The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Training future generations to deliver evidence-based conservation and ecosystem management

Data availability statement: No data was used in this study.Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1002/2688-8319.12032.Supporting Information: eso312032-sup-0001-SuppMat.docx (21.1 KB) available at: https://besjournals.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2F2688-8319.12032&file=eso312032-sup-0001-SuppMat.docx. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.Copyright © 2021 The Authors. 1. To be effective, the next generation of conservation practitioners and managers need to be critical thinkers with a deep understanding of how to make evidence-based decisions and of the value of evidence synthesis. 2. If, as educators, we do not make these priorities a core part of what we teach, we are failing to prepare our students to make an effective contribution to conservation practice. 3. To help overcome this problem we have created open access online teaching materials in multiple languages that are stored in Applied Ecology Resources. So far, 117 educators from 23 countries have acknowledged the importance of this and are already teaching or about to teach skills in appraising or using evidence in conservation decision-making. This includes 145 undergraduate, postgraduate or professional development courses. 4. We call for wider teaching of the tools and skills that facilitate evidence-based conservation and also suggest that providing online teaching materials in multiple languages could be beneficial for improving global understanding of other subject areas. Making informed conservation and ecosystem management choices is based upon a sound understanding of the relevant evidence. There is an increasing wealth of conservation science available, and access to this is becoming easier. But, are conservation practitioners being trained to utilize this information? In conservation, decision-making is often based upon past experience or expert knowledge, as opposed to the full body of scientific literature (e.g., Pullin, Knight, Stone, & Charman, 2004; Rafidimanantsoa, Poudyal, Ramamonjisoa, & Jones, 2018). The failure to include scientific evidence in decision-making has the potential to reduce the effectiveness of management, or even lead to detrimental actions being undertaken (Walsh, Dicks, & Sutherland, 2015). Evidence-based conservation (EBC) seeks to avoid this by providing tools to facilitate and inform decision-making. To do this, scientific evidence is collated and critically appraised for its quality and relevance, and integrated with other knowledge, experience, values and costs (Sutherland, Pullin, Dolman, & Knight, 2004). Wider adoption of EBC requires conservation professionals to be trained in its principles and taught how to use it to inform conservation decision-making.MAVA Foundation; Arcadia Fund

Density-dependent population dynamics and dispersal in heterogeneous metapopulations.

1. Metapopulation microcosms were constructed to test the effect of four different types of habitat heterogeneity on the dynamics and dispersal in spatially extended systems; homogeneity, spatial heterogeneity, temporal heterogeneity and spatio-temporal heterogeneity. Resources were distributed across discrete habitat patches in bruchid beetle (Callosobruchus maculatus) metapopulations, and long-term time series were recorded. 2. Mathematical models were fitted to the long-term time series from the experimental systems using a maximum likelihood approach. Models were composed of separate birth, death, emigration and immigration terms all of which incorporated stochasticity drawn from different probability distributions. Models with density-dependent and density-independent birth, death and emigration terms were investigated and, in each case, the model that best described the empirical data was identified. 3. At the local scale, population sizes differed between patches depending on the type of heterogeneity. Larger populations were associated with higher resource availabilities. As a result of this, the variation between local population sizes was greatest when there was spatial heterogeneity in which mean resource abundance varied from patch to patch. Variation in population sizes within patches was largest when there was temporal heterogeneity. 4. Density-dependent processes leading to the regulation of local population dynamics in our experimental systems were strongest in homogeneity or temporal heterogeneity treatments. Associated with this, we found that these systems were best described using mathematical models with density dependence acting on mortality. In contrast, spatial and spatio-temporal time series were adequately described using density-independent population processes. 5. Experimental metapopulations showed varying degrees of density-dependent dispersal. Local net dispersal each week was primarily driven by the local population size and secondarily affected by neighbourhood population density. Mathematical population models illustrated the importance of explicit description of density-dependent dispersal in all systems except the homogeneous metapopulations

High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation

By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation (http://www.immunophenotype.org). Specifically, high-throughput phenotyping of 530 unique mouse gene knockouts identified 140 monogenic ‘hits’, of which most had no previous immunologic association. Furthermore, hits were collectively enriched in genes for which humans show poor tolerance to loss of function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with each other and with specific physiologic traits. Such linkages limit freedom of movement for individual immune parameters, thereby imposing genetically regulated ‘immunologic structures’, the integrity of which was associated with immunocompetence. Hence, we provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease