Energy Projects in Milton Keynes: Energy Consultative Unit Progress Report 1976-1981

The Energy Consultative Unit was a joint Open University/MKDC body set up by Professor Jake Chapman, founder of the OU Energy Research Group. This report describes the work carried out on energy-related projects in Milton Keynes over the period 1976-1981, many of them involving the Open University. After a short explanation of how energy is used in the UK, the report introduces the Energy Consultative Unit projects and summarises the main conclusions drawn from the Unit's work. It then describes the projects on which the Unit has worked and summarises other energy projects under way in the new city. It does not go into the projects in detail, but there are a number of technical reports available for people who want to study them in more depth, and these are listed in the back of the report. The projects represent the work of a considerable number of people and a list of acknowledgements, indicating who should be contacted for further information, is also set out at the back of the report

Linford Low Energy Houses

This is the final report on the performance of 8 low-energy, passive solar houses at Great Linford, Milton Keynes, monitored by the Open University Energy Research Group (ERG), for the Milton Keynes Development Corporation (MKDC), under contract to the Energy Technology Support Unit (ETSU) at Harwell.[The smaller file contains the Executive Summary; the larger file contains the main report, excluding the Executive Summary]

Phylogenetic relationships of African microhylid frogs inferred from DNA sequences of mitochondrial 12S and 16S rRNA genes

The phylogenetic relationships of microhylid frogs are poorly understood. The first molecular phylogeny for continental African microhylids is presented, including representatives of all subfamilies, six of the eight genera, and the enigmatic hemisotid Hemisus. Mitochondrial 12S and 16S rRNA sequence data were analysed using parsimony, likelihood and Bayesian methods. Analyses of the data are consistent with the monophyly of all sampled subfamilies and genera. Hemisus does not nest within either brevicipitines or non-brevicipitines. It is possibly the sister group to brevicipitines, in which case brevicipitines might not be microhylids. Phrynomantis and Hoplophryne potentially group with non-African, non-brevicipitine microhylids, in agreement with recent morphological and molecular data. Within brevicipitines, Breviceps is recovered as the sister group to a clade of Callulina+Spelaeophryne+Probreviceps. The relationships among the genera within this latter clade are unclear, being sensitive to the method of analysis. Optimal trees suggest the Probreviceps macrodactylus subspecies complex might be paraphyletic with respect to P. uluguruensis, corroborating preliminary morphological studies indicating that P. m. rungwensis may be a distinct species. P. m. loveridgei may be paraphyletic with respect to P. m. macrodactylus, though this is not strongly supported. Some biogeographic hypotheses are examined in light of these findings

Development and Reliability of Countermovement Jump Performance in Youth Athletes at Pre-, Circa- and Post-Peak Height Velocity

The purpose of this study was to establish the intrasession reliability of various outcome, propulsion and braking phase countermovement jump (CMJ) variables and to compare the mean differences in youth athletes at different stages of maturity. Thirty male participants, aged 10-16 years, were grouped as either pre-, circa- or post-peak height velocity (PHV) according to their percentage of predicted adult height. All participants performed 3 CMJ trials on a force plate, sampling at 1000 Hz. A one-way ANOVA identified statistically significant differences between maturity groups for all CMJ variables (P<0.05) excluding propulsion peak rate of force development (RFD), braking peak velocity and countermovement depth. Post-hoc analysis revealed that the significant differences in CMJ variables were between the pre- to post- and circa- to post-PHV groups (P <0.05), with moderate to very large effect sizes. Relative and absolute reliability improved with maturity as the post-PHV group demonstrated superior reliability scores (ICC = 0.627-0.984; CV% = 3.25-21.55) compared to circa- (ICC = 0.570-0.998; CV% = 1.82-20.05) and pre-PHV groups (ICC= 0.851-0.988; CV% = 2.16-14.12). In summary, these results suggest that the biggest differences in CMJ performance are observed between preto post- and circa- to post-PHV, and that careful consideration is warranted when selecting variables in youth athletes at pre- and circa-PHV, given the lower reliability scores observed

Targeted vertebrate surveys enhance the faunal importance and improve explanatory models within the Eastern Arc Mountains of Kenya and Tanzania

Detailed knowledge of species distributions, endemism patterns and threats is critical to site prioritization and conservation planning. However, data from biodiversity inventories are still limited, especially for tropical forests, and even well recognized hotspots remain understudied. We provide an example of how updated knowledge on species occurrence from strategically directed biodiversity surveys can change knowledge on perceived biodiversity importance, and facilitate understanding diversity patterns and the delivery of conservation recommendations.Francesco Rovero, Michele Menegon, Jon Fjeldså, Leah Collett, Nike Doggart, Charles Leonard, Guy Norton, Nisha Owen, Andrew Perkin, Daniel Spitale, Antje Ahrends and Neil D. Burges

