Jim Christopher Rudd Smart

Predictable waves of sequential forest degradation and biodiversity loss spreading from an African city

Tropical forest degradation emits carbon at a rate of ~0.5 Pg·y−1, reduces biodiversity, and facilitates forest clearance. Understanding degradation drivers and patterns is therefore crucial to managing forests to mitigate climate change and reduce biodiversity loss. Putative patterns of degradation affecting forest stocks, carbon, and biodiversity have variously been described previously, but these have not been quantitatively assessed together or tested systematically. Economic theory predicts a systematic allocation of land to its highest use value in response to distance from centers of demand. We tested this theory to see if forest exploitation would expand through time and space as concentric waves, with each wave targeting lower value products. We used forest data along a transect from 10 to 220 km from Dar es Salaam (DES), Tanzania, collected at two points in time (1991 and 2005). Our predictions were confirmed: high-value logging expanded 9 km·y−1, and an inner wave of lower value charcoal production 2 km·y−1. This resource utilization is shown to reduce the public goods of carbon storage and species richness, which significantly increased with each kilometer from DES [carbon, 0.2 Mg·ha−1; 0.1 species per sample area (0.4 ha)]. Our study suggests that tropical forest degradation can be modeled and predicted, with its attendant loss of some public goods. In sub-Saharan Africa, an area experiencing the highest rate of urban migration worldwide, coupled with a high dependence on forest-based resources, predicting the spatiotemporal patterns of degradation can inform policies designed to extract resources without unsustainably reducing carbon storage and biodiversity.

Diving behaviour of whale sharks in relation to a predictable food pulse

We present diving data for four whale sharks in relation to a predictable food pulse (reef fish spawn) and an analysis of the longest continuous fine-resolution diving record for a planktivorous shark. Fine-resolution pressure data from a recovered pop-up archival satellite tag deployed for 206 days on a whale shark were analysed using the fast Fourier Transform method for frequency domain analysis of time-series. The results demonstrated that a free-ranging whale shark displays ultradian, diel and circa-lunar rhythmicity of diving behaviour. Whale sharks dive to over 979.5 m and can tolerate a temperature range of 26.4 °C. The whale sharks made primarily diurnal deep dives and remained in relatively shallow waters at night. Whale shark diving patterns are influenced by a seasonally predictable food source, with shallower dives made during fish spawning periods.

Evaluating farmers’ likely participation in a payment programme for water quality protection in the UK uplands

Maintaining drinking water quality is essential to water companies and their customers, and agricultural non-point source pollution is a major cause of water quality degradation. In this paper, we examine the potential use of payments financed by a water company as incentives for farmers to adjust their agricultural land management practices in order to protect water quality. We use a choice experiment (CE) to measure farmers’ minimum willingness to accept (WTA) requirements to adjust agricultural land management practices in Nidderdale and the Washburn valley (Yorkshire, UK) under a potential local payment for ecosystem services (PES) programme. Latent class analysis of farmers’ CE responses was used to quantify the size and spread of farmers’ preferences and minimum WTA values for compensation payments, and to investigate potential drivers of preference variation. Analysis suggested that the emphasis on sheep or cattle/dairy production within mixed farming businesses in this area provides a partial explanation for the considerable observed heterogeneity in preferences and minimum WTA requirements for participation in a potential PES programme.

Benefits of meeting nutrient reduction targets for the Baltic Sea - a contingent valuation study in the nine coastal states

This paper presents the results of an internationally coordinated contingent valuation study on the benefits of reducing marine eutrophication in the Baltic Sea according to current policy targets. With over 10,500 respondents from the nine coastal states around the sea, we examine public willingness to pay (WTP) for reduced eutrophication and its determinants. There are considerable differences in mean WTP between countries, with Swedes being willing to pay the most and Latvians the least. The aggregate annual WTP is approximately €3600 million. In addition, we find that countries are heterogeneous in terms of the effects of income, attitudes and familiarity on WTP. Income elasticities of WTP are below 1 for all countries, ranging between 0.1 and 0.5. Attitudes and personal experience of eutrophication are important determinants of WTP, but the specific effects differ between countries. The findings can be used in economic analyses for the European Union (EU) Marine Strategy Framework Directive and to justify additional eutrophication reduction measures in the Baltic Sea.

