Niches for Species, a multi-species model to guide woodland management: An example based on Scotland's native woodlands

Designating and managing areas with the aim of protecting biodiversity requires information on species distributions and habitat associations, but a lack of reliable occurrence records for rare and threatened species precludes robust empirical modelling. Managers of Scotland’s native woodlands are obliged to consider 208 protected species, which each have their own, narrow niche requirements. To support decision-making, we developed Niches for Species (N4S), a model that uses expert knowledge to predict the potential occurrence of 179 woodland protected species representing a range of taxa: mammals, birds, invertebrates, fungi, bryophytes, lichens and vascular plants. Few existing knowledge-based models have attempted to include so many species. We collated knowledge to define each species’ suitable habitat according to a hierarchical habitat classification: woodland type, stand structure and microhabitat. Various spatial environmental datasets were used singly or in combination to classify and map Scotland’s native woodlands accordingly, thus allowing predictive mapping of each species’ potential niche. We illustrate how the outputs can inform individual species management, or can be summarised across species and regions to provide an indicator of woodland biodiversity potential for landscape scale decisions. We tested the model for ten species using available occurrence records. Although concordance between predicted and observed distributions was indicated for nine of these species, this relationship was statistically significant in only five cases. We discuss the difficulties in reliably testing predictions when the records available for rare species are typically low in number, patchy and biased, and suggest future model improvements. Finally, we demonstrate how using N4S to synthesise complex, multi-species information into an easily digestible format can help policy makers and practitioners consider large numbers of species and their conservation needs

Management of ash/impurity ratio in sugarcane: Relative effects of genotypes, and N and K fertiliser rates

In sugarcane juice or raw sugar, ash refers to soluble inorganic salts. The ratio of ash/impurity is important because high levels reduce sucrose extraction in sugar mills and the market value of raw sugar. The aim of research reported here was to examine, through a series of field experiments, the effects of genotypes and varying N and K fertiliser application rates on ash and ash/impurity levels. Ash levels were estimated via conductivity measurements, following prior studies indicating close relationships between conductivity and ash. Significant variation due to genotypes for conductivity/impurity levels was observed, with a range of about ±25% around the mean. Despite this variation, broad-sense heritability of conductivity/impurity levels on unselected genotypes on the basis of measurements in one environment were low (0.20), suggesting that selection in early phases of selection systems in breeding programs would probably be of limited value. However, it was recommended that measurements on conductivity/impurity ratio be made in multi-environment trials for genotypes being tested for commercial release, to assist in comprehensive economic evaluation. On average it was found that conductivity/impurity levels increased by 15% per 100 kg/ha of applied K, highlighting potential costs of high rates of K fertiliser. Increased N rates had a significant but small effect on reducing conductivity/impurity levels by ∼10% per additional 100 kg/ha of applied N. The information reported here may be used to help develop optimal strategies for cultivar selection in sugarcane breeding programs and for developing recommendations for optimal fertiliser management, and some guidelines in relation to this are discussed

Bellamyetal_GREENSURGE_Malmo_urbanES_poster_2017_final.pdf

This poster is being presented at the GREEN SURGE conference in Malmo, 19 - 22 September 2017. <div><br></div><div>Green infrastructure, such as trees, parks and waterways can help regulate urban hazards such as water surface run-off, improve the aesthetic and economic value of an area and provide opportunities to interact with nature. To ensure that they deliver these benefits in the places where they are most needed, local authorities, city planners and developers need an evidence base to target green infrastructure resources and effort. We developed SPADES™ (SPatial Decisions on Ecosystem Services), a tool which includes a flexible framework for mapping cultural ecosystem services under existing conditions and alternative scenarios. By explicitly partitioning our predictors we were able to explore their relative weight in driving service ‘use’: is a site valuable because of its green infrastructure, or because it is in a busy, accessible area (or both)? We found levels of demand had the biggest impact, but features such as tree canopy cover were also important.<br></div

Focus 2014

A magazine for alumnae, alumni and friends of the Boston University School of Theology community

Selection for water-soluble carbohydrate accumulation and investigation of genetic x environment interactions in an elite wheat breeding population

Water-soluble carbohydrate accumulation can be selected in wheat breeding programs with consideration of genetic x environmental interactions and relationships with other important characteristics such as relative maturity and nitrogen concentration, although the correlation between WSC traits and grain yield is low and inconsistent