Predicting bee community responses to land-use changes: Effects of geographic and taxonomic biases

Land-use change and intensification threaten bee populations worldwide, imperilling pollination services. Global models are needed to better characterise, project, and mitigate bees' responses to these human impacts. The available data are, however, geographically and taxonomically unrepresentative; most data are from North America and Western Europe, overrepresenting bumblebees and raising concerns that model results may not be generalizable to other regions and taxa. To assess whether the geographic and taxonomic biases of data could undermine effectiveness of models for conservation policy, we have collated from the published literature a global dataset of bee diversity at sites facing land-use change and intensification, and assess whether bee responses to these pressures vary across 11 regions (Western, Northern, Eastern and Southern Europe; North, Central and South America; Australia and New Zealand; South East Asia; Middle and Southern Africa) and between bumblebees and other bees. Our analyses highlight strong regionally-based responses of total abundance, species richness and Simpson's diversity to land use, caused by variation in the sensitivity of species and potentially in the nature of threats. These results suggest that global extrapolation of models based on geographically and taxonomically restricted data may underestimate the true uncertainty, increasing the risk of ecological surprises.

People and their past : is 'community archaeology’ the future?

This thesis looks at how ‘community archaeology’ ideals may influence an inclusive approach to Indigenous heritage management, ensuring Indigenous community power over processes to identify both past and present values of Country. Community archaeology was acclaimed by research archaeologists over a decade ago as a distinctive approach with its own set of practices to incorporate the local community’s perspectives of its past and current associations with place. A core feature of this approach in Australia is the major role the Indigenous community has in decisions about its heritage. Concurrently, considerable concern was being expressed that Indigenous heritage was not sufficiently addressed in environmental impact assessment processes ahead of development. Seen as absent from the process was the inclusion of Indigenous knowledge about both the pre- and post-contact story as well as any scientific advance in understanding an area’s Indigenous history. This research examines these contrasting perspectives seeking to understand the ideals of community archaeology and its potential to value all aspects of Indigenous heritage and so benefit the relevant community. The ideals of community archaeology build on past community collaborations in Australia and also respond to more recent societal recognition of Indigenous rights, reflected in more ethically inclusive planning and heritage statutes. Indigenous communities expressed the view that current systems are still not meeting these policy commitments to give them control over their heritage. This research has examined the on-the-ground reality of heritage work on the outskirts of Canberra and Melbourne. The case studies compare Victorian and ACT heritage management processes across community partnerships with public land managers, and examine how pre-development surveys operate. I conclude that considerable potential for achieving community archaeology ideals exists, and that they are occasionally partially realised, however barriers continue. In essence, the archaeological model persists despite a community archaeology approach requiring a wider set of skills to ensure a comprehensive engagement with an Indigenous community. Other obstacles in the current Indigenous heritage management system include a lack of knowledge and communication about national standards for heritage processes in government agencies and heritage consultants; the administrative framework that can result in inertia or silos between relevant agencies; and funding timeframes that limit possibilities for long-term strategic programs for early identification and management planning for Indigenous heritage. Also, Indigenous communities have varying levels of authority to speak for how their heritage should be managed, yet may not have the resources to do so. This thesis suggests ways to breach these barriers to achieve more inclusive Indigenous heritage management based on community archaeology principles. Policies for a greater acknowledgement of the Indigenous community’s authority to speak for Country; processes that enable and early and comprehensive ‘mapping’ of Country, and long-term resourcing of communities, may have been promised before. In this research I suggest ways to realise such goals.

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.