Explore the vast range of titles available.

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance1. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations2. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index3, and three climatic variables that drive vegetation productivity4 (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing5. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Attractive Targeted Sugar Baits (ATSB) have been demonstrated to result in significant reductions in malaria vector numbers in areas of scarce vegetation cover such as in Mali and Israel, but it is not clear whether such an effect can be replicated in environments where mosquitoes have a wide range of options for sugar resources. The current study evaluated the attractiveness of the predominant flowering plants of Asembo Siaya County, western Kenya in comparison to an ATSB developed by Westham Co. Sixteen of the most common flowering plants in the study area were selected and evaluated for relative attractiveness to malaria vectors in semi-field structures. Six of the most attractive flowers were compared to determine the most attractive to local Anopheles mosquitoes. The most attractive plant was then compared to different versions of ATSB. In total, 56,600 Anopheles mosquitoes were released in the semi-field structures. From these, 5150 mosquitoes (2621 males and 2529 females) of An . arabiensis , An . funestus and An . gambiae were recaptured on the attractancy traps. Mangifera indica was the most attractive sugar source for all three species while Hyptis suaveolens and Tephrosia vogelii were the least attractive plants to the mosquitoes. Overall, ATSB version 1.2 was significantly more attractive compared to both ATSB version 1.1 and Mangifera indica . Mosquitoes were differentially attracted to various natural plants in western Kenya and ATSB. The observation that ATSB v1.2 was more attractive to local Anopheles mosquitoes than the most attractive natural sugar source indicates that this product may be able to compete with natural sugar sources in western Kenya and suggests this product may have the potential to impact mosquito populations in the field.

Smallholder farmers dependent on rain-fed agriculture are particularly vulnerable to extreme climate events and, therefore, it is necessary to identify adaptive measures that would increase farmer resilience to these shocks. The management options in a low-input system, like forest coffee (Coffea arabica), are limited and there are several factors out of farmers' control driving their vulnerability to changing climatic conditions. These can relate to social structures and landscape factors, which can interact to reduce farmers' adaptive capacity, creating a state of contextual vulnerability. We explored the potential synergies of this interaction across elevation, patch area and shade management gradients for smallholder coffee farms around the UNESCO Yayu Coffee Forest Biosphere Reserve in Ethiopia before, during and immediately following the 2015/16 El Niño. We documented a dramatic collapse in coffee yields across all farms, resulting in coffee incomes 29.5% 18.0% and 19.5% 10.0% of 2014 incomes in 2015 and 2016, respectively. We identified farms at elevations between 1500 and 1600 m with canopy openness between 40% and 45% as being consistently low yielding over our study period. We found these farmers had the highest rates of income diversification and, therefore, were already exhibiting adaptive capacity. Farmers with the largest income losses were spatially concentrated between 1600 and 1700 m, located in larger patch areas with lower canopy openness. Farmers at this elevation have access to poor infrastructure, restrictions on shade management and reported higher dependence on income from coffee, indicating an interaction of biotic and social factors exacerbating their vulnerability. Unfortunately, due to a nationally declared state of emergency, we were unable to survey farmers on the adaptive measures they undertook; therefore, we are limited in assessing their resilience. However, we do show the importance of considering both biotically and socially-mediated influences for assessing smallholder vulnerability, particularly barriers to diversifying incomes.

Management for pheasant shooting is a widespread land use in the UK, with potential implications for forest and hedgerow habitats. This study evaluates whether sites managed for pheasant shooting differ ecologically from similar sites not used for shooting. A systematic evidence evaluation of comparative studies was combined with a spatial analysis using remote sensing data (2010–2024). The literature review identified only 32 studies meeting strict criteria for comparability, revealing inconsistent and often weak evidence, with few studies reporting detailed forest management or statistically robust outcomes. While some studies noted increased or decreased biodiversity associated with pheasant shooting, the evidence base was generally of low quality. Remote sensing assessed forest structural and spectral diversity, intactness, and hedgerow density across 1131 pheasant-managed and 1131 matched control sites. Biodiversity data for birds, plants, and butterflies were sourced from GBIF records. Structural diversity and hedgerow density were significantly higher on pheasant-managed sites, while no significant differences were found in forest spectral diversity, intactness, or biodiversity indicators. Pheasant management may shape certain habitat features but has limited demonstrable effects on overall biodiversity. Further field-based, controlled studies are required to understand causal mechanisms and inform ecologically sustainable shooting practices.

Attractive Targeted Sugar Baits (ATSB) have been demonstrated to result in significant reductions in malaria vector numbers in areas of scarce vegetation cover such as in Mali and Israel, but it is not clear whether such an effect can be replicated in environments where mosquitoes have a wide range of options for sugar resources. The current study evaluated the attractiveness of the predominant flowering plants of Asembo Siaya County, western Kenya in comparison to an ATSB developed by Westham Co. Sixteen of the most common flowering plants in the study area were selected and evaluated for relative attractiveness to malaria vectors in semi-field structures. Six of the most attractive flowers were compared to determine the most attractive to local Anopheles mosquitoes. The most attractive plant was then compared to different versions of ATSB. In total, 56,600 Anopheles mosquitoes were released in the semi-field structures. From these, 5150 mosquitoes (2621 males and 2529 females) of An. arabiensis, An. funestus and An. gambiae were recaptured on the attractancy traps. Mangifera indica was the most attractive sugar source for all three species while Hyptis suaveolens and Tephrosia vogelii were the least attractive plants to the mosquitoes. Overall, ATSB version 1.2 was significantly more attractive compared to both ATSB version 1.1 and Mangifera indica. Mosquitoes were differentially attracted to various natural plants in western Kenya and ATSB. The observation that ATSB v1.2 was more attractive to local Anopheles mosquitoes than the most attractive natural sugar source indicates that this product may be able to compete with natural sugar sources in western Kenya and suggests this product may have the potential to impact mosquito populations in the field.

