KEVIN J GASTON

Soga, M. & Gaston, K.J. 2024. Extinction of experience due to climate change. Nature Climate Change 14, 108-110.

Ongoing climate change has the potential to reduce people’s direct experiences with nature, leading to or further exacerbating the ‘extinction of experience’. We argue that understanding these impacts is crucial, as the extinction of experience can have adverse consequences for both humans and the natural environment.

Morrell, S., Hatchell, J., Wordingham, F., Bennie, J., Inston, M.J. & Gaston, K.J. 2024. Changing streetlighting schemes and the ecological availability of darkness. Journal of the Royal Society Interface 21, 20230555.

Artificial light at night (ALAN), from streetlights and other sources, has a wide variety of impacts on the natural environment. A significant challenge remains, however, to predict at intermediate spatial extents (e.g. across a city) the ALAN that organisms experience under different lighting regimes. Here we use Monte Carlo radiative Transfer to model the three-dimensional lighting environment at, and just above, ground level, on the spatial scales at which animals and humans experience it. We show how this technique can be used to model a suite of both real and hypothetical lighting environments, mimicking the transition of public infrastructure between different lighting technologies. We then demonstrate how the behaviour of animals experiencing these simulated lighting environments can be emulated to probe the availability of darkness, and dark corridors, within them. Our simulations show that no single lighting technology provides an unmitigated alleviation of negative impacts within urban environments, and that holistic treatments of entire lighting environments should be employed when understanding how animals use and traverse them.

Marini, L., Batáry, P., Carmenta, R., Gaston, K.J., Gordon, R., Macinnis-Ng, C., Mori, A.S., Nuñez, M. & Barlow, J. 2024. Ecology and conservation under ageing and declining human populations. Journal of Applied Ecology 61, 1982-1988.

1. Much research and media attention has revolved around the environmental impacts of growing global human populations. While the conclusions remain contested, these assessments have largely neglected the ecological and conservation impacts of other key regional processes such as declining populations, ageing demographics and rural-to-urban migration.

2. These demographic shifts are increasingly prevalent across many regions of the world, and will have significant direct effects on natural resource management and biodiversity conservation by altering individual consumption patterns, land use, land stewardship and natural disturbances. Given that the scientific foundation around this topic is still developing, we first present an initial examination of some of the key environmental impacts, aiming to elevate awareness and encourage further research in these areas.

3. Beyond the ecological implications, declining populations, ageing demographics and rural-to-urban migration carry intricate social and cultural consequences that can affect people and nature interactions. Ecological studies that focus on single dimensions of biodiversity or ecosystem responses often overlook these complexities. Demographic changes are likely to be accompanied by shifts in environmental attitudes and connections with nature, all of which will influence our capacity to adapt to or mitigate environmental changes. Finally, environmental policy and practice frameworks are potentially unprepared and their success could be sensitive to these socio-cultural and demographic shifts.

4. Synthesis and applications: This brief overview demonstrates that population decline, ageing and rural-to-urban migration can have extensive implications for biodiversity and the socio-cultural relationships between people and nature.

Gaston, K.J. 2024. Characterizing personalized ecologies. Journal of Zoology 322, 291-308.

People have unique sets of direct sensory interactions with wild species, which change through their days, weeks, seasons, and lifetimes. Despite having important influences on their health and well-being and their attitudes towards nature, these personalized ecologies remain surprisingly little studied and are poorly understood. However, much can be inferred about personalized ecologies by considering them from first principles (largely macroecological), alongside insights from research into the design and effectiveness of biodiversity monitoring programmes, knowledge of how animals respond to people, and studies of human biology and demography. Here I first review how three major sets of drivers, opportunity, capability and motivation, shape people’s personalized ecologies. Second, I then explore the implications of these mechanisms for how more passively and more actively practical improvements can be made in people’s personalized ecologies. Particularly in light of the declines in the richness of these ecologies that are being experienced in much of the world (the so-called ‘extinction of experience’), and the significant consequences, marked improvement in many people’s interactions and experiences with nature may be key to the future of biodiversity.

