A species accumulation curve is frequently applied to predict the overall species richness of a given area when resources for surveying the whole region are unavailable. It typically involves plotting a species accumulation against sampling effort, choosing a mathematical function to fit the curve, and extrapolating final species richness based on the function. Both the order of inputting in sampling data and the selected function affect the shape of the curve and the predicted species richness. Conventionally a randomisation process is used to minimise the prediction error caused by the order of data input. However, this randomisation process means that useful additional information on community structure is lost that may increase the predictive power of species accumulation curves. In this study, the degree to which incorporating nested structure (that is, inputting data from the most species rich to species poor sites, rather than randomly) improves the predictive power of species accumulation functions was assessed, with British avian data as an example. Two methods of ordering input data (randomly and based on nested structure) each for three levels of sampling efforts (10%, 20%, 40%) were fitted to three species accumulation curves functions (negative exponential, logarithmic, and Clench) under two spatial scales (the whole British island and 100 km square). While inputting data based on nested order had similar performance as random order under British island scale, inputs based on nestedness order detectably increase the predictability of total species richness at the 100 km square scale, especially coupled with the logarithmic function. This is probably because there is only one possible curve when ranking sites by nested order (starting with the most species-rich sites) whereas there are many possible curves when ranking sites based on random order. This study demonstrated that sampling according to nested order is generally more favourable than when based on random order. More studies considering different species and study site characteristics are needed to test for the general applicability of using nested order in species accumulation curves.

Detailed spatial data on noise levels are needed to identify quiet areas. Yet noise maps derived from sound propagation models based on traffic flows or sensor networks are often incomplete. Surveys using mobile sound recording coupled with machine learning modelling have offered a possible solution, but so far have focused on averaged noise levels. We argue that quiet areas should ideally be consistently quiet, rather than simply quiet on average, yet mobile survey data usually lack the full temporal profile needed to quantify consistency in noise levels. Using data from our Southampton study area, we show that modification of the loss function used in machine learning modelling of mobile survey data can yield information on the likely range of noise levels at any location across an entire city. We use this approach not only to identify locations that are consistently quiet, but also to help understand which urban features may be associated with quiet, average and noisy events at any given location.

Authoritative, trustworthy, continual, automatic hourly air quality monitoring is a relatively recent innovation. The task of reliably identifying long-term trends in air quality is therefore very challenging, as well as complex. Ports are major sources of atmospheric pollution, which is linked to marine traffic and increased road traffic congestion. This study investigated the long-term trends and drivers of atmospheric pollution in the port cities of Houston, London, and Southampton in 2000–2019. Authoritative air quality and meteorological data for seven sites at these three locations were meticulously selected alongside available traffic count data. Data were acquired for sites close to the port and sites that were near the city centre to determine whether the port emissions were influencing different parts of the city. Openair software was used for plots and statistical analyses. Pollutant concentrations at Houston, Southampton and Thurrock (London) slowly reduced over time and did not exceed national limits, in contrast to NO2 and PM10 concentrations at London Marylebone Road. Drivers of atmospheric pollution include meteorology, geographical and temporal variation, and traffic flow. Statistically significant relationships (p < 0.001) between atmospheric pollution concentration and meteorology across most sites were found, but this was not seen with traffic flows in London and Southampton. However, port emissions and the other drivers of atmospheric pollution act together to govern the air quality in the city.

A long-term historical analysis of the impacts of recreational boating on marine surface water quality during a regatta (Cowes Week) in an internationally crucial waterway, the Solent Strait (Hampshire, UK) is presented. Water quality indicators studied included nitrogen concentration, bacterial indicators, and oxygen saturation, at three sampling sites at/near Cowes during 2001-2019. Findings include that sewage discharge from recreational boats is the key contributor to localised faecal contamination of marine surface waters, putting bathers and shellfisheries at risk. Bathing water quality monitoring and pollution warning systems should be strengthened prior to and during this type of regatta and access to bathing water areas may need to be restricted. These findings have implications for the regulation, future monitoring and management strategies for discharges from recreational boats during extended regattas. Adequate and affordable local facilities for recovering sewage wastewater from recreational boats should be provided alongside appropriate mechanisms for communication to sailors.