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the pre-satellite era. Here we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitised historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a five-fold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha(-1) yr(-1) . This is at least three-fold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha(-1) , compared to a committed loss of 11.9 (7.2-16.6) Mg C ha(-1) within areas lacking such protection. Furthermore, for nine protected areas where LULCC data is available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics. This article is protected by copyright. All rights reserved

Correction to: Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

Abstract Upon publication of the original article [1], the authors noticed that the figure labelling for Fig. 4 in the online version was processed wrong. The top left panel should be panel a, with the panels to its right being b and c. d and e should be the panels on the lower row, and f is correct. The graphs themselves are all correct. It is simply the letter labels that are wrong

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Funder: Critical Ecosystem Partnership Fund; Id: http://dx.doi.org/10.13039/100013724Funder: Global Environment Facility; Id: http://dx.doi.org/10.13039/100011150Funder: Danish International Development Agency; Id: http://dx.doi.org/10.13039/501100011054Funder: Scottish Government’s Rural and Environment Science and Analytical Services DivisionFunder: Finnish International Development AgencyFunder: Leverhulme Trust; Id: http://dx.doi.org/10.13039/501100000275Societal Impact Statement: Large areas of tropical forest are degraded. While global tree cover is being mapped with increasing accuracy from space, much less is known about the quality of that tree cover. Here we present a field protocol for rapid assessments of forest condition. Using extensive field data from Tanzania, we show that a focus on remotely‐sensed deforestation would not detect significant reductions in forest quality. Radar‐based remote sensing of degradation had good agreement with the ground data, but the ground surveys provided more insights into the nature and drivers of degradation. We recommend the combined use of rapid field assessments and remote sensing to provide an early warning, and to allow timely and appropriately targeted conservation and policy responses. Summary: Tropical forest degradation is widely recognised as a driver of biodiversity loss and a major source of carbon emissions. However, in contrast to deforestation, more gradual changes from degradation are challenging to detect, quantify and monitor. Here, we present a field protocol for rapid, area‐standardised quantifications of forest condition, which can also be implemented by non‐specialists. Using the example of threatened high‐biodiversity forests in Tanzania, we analyse and predict degradation based on this method. We also compare the field data to optical and radar remote‐sensing datasets, thereby conducting a large‐scale, independent test of the ability of these products to map degradation in East Africa from space. Our field data consist of 551 ‘degradation’ transects collected between 1996 and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and coastal forests. Degradation was widespread, with over one‐third of the study forests—mostly protected areas—having more than 10% of their trees cut. Commonly used optical remote‐sensing maps of complete tree cover loss only detected severe impacts (≥25% of trees cut), that is, a focus on remotely‐sensed deforestation would have significantly underestimated carbon emissions and declines in forest quality. Radar‐based maps detected even low impacts (<5% of trees cut) in ~90% of cases. The field data additionally differentiated types and drivers of harvesting, with spatial patterns suggesting that logging and charcoal production were mainly driven by demand from major cities. Rapid degradation surveys and radar remote sensing can provide an early warning and guide appropriate conservation and policy responses. This is particularly important in areas where forest degradation is more widespread than deforestation, such as in eastern and southern Africa

Detecting and predicting forest degradation: A comparison of ground surveys and remote sensing in Tanzanian forests

Summary • Tropical forest degradation is widely recognised as a driver of biodiversity loss and a major source of carbon emissions. However, in contrast to deforestation, the more gradual changes from degradation are challenging to detect, quantify, and monitor. Here we present a field protocol for rapid, area-standardised quantifications of forest condition, which can also be done by non-specialists. Using the example of threatened high-biodiversity forests in Tanzania, we analyse and predict degradation based on this method. We also compare the field data to optical and radar remote sensing datasets, thereby conducting a large-scale, independent test of the ability of these products to map degradation in East Africa from space. • Our field data consist of 551 ‘degradation’ transects collected between 1996 and 2010, covering >600 ha across 86 forests in the Eastern Arc Mountains and coastal forests. • Degradation was widespread, with over one third of the study forests – mostly protected areas – having more than 10% of their trees cut. Commonly-used optical remote-sensing maps of complete tree cover loss only detected severe impacts (≥25% of trees cut), i.e. a focus on remotely sensed deforestation would have significantly underestimated carbon emissions and declines in forest quality. Radar-based maps detected even low impacts (<5% of trees cut) in ~90% of cases. The field data additionally allowed to differentiate different types and drivers of harvesting, with spatial patterns suggesting that logging and charcoal production were mainly driven by demand from major cities. • Rapid degradation surveys and radar remote sensing can provide an early warning and guide appropriate conservation and policy responses. This is particularly important in areas where forest degradation is more widespread than deforestation, such as in east and southern Africa