Experiences of nature provide many mental-health benefits, particularly for people living in urban areas. The natural characteristics of city residents’ neighborhoods are likely to be crucial determinants of the daily nature dose that they receive; however, which characteristics are important remains unclear. One possibility is that the greatest benefits are provided by characteristics that are most visible during the day and so most likely to be experienced by people. We demonstrate that of five neighborhood nature characteristics tested, vegetation cover and afternoon bird abundances were positively associated with a lower prevalence of depression, anxiety, and stress. Furthermore, dose–response modeling shows a threshold response at which the population prevalence of mental-health issues is significantly lower beyond minimum limits of neighborhood vegetation cover (depression more than 20% cover, anxiety more than 30% cover, stress more than 20% cover). Our findings demonstrate quantifiable associations of mental health with the characteristics of nearby nature that people actually experience.

Fifty years ago, volunteers began annual breeding bird surveys in woodlands as part of the Common Bird Census. Few probably would have anticipated the enormous changes the bird communities in those woodlands have shown, but their data have been a gold-mine for understanding how the many guises of environmental change are impacting birds. In our latest study we worked with colleagues at the University of Reading, Centre for Ecology and Hydrology, Butterfly Conservation and Natural England to assess how climate change and habitat interact to affect bird and butterfly populations. As climate warms, we expect species that are tolerant of warm climates to be least affected, or indeed to benefit in areas that were formerly too cold for them. Conversely, species that prefer cold climates are expected to fare poorly, perhaps by declining or retreating from warming areas. Following previous studies, we used the Species Temperature Index (STI), which corresponds to the average temperature across the European range of each species, to rank bird and butterfly species from cold-associated (e.g. Meadow Pipit, Willow Warbler, Chequered Skipper, Northern Brown Argus) to warm-associated (e.g. Cetti’s Warbler, Stonechat, Lulworth Skipper, Gatekeeper). Several studies have combined these STI values with the species’ population trends at individual sites to produce a composite “Community Temperature Index” (CTI). Most studies find this CTI is increasing, which is usually taken to mean that the community is increasingly dominated by species that prefer warm conditions. We took this further by looking separately at how the different species in the communities are faring. Although the bird community CTIs had increased, changes for constituent species weren’t as predicted. For example, the top 25% of birds as ranked by warmth-association had not increased as predicted but had declined on average. The overall increase in bird CTI was driven by a large decline in the abundance of the most cold-associated species and an increase for moderately warm-associated species. Importantly, the extent of the declines of the most cold- and warm-associated species was related to the amount of intensively managed land surrounding the monitored woodlands. This suggests that the lack of natural habitat in the surroundings makes it harder for cold-associated birds to find cool corners of sites, or to disperse away from warming regions. Butterfly results were subtly different but with similar conclusions about the role of intensively managed land. This provides a clear recommendation to land managers and conservation agencies – creating larger natural areas in strategic places will help species to cope with the changing climate.

Renewable energy is a key part of strategies to reduce the effects of climate change. However, there are concerns about the potential impacts of large renewable developments, such as offshore wind farms, on wildlife. A significant amount of research has been directed at understanding how these developments may affect marine wildlife, particularly seabirds. Key impacts on seabirds are likely to include increased mortality through collisions with wind turbines, and displacement from preferred foraging areas. However, whilst we can estimate what impact any development may have at an individual level, understanding what this means for the population as a whole is more complex. New research led by Aonghais Cook of the BTO has tested a variety of analytical tools, or models, to assess the likely population-level consequences of the impacts arising from any individual wind farm development. These include tools predicting the likelihood of a given outcome (e.g. the probability of a 25% decline) and those that compare scenarios with and without the development. The results demonstrate that conclusions about the significance of any population-level consequences differ according to the initial assumptions made about a seabird species’ survival, breeding success and population trend. The effect of these assumptions is particularly noticeable for approaches that predict the likelihood of a given outcome. In a world where our knowledge of wildlife populations is often imperfect, this may lead to situations where conclusions about the significance of any population-level impacts are driven by how knowledgeable we are about the population concerned, rather than by the magnitude of any impact. This research suggests that future assessments should compare the outputs of models considering scenarios for wildlife with and without any wind farm development. However, given that our knowledge of the population concerned can influence our conclusions, it is important that all assumptions used in the modelling are clearly stated. Judgement of whether any population-level consequences can be deemed acceptable should then be made with reference to our knowledge of the species concerned and its local, regional, national and international populations, ensuring that decisions about offshore wind farm development are made in the best possible way for wildlife.

As the effects of climate change are becoming ever more evident and widespread, methods to measure the impact on ecological communities and to understand how such impacts occur are more valuable. Recently published research, led by the BTO in collaboration with the Centre for Ecology and Hydrology, BioSS, Butterfly Conservation and Rothamsted Research, describes the development of a new indicator for detecting the effect of climate change in British butterflies and moths, which also provides new insights into when species are most sensitive to change. Data from the UK Butterfly Monitoring Scheme and the Rothamsted Insect Survey were used to calculate population trends over a 35 year period and to model each species’ population response to seasonal temperatures. These estimates of species’ responses to temperature can be used to describe communities according to how they have been shaped by temperature - the Community Temperature Response (CTR). A rise in CTR occurs when populations of species which ‘do better’ in warmer conditions increase in abundance more than populations of species whose populations ‘like’ it cold. Using twenty years of butterfly and moth data from twelve UK Environmental Change Network sites run by the Centre for Ecology and Hydrology we tested whether this indicator could track spatial and temporal climate-driven community change. The authors, led by Blaise Martay, predicted that moth and butterfly communities in warmer sites and years would contain more individuals of species that increase in response to rising temperatures, than those in the colder sites and years. Although they didn’t find this relationship if species’ response to annual temperature was used to describe the community, they instead found that communities were shaped by seasonal temperatures. In particular, moth communities were influenced most by summer temperature while winter temperature was the strongest driver of butterfly communities. Importantly, this shows that the CTR indicator can effectively indicate the biological impacts of climate change over time. Seasonal as well as annual temperatures must therefore be considered when predicting species’ vulnerability to climate change. It has been previously assumed that British butterflies will be fairly resilient to climate change because temperatures in Britain are colder than in much of their European range and populations tend to increase in response to warmer summer weather. However, as winter temperatures were found to be the main driver of butterfly community change, British butterflies may be more vulnerable to climate change than previously thought.