Bare board AudioMoth recorders offer a low-cost, open-source solution to passive acoustic monitoring (PAM) but need protecting in an enclosure. We were concerned that the choice of enclosure may alter the spectral characteristics of recordings. We focus on polythene bags as the simplest enclosure and assess how their use affects acoustic metrics. Using an anechoic chamber, a series of pure sinusoidal tones from 100 Hz to 20 kHz were recorded on 10 AudioMoth devices and a calibrated Class 1 sound level meter. The recordings were made on bare board AudioMoth devices, as well as after covering them with different bags. Linear phase finite impulse response filters were designed to replicate the frequency response functions between the incident pressure wave and the recorded signals. We applied these filters to ~1000 sound recordings to assess the effects of the AudioMoth and the bags on 19 acoustic metrics. While bare board AudioMoth showed very consistent spectral responses with accentuation in the higher frequencies, bag enclosures led to significant and erratic attenuation inconsistent between frequencies. Few acoustic metrics were insensitive to this uncertainty, rendering index comparisons unreliable. Biases due to enclosures on PAM devices may need to be considered when choosing appropriate acoustic indices for ecological studies. Archived recordings without adequate metadata may potentially produce biased acoustic index values and should be treated cautiously.

This study presents an important long-term historical analysis of water quality in an internationally crucial waterway (the Solent, Hampshire, UK), in the context of increasing adoption of open-loop Exhaust Gas Cleaning Systems by shipping. The pollutants studied were acidification (pH), zinc, and benzo [a] pyrene, alongside temperature. We compared baseline sites to locations likely to be impacted by pollution. The Solent's average water temperature is slightly increasing, with temperatures at wastewater sites significantly higher. Acidification suggests a complex story, with a highly significant small overall increase in pH during the study period but significantly different values at wastewater and port sites. Zn concentrations have significantly reduced but increased in enclosed waters such as marinas. BaP showed no long-term trend with values at marinas significantly and consistently higher. The findings provide valuable long-term background data and insights that can feed into the upcoming review of the European Union's Marine Strategy Framework Directive and ongoing discussions about the regulation of, and future monitoring and management strategies for coastal/marine waterways.

Urban noise is both a serious environmental pollutant affecting ecological systems, and a major public health issue impacting millions of people worldwide. Noise levels are increasing and, without action, will lead to significant disruption of ecosystem services and a multitude of health effects such as cardiovascular diseases, hypertension, hearing impairment, preterm births, decreased cognitive performance, sleep disturbance, annoyance, anxiety and depression. The covid pandemic presented a unique opportunity to study the soundscape of cities with reduced human activity, especially the decreased use of motor vehicles, a primary source of urban noise. In this paper, we compare noise metrics, psychoacoustic indices and ecoacoustic indices derived from urban transect walks undertaken during (2020) and after (2022) the covid lockdowns in Southampton, UK. In this way, we assess not only noise levels, but also changes to the quality of the urban soundscape. Our aim is to understand the "art of the possible" in improving the soundscapes of active cities, and to help better inform urban planners and health practitioners in tackling a serious yet often hidden environmental crisis.

Forests are key native habitats in temperate environments. While their structure and composition contribute to shaping local-scale community assembly, their role in driving larger-scale species distributions is understudied. We used detailed forest inventory data, an extensive dataset of occurrence records, and species distribution models integrated with a functional approach, to disentangle mechanistically how species-forest dependency processes drive the regional-scale distributions of nine forest specialist bats in a Mediterranean region in the south of Spain. The regional distribution patterns of forest bats were driven primarily by forest composition and structure rather than by climate. Bat roosting ecology was a key trait explaining the strength of the bat-forest dependency relationships. Tree roosting bats were strongly associated with mature and heterogeneous forest with large trees (diameters > 425 mm). Conversely, and contrary to what local-scale studies show, our results did not support that flight-related traits (wing loading and aspect ratio) drive species distributional patterns. Mediterranean forests are expected to be severely impacted by climate change. This study highlights the utility of disentangling species-environment relationships mechanistically and stresses the need to account for species-forest dependency relationships when assessing the vulnerability of forest specialists towards climate change.