The current and future management of wild mammals hunted with dogs in England and Wales

There is increasing concern about the use of lethal methods to control wild mammal populations, especially those methods that may have significant impacts on animal welfare. The continued use of dogs to hunt wild mammals in England and Wales, principally foxes (Vulpes vulpes), red deer (Cervus elaphus), brown hares (Lepus europaeus) and mink (Mustela vison), has become a focus for political debate and has been the subject of a recent UK government inquiry. This paper reports the results of a questionnaire study to quantify the use, effectiveness and acceptability of the different methods currently used to manage these four species, and future changes in management following a possible ban on hunting with dogs. There was no straightforward relationship between culling pressure and perceived pest status of the different species from the questionnaire data. For foxes and brown hares, the proportion of land managers (practitioners) carrying out lethal control was higher than that considering these species to be pests. However, the reverse was the case for mink. The most frequently used and effective control methods, which were most acceptable to practitioners and public alike, were various forms of shooting. The general public perceived hunting with dogs as one of the least acceptable means of control for all four species. Practitioners thought that hunting with dogs for red deer and the use of terriers against foxes were among the least acceptable forms of control, but considered hunting with dogs in other situations and for other species to be relatively acceptable. Most practitioners said a ban on hunting with dogs would make no difference to their management of the four species. A ban on hunting with dogs would have minimal impact on populations of foxes, red deer and mink, but it may be of conservation benefit to hares.

Applications of Bayesian belief networks in water resource management

Bayesian belief networks (BBNs) are probabilistic graphical models that can capture and integrate both quantitative and qualitative data, thus accommodating data-limited conditions. This paper systematically reviews applications of BBNs with respect to spatial factors, water domains, and the consideration of climate change impacts. The methods used for constructing and validating BBN models, and their applications in different forms of decision-making support are examined. Most reviewed publications originate from developed countries (70%), in temperate climate zones (42%), and focus mainly on water quality (42%). In 60% of the reviewed applications model validation was based on the expert or stakeholder evaluation and sensitivity analysis, and whilst in 27% model performance was not discussed. Most reviewed articles applied BBNs in strategic decision-making contexts (52%). Integrated modelling tools for addressing challenges of dynamically complex systems were also reviewed by analysing the strengths and weaknesses of BBNs, and integration of BBNs with other modelling tools. The application of BBNs to water resource management was rarely applied in developing countries and in tropical regions.Only 8% reviewed papers explored potential impacts of climate change on water resources.Only 11% and 6% of reviewed articles applied influence diagrams and Object-Oriented Bayesian Networks respectively.Most reviewed articles applied BBNs in strategic decision-making contexts (52%) for water resource management.Results from BBN models were rarely compared or tested against other modelling approaches to validate their performance.

Identifying conflicts and opportunities for collaboration in the management of a wildlife resource: a mixed-methods approach

Context The sustainable management of many common-pool ecological resources can be strengthened through collaboration among stakeholder groups. However, the benefits of collaborative management are often not realised because of conflicts of interest among stakeholders. Effective strategies for enhancing collaborative management require an understanding of the trade-offs that managers make between different management outcomes and an understanding of the socioeconomic and location-specific differences that drive these preferences. Approaches based on quantitative or qualitative methods alone often fail to reveal some of the underlying factors inhibiting collaboration. Aims Our aim was to understand the relative importance that private-sector deer managers attach to changes in the following three outcomes of deer management: deer numbers, deer-related road-traffic accidents (RTAs) and deer impacts on conservation woodlands. Methods We used a mixed-methods approach, combining choice-experiment methodology with qualitative analysis of focus-group discussions from 10 study regions throughout Britain. Key results Our results showed that most of the private-sector stakeholders responsible for deer-management decisions at the local level would prefer to see a future with fewer deer-related RTAs but do not want to see a future with lower deer population levels. This is especially the case for those stakeholders managing for sporting purposes and those that rely on deer as a financial resource. Conclusions The preferences of many private-sector stakeholders responsible for deer management are at odds with those of private landowners currently experiencing economic and conservation damage from deer, and with the aims of government and non-government bodies seeking to reduce grazing and browsing damage through lower deer densities. Similar barriers to collaborative management are likely to exist in any situations where ecological resources deliver an unequal distribution of benefits and costs among stakeholders. Implications Overcoming barriers to collaboration requires enhanced understanding of how different collaborative mechanisms are viewed amongst the stakeholder community and how collaborative management can be promoted. More holistic approaches to deer management, which include greater public awareness, additional road-traffic speed restrictions and appropriate fencing, or perhaps include deer-population reduction as only one of a suite of mechanisms for delivering multiple benefits from the land, are likely to gain more support from private-sector stakeholders. Mixed-methods approaches can provide an important first step in terms of both quantifying preferences in relation to the management of ecological resources and enabling detailed insights into the motivations and behaviours underlying them.

