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Background Intensification of land use threatens to increase the emergence and prevalence of zoonotic diseases, with an adverse impact on human wellbeing. Understanding how the interaction between agriculture, natural systems, climate and socioeconomic drivers influence zoonotic disease distribution is crucial to inform policy planning and management to limit the emergence of new infections. Objectives Here we assess the relative contribution of environmental, climatic and socioeconomic factors influencing reported cryptosporidiosis across Australia from 2001 to 2018. Methods We apply a Bayesian spatio-temporal analysis using Integrated Nested Laplace Approximation (INLA). Results We find that area-level risk of reported disease are associated with the proportions of the population under 5 and over 65 years of age, socioeconomic disadvantage, annual rainfall anomaly, and the proportion of natural habitat remaining. This combination of multiple factors influencing cryptosporidiosis highlights the benefits of a sophisticated spatio-temporal statistical approach. Two key findings from our model include: an estimated 4.6% increase in the risk of reported cryptosporidiosis associated with 22.8% higher percentage of postal area covered with original habitat; and an estimated 1.8% increase in disease risk associated with a 77.99 mm increase in annual rainfall anomaly at the postal area level. Discussion These results provide novel insights regarding the predictive effects of extreme rainfall and the proportion of remaining natural habitat, which add unique explanatory power to the model alongside the variance associated with other predictive variables and spatiotemporal variation in reported disease. This demonstrates the importance of including perspectives from land and water management experts for policy making and public health responses to manage environmentally mediated diseases, including cryptosporidiosis.

Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions., Trends The majority of biodiversity modelling approaches do not explicitly address the question of saturation. Theoretical and methodological implications of saturation or unsaturation in biodiversity modelling. Addressing saturation or unsaturation is vital to produce more reliable conservation strategies. Integrative community modelling frameworks may be the way forward.

Barnes and Roderick [Barnes, B., Roderick, M.L., 2004. An ecological framework linking scales across space and time based on self-thinning. Theoret. Popul. Biol. 66, 113–128] developed a generic ecological framework for scaling from individuals to ecosystems. Their approach is general and can be applied to predict above-ground, or total (above- and below-ground), dry mass. In practice, the most common situation is to measure above-ground dry mass, and apply an allometric relationship to estimate the below-ground component. In this paper we develop a general theory for incorporating the dynamics of plant partitioning into the generic framework. We consider the inclusion of allometric relationships between components (such as between roots and shoots), as well as process driven relationships, and illustrate the application of each case. Through this approach, local scale measurements and individual-based dynamic relationships pertaining to plant partitioning can be applied to an understanding of partitioning at the patch (or ecosystem) scale. Moreover, we also demonstrate that the empirically based allometric relationships have, in some circumstances, a physical explanation, providing biological meaning to empirically established allometric constants.

Recently, there has been a surge in interest in how beta-diversity is defined and applied (e.g., [1]). Socolar et al. [2] have rightly recognised the fundamental importance of considering beta-diversity for conserving biodiversity, and clearly explain the various ways in which beta-diversity may respond to contrasting ecological and anthropogenic forces. However, there are many ways in which beta-diversity already underpins much of modern conservation science and practice, although differences in terminology means that this may not always be explicit.

Viewing a problem from a different angle can often provide new insight. Meelis Partel and colleagues recently suggested an interesting and novel way to view the species that are absent from a community; what they call ‘dark diversity’ [1]. The dark diversity for a local community is the pool of species occurring within the region that could inhabit that location but are not currently present. Although it is proposed that this new perspective on missing species can contribute to the understanding and management of natural communities, we point to several important issues that require resolution for the dark diversity concept to be of practical value to ecologists.