Urban noise pollution is a major environmental issue, second only to fine particulate matter in its impacts on physical and mental health. To identify who is affected and where to prioritise actions, noise maps derived from traffic flows and propagation algorithms are widely used. These may not reflect true levels of exposure be -cause they fail to consider noise from all sources and may leave gaps where roads or traffic data are absent. We present an improved approach to overcome these limitations. Using walking surveys, we recorded 52,366 audio clips of 10 s each along 733 km of routes throughout the port city of Southampton. We extracted power levels in low (11 to 177 Hz), mid (177 Hz to 5.68 kHz), high (5.68 to 22.72 kHz) and A-weighted frequencies and then built machine-learning (ML) models to predict noise levels at 30 m resolution across the entire city, driven by urban form. Model performance (r(2)) ranged from 0.41 (low frequencies) to 0.61 (mid frequencies) with mean absolute errors of 4.05 to 4.75 dB. The main predictors of noise were related to modes of transport (road, air, rail and water) but for low frequencies, port activities were also important. When mapped to the city scale, A-weighted frequencies produced a similar spatial pattern to mid-frequencies, but did not capture the major sources of low frequency noise from the port or scattered hotspots of high frequencies. We question whether A-weighted noise mapping is adequate for health and wellbeing impact assessments. We conclude that mobile surveys combined with ML offer an alternative way to map noise from all sources and at fine resolution across entire cities that may more accurately reflect true exposures. Our approach is suitable for noise data gathered by citizen scientists, or from a network of sensors, as well as from structured surveys. (C) 2021 Elsevier B.V. All rights reserved.

Whilst Africa is among the most vulnerable regions to climate change, relevant scenario models suggests that Eastern Africa will be among the regions with the largest decline in agricultural yields in the continent due to increasing mean surface temperatures and GHG concentrations. Climate change impacts in the Eastern African region will include an acceleration of the hydrologic cycle, occasioning increased variance in rainfall. This will particularly impact dryland environments due to their climate sensitive production systems and low adaptive capacities. Context specific adaptive responses will be necessary to reduce vulnerability of communities to environmental change, hence increasing their resilience to climate variability. Such adaptive solutions will require, among others, the building of institutional capacity in technology and governance particularly in the food, energy and water nexus. Appropriate technologies such as rainwater harvesting systems, can be applied for supplemental irrigation, and in conjunction with good agricultural technologies, would ensure food, energy and water security at the household level among the small holders. This chapter discusses regional strategies to address food security, energy needs and water resources in the Eastern African region. It postulates that current sectoral approach is not sustainable and therefore provides a nexus perspective, based on use of Rainwater Harvesting Technologies at the farm level, as a step towards sustainability.

It is surprising difficult to define where a city center lies, yet its location has a profound effect on a city's structure and function. We examine whether city center typicality points can be consistently located on historical maps such that their centroid identifies a meaningful central location over a 500-year period in Southampton, UK. We compare movements of this city center centroid against changes in the geographical center of the city as defined by its boundary. Southampton's historical maps were georectified with a mean accuracy of 21 m (range 9.9 to 47 m), and 18 to 102 typicality points were identified per map, enough to chart changes in the city center centroid through time. Over nearly 500 years, Southampton's center has moved just 343 m, often corresponding with the key retail attractants of the time, while its population has increased 80-fold, its administrative area 60-fold and its geographical center moved 1985 m. This inertia to change in the city center presents environmental challenges for the present-day, made worse by the geography of Southampton, bounded by the sea, rivers and major roads. Geographical context, coupled with planning decisions in the past that maintain a city center in its historical location, place limits on the current sustainability of a city.

The interacting impacts of habitat fragmentation and climate change present a substantial threat for biodiversity, constituting a 'deadly anthropogenic cocktail'. A range of conservation actions has been proposed to allow biodiversity to respond to those environmental changes. However, determining the relative effectiveness of these actions has been hampered by incomplete evidence. Empirical studies have provided important insights to inform conservation, but the challenge of considering multiple actions at large spatial and temporal scales is considerable. We adopt an individual-based modelling approach to qualitatively assess the effectiveness of alternative conservation actions in facilitating range expansion and patch occupancy for eight virtual species. We test actions to: (i) improve the quality of existing habitat patches, (ii) increase the permeability of the surrounding matrix, (iii) restore degraded habitat, (iv) create new habitat patches to form stepping-stones or (v) create new habitat to enlarge existing habitat patches. These actions are systematically applied to six real landscapes of the UK, which differ in their degree of habitat fragmentation and availability. Creating new habitat close to existing patches typically provides the strongest benefits for both range expansion and patch occupancy across species and landscapes. However, some landscapes may be so degraded that even under unrealistically high levels of management action, species' performances cannot be rescued. We identify that it is possible to develop a triage of conservation actions at the landscape, species and investment level, thereby providing timely evidence to inform action on the ground to lessen the hangover from the deadly anthropogenic cocktail.