Mapping wildlife: integrating stakeholder knowledge with modelled patterns of deer abundance by using participatory GIS

Context. Some species that are perceived by certain stakeholders as a valuable resource can also cause ecological or economic damage, leading to contrasting management objectives and subsequent conflict between stakeholder groups. There is increasing recognition that the integration of stakeholder knowledge with formal scientific data can enhance the information available for use in management. This is especially true where scientific understanding is incomplete, as is frequently the case for wide-ranging species, which can be difficult to monitor directly at the landscape scale. Aims. The aim of the research was to incorporate stakeholder knowledge with data derived from formal quantitative models to modify predictions of wildlife distribution and abundance, using wild deer in the UK as an example. Methods. We use selected predictor variables from a deer–vehicle collision model to estimate deer densities at the 10-km square level throughout the East of England. With these predictions as a baseline, we illustrate the use of participatory GIS as a methodological framework for enabling stakeholder participation in the refinement of landscape-scale deer abundance maps. Key results. Stakeholder participation resulted in modifications to modelled abundance patterns for all wild deer species present in the East of England, although the modifications were minor and there was a high degree of consistency among stakeholders in the adjustments made. For muntjac, roe and fallow deer, the majority of stakeholder changes represented an increase in density, suggesting that populations of these species are increasing in the region. Conclusions. Our results show that participatory GIS is a useful technique for enabling stakeholders to contribute to incomplete scientific knowledge, especially where up-to-date species distribution and abundance data are needed to inform wildlife research and management. Implications. The results of the present study will serve as a valuable information base for future research on deer management in the region. The flexibility of the approach makes it applicable to a range of species at different spatial scales and other wildlife conflict issues. These may include the management of invasive species or the conservation of threatened species, where accurate spatial data and enhanced community involvement are necessary in order to facilitate effective management.

Public preferences for production of local and global ecosystem services

Many regulating ecosystem services exhibit non-excludability and non-rivalry characteristics akin to public goods. This makes it unlikely that such regulating ecosystem services will attract a price in the marketplace. Policymakers, therefore, find difficulties in determining a correct economic valuation for regulating ecosystem services, with potentially severe consequences for aligning policy for ecosystem service provision with public preferences for service delivery. This research used a choice modelling approach to estimate public preferences for delivery of two regulating ecosystem services; reductions in the flood risk to the British city of York (implemented by filling in drainage ditches in peat moorland further up the catchment), and a reduction in CO2 emissions (implemented by planting Poplar trees for biomass either locally in the study area or elsewhere in the UK). The choice experiment presented respondents with options providing different levels of CO2 reduction, implemented locally or nationally, and different levels of flood risk reduction, at a range of different prices, with a tax as the payment vehicle. Subsequent analysis with latent class (LC) models showed considerable heterogeneity of preference among respondents, particularly with regard to the location of tree planting for CO2 reduction. One LC segment showed a significant preference for achieving a high level CO2 reduction through national, as opposed to local tree planting, potentially indicating the existence of NIMBYism. The same LC segment displayed a preference for moderate reductions in the flood risk to York, even though this would deliver no personal benefit for a substantial proportion of the segment. This could, therefore, indicate altruistic behaviour towards geographically proximate beneficiaries.

The impact of changing climate on perennial crops: the case of tea production in Sri Lanka

The plantation crop sector, particularly tea, is a key contributor to the Sri Lankan economy in terms of foreign exchange earnings, employment, and food supply. However, changes in temperature, rainfall, and the occurrence of extreme weather events have adversely affected the sector. Many studies in the literature have focused on climate change impacts on major annual crops; however, to date, comprehensive assessments of the economic impacts of weather variations on perennial crops are rare. In this paper, we use monthly panel data from 40 different tea estates in Sri Lanka over a 15-year period to analyse weather effects on production from the tea plantation sector. Specifically, we use a two-stage panel data approach to explore how tea production in Sri Lanka is affected by both short-term weather variations and long-term climate change. Overall, our findings show that a hotter and wetter climate will have a detrimental effect on Sri Lankan tea production. In high, medium, and low emissions futures, our predictions show a negative proportional impact from increased rainfall and increased average temperature. Under a high emissions scenario, by mid-century, a decline of 12% in annual tea production is predicted. Other climate-susceptible perennial crops such as rubber, coconut, and oil palm play similarly major roles in the economies of other developing countries, suggesting that our approach could usefully be replicated elsewhere.