution to the ability to address resilience and sustainability of fishing industries and associated communities.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.