Aim Decision-making for conservation management often involves evaluating risks in the face of environmental uncertainty. Models support decision-making by (1) synthesizing available knowledge in a systematic, rational and transparent way and (2) providing a platform for exploring and resolving uncertainty about the consequences of management decisions. Despite their benefits, models are still not used in many conservation decision-making contexts. In this article, we provide evidence of common objections to the use of models in environmental decision-making. In response, we present a series of practical solutions for modellers to help improve the effectiveness and relevance of their work in conservation decision-making.Location Global review.Methods We reviewed scientific and grey literature for evidence of common objections to the use of models in conservation decision-making. We present a set of practical solutions based on theory, empirical evidence and best-practice examples to help modellers substantively address these objections.Results We recommend using a structured decision-making framework to guide good modelling practice in decision-making and highlight a variety of modelling techniques that can be used to support the process. We emphasize the importance of participatory decision-making to improve the knowledgebase and social acceptance of decisions and to facilitate better conservation outcomes. Improving communication and building trust are key to successfully engaging participants, and we suggest some practical solutions to help modellers develop these skills.Main conclusions If implemented, we believe these practical solutions could help broaden the use of models, forging deeper and more appropriate linkages between science and management for the improvement of conservation decision-making.

Plant and animal survey detection rates are important for ecological surveys, environmental impact assessment, invasive species monitoring, and modeling species distributions. Species can be difficult to detect when rare but, in general, how detection probabilities vary with abundance is unknown. We developed a new detectability model based on the time to detection of the first individual of a species. Based on this model, the predicted detection rate is proportional to a power function of abundance with a scaling exponent between zero and one that depends on clustering of individuals. We estimated the model parameters with data from three independent datasets: searches for chenopod shrub species and coins, experimental searches for planted seedlings, and frog surveys at multiple sites in sub‐tropical forests of eastern Australia. Analyses based on the detection time and detection probability suggest that detection rate increases with abundance as predicted. The model provides a way to scale detection rates to cases of low abundance when direct estimation of detection rates is often impractical.

Substantial advances have been made in our understanding of the movement of species, including processes such as dispersal and migration. This knowledge has the potential to improve decisions about biodiversity policy and management, but it can be difficult for decision makers to readily access and integrate the growing body of movement science. This is, in part, due to a lack of synthesis of information that is sufficiently contextualized for a policy audience. Here, we identify key species movement concepts, including mechanisms, types, and moderators of movement, and review their relevance to (1) national biodiversity policies and strategies, (2) reserve planning and management, (3) threatened species protection and recovery, (4) impact and risk assessments, and (5) the prioritization of restoration actions. Based on the review, and considering recent developments in movement ecology, we provide a new framework that draws links between aspects of movement knowledge that are likely the most relevant to each biodiversity policy category. Our framework also shows that there is substantial opportunity for collaboration between researchers and government decision makers in the use of movement science to promote positive biodiversity outcomes.