Cox, D.T.C. & Gaston, K.J. 2024. Ecosystem functioning across the diel cycle in the Anthropocene. Trends in Ecology and Evolution39, 31-40.

Given the marked differences in environmental conditions and active biota between daytime and nighttime, it is almost inevitable that ecosystem functioning will also differ. However, understanding of these differences has been hampered due to the challenges of conducting research at night. At the same time, many anthropogenic pressures are most forcefully exerted or have greatest effect during either daytime (e.g., high temperatures, disturbance) or nighttime (e.g., artificial lighting, nights warming faster than days). Here,we explore current understanding of diel (daily) variation in five key ecosystem functions and when during the diel cycle they primarily occur [predation (unclear), herbivory (nighttime), pollination (daytime), seed dispersal (unclear), carbon assimilation (daytime)] and how diel asymmetry in anthropogenic pressures impacts these functions.

Cox, D.T.C. & Gaston, K.J. 2024. Cathemerality: a key temporal niche. Biological Reviews 99, 329-347.

Given the marked variation in abiotic and biotic conditions between day and night, many species specialise their physical activity to being diurnal or nocturnal, and it was long thought that these strategies were commonly fairly fixed and invariant. The term ‘cathemeral’, was coined in 1987, when Tattersall noted activity in a Madagascan primate during the hours of both daylight and darkness. Initially thought to be rare, cathemerality is now known to be a quite widespread form of time partitioning amongst arthropods, fish, birds, and mammals. Herein we provide a synthesis of present understanding of cathemeral behaviour, arguing that it should routinely be included alongside diurnal and nocturnal strategies in schemes that distinguish and categorise species across taxa according to temporal niche. This synthesis is particularly timely because (i) the study of animal activity patterns is being revolutionised by new and improved technologies; (ii) it is becoming apparent that cathemerality covers a diverse range of obligate to facultative forms, each with their own common sets of functional traits, geographic ranges and evolutionary history; (iii) daytime and nighttime activity likely plays an important but currently neglected role in temporal niche partitioning and ecosystem functioning; and (iv) cathemerality may have an important role in the ability of species to adapt to human-mediated pressures.

Baker, D.J., Maclean, I.M.D. & Gaston, K.J. 2024. Effective strategies for correcting spatial sampling bias in species distribution models without independent test data. Diversity and Distributions 30, e13802.

Aim: Spatial sampling bias (SSB) is a feature of opportunistically sampled species
records. Species distribution models (SDMs) built using these data (i.e. presence-background models) can produce biased predictions of suitability across geographic
space, confounding species occurrence with the distribution of sampling effort. A
wide range of SSB correction methods have been developed but simulations suggest
effects on predictive performance are highly variable. Here, we aim to identify the
SSB correction methods that have the highest likelihood of improving true predictive
performance and evaluation strategies that provide a reliable indicator of model performance when independent test data are unavailable.
Location: Global, simulation.
Time Period: Current, simulation.
Methods: A meta-analysis was used to evaluate the performance of SSB correction
methods in studies where there were direct comparisons between corrected and uncorrected SDMs. A simulation model was then developed to test evaluation strategies against a known truth using four common SSB correction methods.
Results: Effect sizes from published studies suggest some support for small positive
effects of SSB correction on predictive performance when assessed using independent
test data, but this was not evident using internal cross-validation and no single method stood out as consistently effective. Simulations support these findings and show that evaluation using internal test data was generally a poor indicator of the true effect of SSB correction. Methods that adjust models relative to a known driver of SSB produced the largest performance gains, but were also the most inconsistent.
Main Conclusions: Correcting SSB in presence-background SDMs without independent test data to evaluate the effect on model performance requires careful implementation. We recommend clearer documentation of SSB correction effects on SDMs, presenting results from models with and without correction, evaluating effects of different assumptions of SSB implementation on predictions, as well as greater efforts to collect independent test datasets to validate model predictions.