Continuous exposure to noise can lead to premature hearing loss, reduced cognitive performance, insomnia, stress, hypertension, cardiovascular diseases and stroke. Road noise affects the health of >125 million people in the European Union and Member States are required to map major noise hotspots. These strategic noise maps are usually derived from traffic counts and propagation models because large- scale measurement of the acoustic environment using conventional methods is infeasible. In this study, the authors surveyed the entire city of Southampton, UK using a mobile survey technique, capturing spatial variations in street-level sound characteristics across multiple frequencies from all sound sources. Over 52,000 calibrated and georeferenced sound clips covering 11 Hz to 22.7 kHz are analysed here to investigate variations in sound frequency composition across urban space and then applied to two issues: the definition of naturalness in the acoustic environment; and perceptions of social inequity in sound exposure. Clusters of acoustic characteristics were identified and mapped using spectral clustering and principal components analysis based on octave bands, ecoacoustic indices and dBA. We found independent patterns in low, mid and high frequencies, and the ecoacoustic indices that related to land use. Ecoacoustic indices partially mapped onto greenspace, identifying naturalness, but not uniquely, probably because urban anthropogenic sounds occur at higher frequencies than in the natural areas where such indices were developed. There was some evidence of inequity in sound exposure according to social deprivation and ethnicity, and results differed according to frequency bands. The consequences of these findings and the benefits of city-wide sound surveys for urban planning are discussed.

Understanding the dynamics of socio‐ecological systems is crucial to the development of environmentally sustainable practices. Models of social or ecological sub‐systems have greatly enhanced such understanding, but at the risk of obscuring important feedbacks and emergent effects. Integrated modelling approaches have the potential to address this shortcoming by explicitly representing linked socio‐ecological dynamics. We developed a socio‐ecological system model by coupling an existing agent‐based model of land‐use dynamics and an individual‐based model of demography and dispersal. A hypothetical case‐study was established to simulate the interaction of crops and their pollinators in a changing agricultural landscape, initialised from a spatially random distribution of natural assets. The bi‐directional coupled model predicted larger changes in crop yield and pollinator populations than a unidirectional uncoupled version. The spatial properties of the system also differed, the coupled version revealing the emergence of spatial land‐use clusters that neither supported nor required pollinators. These findings suggest that important dynamics may be missed by uncoupled modelling approaches, but that these can be captured through the combination of currently‐available, compatible model frameworks. Such model integrations are required to further fundamental understanding of socio‐ecological dynamics and thus improve management of socio‐ecological systems.

Sub-national governments are increasingly interested in local-level climate change management.Carbon-(CO 2 and CH 4 ) and climate-footprints-(Kyoto Basket GHGs) (effectively single impact category LCA metrics, for global warming potential) provide an opportunity to develop models to facilitate effective mitigation.Three approaches are available for the footprinting of sub-national communities.Territorial-based approaches, which focus on production emissions within the geo-political boundaries, are useful for highlighting local emission sources but do not reflect the transboundary nature of sub-national community infrastructures.Transboundary approaches, which extend territorial footprints through the inclusion of key cross boundary flows of materials and energy, are more representative of community structures and processes but there are concerns regarding comparability between studies.The third option, consumption-based, considers global GHG emissions that result from final consumption (households, governments, and investment).Using a case study of Southampton, UK, this chapter develops the data and methods required for a sub-national territorial, transboundary, and consumption-based carbon and climate footprints.The results and implication of each footprinting perspective are discussed in the context of emerging international standards.The study clearly shows that the carbon footprint (CO 2 and CH 4 only) offers a low-cost, low-data, universal metric of anthropogenic GHG emission and subsequent management.