The Spanish conquest of the Cuchumatanes Highlands (1524–1541 CE) led to dramatic land use changes adhering to colonial practices and values, which included the rearing of livestock, agriculture, timber extraction, mining, and the relocation of indigenous populations to new settlements. These changes are often recorded in historical accounts and official records; however, these are sparse, incomplete, and have been lost over the passage of time. Here, we present a high-resolution palaeoenvironmental reconstruction for Cenote Kail (Guatemala) since the Spanish Conquest, to provide additional evidence of land use changes from an integrated multi-proxy perspective. We analysed: (i) fossil pollen; (ii) macroscopic and microscopic charcoal; and (iii) dung fungal spores (Sporormiella) from a lake sediment core extracted from Cenote Kail in the Cuchumatanes highlands, combining these analyses with remotely sensed satellite data. We reconstructed: (i) forest composition and dynamics; (ii) burning, (iii) fauna abundance, and (iv) agricultural activities. High resolution age-depth modelling was conducted using a combination of ²¹⁰Pb and ¹⁴C dates. The high temporal resolution enabled a novel integrated validation of the charcoal data sets with remotely sensed satellite data and the historical record. Three stages of floral compositional change were discerned from the palynological assemblage data encompassing: (i) the decline of mixed hard wood forests (MHWF), associated with the building of new settlements, agriculture and timber extraction for fuel (1550–1675 CE); (ii) pastoral expansions involving the rearing of livestock (1700–1800 CE); and (iii) the expansions of urban settlements and increasing management of the land (1821–2015 CE). Seed predation is suggested as the dominant factor preventing MHWF from re-establishing in the Cuchumatanes Highlands over the past 500 years. Burning is limited locally and regionally and in line with the modern regime, which suggests that fire has been managed and controlled since European contact.

Participatory Ecological Monitoring (PEM) Is a conservation methodology aiming to Include local communities In the collection and analysis of biodiversity and threats data in a managed conservation zone. Often implemented annually, PEM optimises local knowledge to help understand ecological change which is an essential step towards assessing the success or failure of conservation activity and improving conservation effectiveness.

Population‐level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite‐derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green‐up for a 385‐ha mixed‐deciduous woodland. Using data spanning 13 years, we demonstrate that annual population‐level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite‐derived spring vegetation phenology. We go on to show that timing of local vegetation green‐up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote‐sensed vegetation phenology and reproductive phenology in both species. Marked within‐population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small‐scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within‐population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment. Current understanding of how animals synchronise life history events, such as the production of offspring, with the phenology of their food source is limited by the fact that the majority of studies simply correlate average phenotypes across years, neglecting a potentially important spatial dimension in the environment within populations. In this study we use the classic tri‐trophic system of passerine songbirds, caterpillars, and deciduous tree to explore whether satellite‐derived measures of vegetation spring green‐up can be used to predict within‐population variation in great tit (Parus major) and blue tit (Cyanistes caeruleus) breeding phenology. We show that timing of reproduction in both species correlates positively with local vegetation green‐up at the population and individual levels, and that there is marked spatial variation across the study site in the strength of this phenological matching, which can be predicted by habitat type.

With a growing emphasis on the societal benefits gained through recreation outdoors, a method is needed to identify which spaces are most valuable for providing those benefits. Social media platforms offer a wealth of useful information on where people prefer to enjoy the outdoors. We combined geotagged images from Flickr with several environmental metrics in a Maxent model to calculate the probability of a photograph being taken (the potential supply of recreational amenity). We then built a set of population density kernels to express the potential demand of recreational amenity. Linear regression was used to compare supply and demand layers to visitation records from 540 recreation sites across Europe. The result was a map estimating the number of visitors/km2/year. Our analysis showed that natural areas near population centres deliver more recreational benefit than attractive sites in remote locations. The former should therefore be prioritised by planners and policymakers seeking to protect or improve recreational amenity.

The local ecological footprinting tool (LEFT) uses globally available databases, modeling, and algorithms to remotely assess locally important ecological features across landscapes based on five criteria: biodiversity (beta-diversity), vulnerability (threatened species), fragmentation, connectivity, and resilience. This approach can be applied to terrestrial landscapes at a 300-m resolution within a given target area. Input is minimal (latitude and longitude) and output is a computer-generated report and series of maps that both individually and synthetically depict the relative value of each ecological criteria. A key question for any such tool, however, is how representative is the remotely obtained output compared to what is on the ground. Here, we present the results from comparing remotely- vs. field-generated outputs from the LEFT tool on two distinct study areas for beta-diversity and distribution of threatened species (vulnerability), the two fields computed by LEFT for which such an approach is feasible. The comparison method consists of a multivariate measure of similarity between two fields based on discrete wavelet transforms, and reveals consistent agreement across a wide range of spatial scales. These results suggest that remote assessment tools such as LEFT hold great potential for determining key ecological features across landscapes and for being utilized in preplanning biodiversity assessment tools.