Research & Publications

Abstract Roadkill is widely recognized as one of the primary negative effects of roads on many wildlife species and also has socioeconomic impacts when they result in accidents. A comprehensive dataset of roadkill locations is essential to evaluate the factors contributing to roadkill risk and to enhance our comprehension of its impact on wildlife populations and socioeconomic dimensions. We undertook a compilation of roadkill records, encompassing both published and unpublished data gathered from road surveys or opportunistic sources. GLOBAL ROADKILL DATA includes 208,570 roadkill records of terrestrial vertebrates from 54 countries across six continents, encompassing data collected between 1971 and 2024. This dataset serves to minimise the collection of redundant data and acts as a valuable resource for local and macro scale analysis regarding rates of roadkill, road- and landscape-related features associated with risk of roadkill, vulnerability of species to road traffic, and populations at risk of local extinction. The objective of this dataset is to promote scientific progress in infrastructure ecology and terrestrial vertebrate conservation while limiting the socio-economic costs.

Abstract Cognitive resilience (CR) describes the phenomenon of individuals evading cognitive decline despite prominent Alzheimer’s disease neuropathology. Operationalization and measurement of this latent construct is non-trivial as it cannot be directly observed. The residual approach has been widely applied to estimate CR, where the degree of resilience is estimated through a linear model’s residuals. We demonstrate that this approach makes specific, uncontrollable assumptions and likely leads to biased and erroneous resilience estimates. This is especially true when information about CR is contained in the data the linear model was fitted to, either through inclusion of CR-associated variables or due to correlation. We propose an alternative strategy which overcomes the standard approach’s limitations using machine learning principles. Our proposed approach makes fewer assumptions about the data and CR and achieves better estimation accuracy on simulated ground-truth data.

Abstract Food security information systems (FSIS) face unprecedented threats from abrupt shifts in political and funding priorities, misinformation, and manipulation. We draw on 50 years of research in Food Policy and the broader FSIS literature to offer five resilience characteristics to guide development of a future-fit FSIS: (1) safeguard integrity and impartiality; (2) ensure independent and transparent governance; (3) optimize data and analysis value streams for decision-making; (4) break down sectoral barriers for holistic food security characterization; and (5) innovate responsibly while embedding accountability and learning. We suggest recommended actions based on these resilience characteristics to co-create a more resilient FSIS ecosystem to guide humanitarian responses, advance preventive action for acute crises, and efficiently deliver results.

Abstract Although modifiable risk factors may account for around 40 % of population variability in dementia risk, the effect of risk factor interrelationships on pathology-cognition relationships is poorly understood. Using risk factor data from a cohort of 203 cognitively normal older adults (73 ± 6.4 years, 56 % female), we used k-means clustering to assign participants to one of three risk-related profiles; namely, positive-active (physical/cognitive activity, education), positive-affective (sleep, depression, personality), and negative multi-domain clusters. Linear mixed-effects models showed an attenuated effect of β-amyloid on non-memory cognition decline in positive profiles (positive-active: β=3.7, p = 0.008, positive-affective: β=3.7, p = 0.007) compared to the negative profile. While a significant entorhinal tau x time effect (p < 0.001) was observed in a model predicting episodic memory decline, cluster membership did not modify this relationship. These findings suggest that different risk profiles moderate pathology-cognition relationships, and highlight the role of groups of modifiable resilience factors in mitigating the effects of β-amyloid deposition.

Abstract Cortical tau deposition begins in higher-order association regions and spreads to lower-order primary sensory-motor networks in moderate/advanced Alzheimer's dementia. The neural mechanisms underlying this spatiotemporal pattern remain elusive. Initial evidence has shown that coupled dynamic, low-frequency (<0.1 Hz) brain activity in cerebrospinal fluid (CSF) flow and gray matter (global brain-CSF coupling) might be related to CSF clearance and thus β-amyloid accumulation. Here, we report that tau deposition in higher-order regions, particularly individuals with evaluated β-amyloid, is related to decreased global brain-CSF coupling in humans. Brain dynamics manifesting as propagating waves between higher- and lower-order regions mediate the association between tau and global brain-CSF coupling. Preferential tau deposition in higher-order regions is associated with weaker activation strength there during propagation and less involvement in global brain activity and CSF inflow. The findings suggest an important role of dynamic, spontaneous global brain activity in Alzheimer's tau pathology and cognition.