The urban heat island effect is an important 21st century issue because it intersects with the complex challenges of urban population growth, global climate change, public health and increasing energy demand for cooling. While the effects of urban landscape composition on land surface temperature (LST) are well-studied, less attention has been paid to the spatial arrangement of land cover types especially in smaller, often more diverse cities. Landscape configuration is important because it offers the potential to provide refuge from excessive heat for both people and buildings. We present a novel approach to quantifying how both composition and configuration affect LST derived from Landsat imagery in Southampton, UK. First, we trained a machine-learning (generalized boosted regression) model to predict LST from landscape covariates that included the characteristics of the immediate pixel and its surroundings. The model achieved a correlation between predicted and measured 1ST of 0.956 on independent test data (n = 102,935) and included predictors for both the immediate and adjacent land use. In contrast to other studies, we found adjacency effects to be stronger than immediate effects at 30 m resolution. Next, we used a landscape generation tool (Landscape Generator) to alter landscape configuration by varying natural and built patch sizes and arrangements while holding composition constant. The generated neutral landscapes were then fed into the machine learning model to predict patterns of LST. When we manipulated landscape configuration, the average city temperature remained the same but the local minima varied by 0.9 degrees C and the maxima by 4.2 degrees C. The effects on LST and heat island metrics correlated with landscape fragmentation indices. Moreover, the surface temperature of buildings could be reduced by up to 2.1 degrees C through landscape manipulation. We found that the optimum mix of land use types is neither at the land-sharing nor land-sparing extremes, but a balance between the two. In our city, maximum cooling was achieved when similar to 60% of land was left natural and distributed in 7-8 patches km(-2) although this could be location dependent and further work is needed. Opportunities for urban cooling should be required in the planning process and must consider both composition and configuration at the landscape scale if cities are to build capacity for a growing population and climate change.

There has been a growing interest across the British conservation community in recent years in establishing conservation over large areas. Much of this thinking was crystallised in the Making Space for Nature report (Lawton and others 2010) , and has since become prominent in conservation policy. To maximise the success of future projects, there is a need to get a better overview of the many large-scale conservation (LSC) initiatives that already exist, and to investigate what can be learned from past experience. To date there has been no thorough study of the scope, spatial extent, management and planning approaches and effectiveness of LSC. This report summarises the results of a research study that provides the first comprehensive review of large-scale conservation initiatives in England, Scotland and Wales. The study was made up of a series of linked research projects with funding and support from Defra, Natural England, Scottish Natural Heritage and Natural Resources Wales and was carried out by the University of Southampton, University of Cambridge, Natural England and Atkins.

There has been a growing interest across the British conservation community in recent years in establishing conservation over large areas. Much of this thinking was crystallised in the Making Space for Nature report (Lawton and others 2010) , and has since become prominent in conservation policy. To maximise the success of future projects, there is a need to get a better overview of the many large-scale conservation (LSC) initiatives that already exist, and to investigate what can be learned from past experience. To date there has been no thorough study of the scope, spatial extent, management and planning approaches and effectiveness of LSC. This report summarises the results of a research study that provides the first comprehensive review of large-scale conservation initiatives in England, Scotland and Wales. The study was made up of a series of linked research projects with funding and support from Defra, Natural England, Scottish Natural Heritage and Natural Resources Wales and was carried out by the University of Southampton, University of Cambridge, Natural England and Atkins.

Visitor tracking is frequently used in tourism planning for large sites, but is far less common at individual attractions, despite a body of literature examining the detrimental impact of crowding on visitor experience. This study used handheld geographic positioning system (GPS) units to track 931 groups of visitors around a single tourist attraction to determine where they went and how long they dwelt at particular locations. The tracking data were combined with survey data to discover whether different types of visitors behaved differently when exploring the attraction. The majority of visitors followed similar routes revealing a strong ‘main path inertia’ with over half missing exhibits away from the perceived main route. Different group types varied in how long they dwelt at different locations and in how long they spent at the attraction altogether.

Protected areas (PAs) are vital for conserving biodiversity, but many PA networks consist of fragmented habitat patches that poorly represent species and ecosystems. One possible solution is to create conservation landscapes that surround and link these PAs. This often involves working with a range of landowners and agencies to develop large-scale conservation initiatives (LSCIs). These initiatives are being championed by both government and civil society, but we lack data on whether such landscape-level approaches overcome the limitations of more traditional PA networks. Here we expand on a previous gap analysis of England to explore to what extent LSCIs improve the representation of different ecoregions, land-cover types and elevation zones compared to the current PA system. Our results show the traditional PA system covers 6.37% of England, an addition of only 0.07% since 2001, and that it is an ecologically unrepresentative network that mostly protects agriculturally unproductive land. Including LSCIs in the analysis increases the land for conservation more than tenfold and reduces these representation biases. However, only 24% of land within LSCIs is currently under conservation management, mostly funded through agri-environment schemes, and limited monitoring data mean that their contribution to conservation objectives is unclear. There is also a considerable spatial overlap between LSCIs, which are managed by different organisations with different conservation objectives. Our analysis is the first to show how Other Effective Area-Based Conservation Measures (OECMs) can increase the representativeness of conservation area networks, and highlights opportunities for increased collaboration between conservation organisations and engagement with landowners.