Summary
Monitoring is essential for effective conservation and management of threatened species and ecological communities. However, more often than not, threatened species monitoring is poorly implemented, meaning that conservation decisions are not informed by the best available knowledge. We outline challenges and provide best‐practice guidelines for threatened species monitoring, informed by the diverse perspectives of 26 conservation managers and scientists from a range of organisations with expertise across Australian species and ecosystems. Our collective expertise synthesised five key principles that aim to enhance the design, implementation and outcomes of threatened species monitoring. These principles are (i) integrate monitoring with management; (ii) design fit‐for‐purpose monitoring programs; (iii) engage people and organisations; (iv) ensure good data management; and (v) communicate the value of monitoring. We describe how to incorporate these principles into existing frameworks to improve current and future monitoring programs. Effective monitoring is essential to inform appropriate management and enable better conservation outcomes for our most vulnerable species and ecological communities.
Indigenous knowledge systems hold detailed information on current and past environments that can inform ecological understanding as well as contemporary environmental management. Despite its applicability, there are limited examples of indigenous knowledge being incorporated in species distribution models, which are widely used in the ecological sciences. In a collaborative manner, we designed a structured elicitation process and statistical framework to combine indigenous knowledge with survey data to model the distribution of a threatened and culturally significant species (greater bilby or mankarr [Macrotis lagotis]). We used Martu (Aboriginal people of the Australian western deserts) occurrence knowledge and presence data from track-based surveys to create predictive species distribution models with the Maxent program. Predictions of species distribution based on Martu knowledge were broader than those created with survey data. Together the Martu and survey models showed potential local declines, which were supported by Martu observation. Both data types were influenced by sampling bias that appeared to affect model predictions and performance. Martu provided additional information on habitat associations and locations of decline and descriptions of the ecosystem dynamics and disturbance regimes that influence occupancy. We concluded that intercultural approaches that draw on multiple sources of knowledge and information types may improve species distribution modeling and inform management of threatened or culturally significant species.
Fundamental to many theories of sexual selection is the expectation that sexual traits, which males use in an attempt to increase mating success, confer costs as well as benefits to individual males. Although evolution of exaggerated male traits is predicted to be halted, by costs applied by natural selection, there is a lack of empirical work devoted to quantitatively establishing whether natural selection opposes sexual selection generated by the preferences of females. In this study, we quantified natural and sexual selection gradients on breeding values for cuticular hydrocarbon (CHC) components of male contact pheromones in Drosophila serrata. As male sexual traits may often be environmentally condition dependent, breeding values were used in the selection analysis to remove the possibility of environmental correlations between the measured trait and fitness biasing estimates of selection. The direction of natural selection was found to oppose sexual selection on a subset of CHCs examined. Opposing natural and sexual selection suggests that further evolution of the male pheromone may in part be limited by costs associated with attractive male CHC blends.
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