Assessing processes of long-term land cover change and modelling their effects on tropical forest biodiversity patterns – a remote sensing and GIS-based approach for three landscapes in East Africa: Assessing processes of long-term land cover change and modelling their effects on tropical forest biodiversity patterns – a remote sensing and GIS-based approach for three landscapes in East Africa

The work describes the processing and analysis of remote sensing time series data for a comparative assessment of changes in different tropical rainforest areas in East Africa. In order to assess the effects of the derived changes in land cover and forest fragmentation, the study made use of spatially explicit modelling approaches within a geographical information system (GIS) to extrapolate sets of biological field findings in space and time. The analysis and modelling results were visualised aiming to consider the requirements of three different user groups. In order to evaluate measures of forest conservation and to derive recommendations for an effective forest management, quantitative landscape-scale assessments of land cover changes and their influence on forest biodiversity patterns are needed. However, few remote sensing studies have accounted for all of the following aspects at the same time: (i) a dense temporal sequence of land cover change/forest fragmentation information, (ii) the coverage of several decades, (iii) the distinction between multiple forest formations and (iv) direct comparisons of different case studies. In regards to linkages of remote sensing with biological field data, no attempts are known that use time series data for quantitative statements of long-term landscape-scale biodiversity changes. The work studies three officially protected forest areas in Eastern Africa: the Kakamega-Nandi forests in western Kenya (focus area) and Mabira Forest in south-eastern Uganda as well as Budongo Forest in western Uganda (for comparison purposes). Landsat imagery of in total eight or seven dates in regular intervals from 1972/73 to 2003 was used. Making use of supervised multispectral image classification procedures, in total, 12 land cover classes (six forest formations) were distinguished for the Kakamega-Nandi forests and for Budongo Forest while for Mabira Forest ten classes could be realised. An accuracy assessment via error matrices revealed overall classification accuracies between 81% and 85%. The Kakamega-Nandi forests show a continuous decrease between 1972/73 and 2001 of 31%, Mabira Forest experienced an abrupt loss of 24% in the late 1970s/early 1980s, while Budongo Forest shows a relatively stable forest cover extent. An assessment of the spatial patterns of forest losses revealed congruence with areas of high population density while a spatially explicit forest fragmentation index indicates a strong correlation of forest fragmentation with forest management regime and forest accessibility by roads. For the Kenyan focus area, three sets of biological field abundance data on keystone species/groups were used for a quantitative assessment of the influence of long-term changes in tropical forests on landscape-scale biodiversity patterns. For this purpose, the time series was extended with another three land cover data sets derived from aerial photography (1965/67, 1948/(52)) and old topographic maps (1912/13). To predict the spatio-temporal distribution of the army ant Dorylus wilverthi and of ant-following birds, GIS operators (i.e. focal and local functions) and statistical tests (i.e. OLS or SAR regression models) were combined into a spatial modelling procedure. Abundance data on three guilds of birds differing in forest dependency were directly extrapolated to five forest cover classes as distinguished in the time series. The results predict declines in species abundances of 56% for D. wilverthi, of 58% for ant-following birds and an overall loss of 47% for the bird habitat guilds, which in all three cases greatly exceed the rate of forest loss (31%). Additional extrapolations on scenarios of deforestation and reforestation confirmed the negative ecological consequences of splitting-up contiguous forest areas but also showed the potential of mixed indigenous forest plantings. The visualisation of the analysis and modelling results produced a mixture of different outcomes. Map series and a matrix of maps both showing species distributions aim to address scientists and decision makers. The results of the land cover change analysis were synthesised in a map of land cover development types for each study area, respectively. These maps are designed mainly for scientists. Additional maps of change, limited to a single class of forest cover and to three dates were generated to ensure an easy-to-grasp communication of the major forest changes to decision makers. Additionally, an easy-to-handle visualisation tool to be used by scientists, decision makers and local people was developed. For the future, an extension of this study towards a more complete assessment including more species/groups and also ecosystem functions and services would be desirable. Combining a framework for land cover simulation with a framework for running empirical extrapolation models in an automated manner could ideally result in a GIS-based, integrated forest ecosystem assessment tool to be used as regional spatial decision support system.Die Arbeit beschreibt die Prozessierung und Analyse von Fernerkundungs-Zeitreihendaten für eine vergleichende Abschätzung von Veränderungen verschiedener tropischer Waldökosysteme Ostafrikas. Um Effekte der Veränderungen bzgl. Landbedeckung und Waldfragmentierung auf Biodiversitätsmuster abzuschätzen, wurden verschiedene räumlich explizite Modellierungssätze innerhalb eines geographischen Informationssystems (GIS) zur räumlichen und zeitlichen Extrapolation biologischer Felderhebungsdaten benutzt. Die Visualisierung der Analyse- und Modellierungsergebnisse erfolgte unter Berücksichtigung der Bedürfnisse von drei verschiedenen Nutzergruppen. Um Waldschutzmaßnahmen zu evaluieren und Empfehlungen für ein effektives Waldmanagement abzuleiten, sind quantitative Abschätzungen von Landbedeckungsveränderungen sowie von deren Einfluss auf tropische Waldbiodiversitätsmuster nötig. Wenige fernerkundungsbasierte Studien haben jedoch bislang alle der folgenden Faktoren berücksichtigt: (i) Informationen zu Veränderungen von Landbedeckung und Waldfragmentierung in dichter zeitlicher Sequenz, (ii) die Abdeckung mehrerer Jahrzehnte, (iii) die Unterscheidung zwischen mehreren Waldformationen, und (iv) direkte Vergleiche von unterschiedlichen Fallstudien. Hinsichtlich Verknüpfungen von Fernerkundung mit biologischen Felddaten sind bisher keine Studien bekannt, die Zeitreihendaten für quantitative Aussagen zu Langzeitveränderungen von Biodiversität auf Landschaftsebene verwenden. Die Arbeit untersucht drei offiziell geschützte Gebiete: die Kakamega-Nandi forests in Westkenia (Hauptuntersuchungsgebiet) sowie Mabira Forest in Südost-Uganda und Budongo Forest in West-Uganda (zu Vergleichszwecken). Es wurden Landsat-Daten für insgesamt acht bzw. sieben Zeitpunkte zwischen 1972/73 und 2003 in ungefähr gleichen Abständen erworben. Mit Hilfe von überwachten, multispektralen Klassifizierungsverfahren wurden für die Kakamega-Nandi forests und Budongo Forest jeweils 12 Landbedeckungsklassen (sechs Waldformationen) und für Mabira Forest zehn Klassen unterschieden. Eine Genauigkeitsprüfung mit Hilfe von Fehlermatrizen ergab Gesamtklassifizierungsgenauigkeiten zwischen 81% und 85%. Die Kakamega-Nandi forests sind durch eine kontinuierliche Waldabnahme von 31% zwischen 1972/73 und 2001 gekennzeichnet, Mabira Forest zeigt einen abrupten Waldverlust von 24% in den späten 1970ern/frühen 1980ern, während die Ergebnisse für Budongo Forest eine relativ stabile Waldbedeckung ausweisen. Während eine Abschätzung der räumlichen Muster von Waldverlusten eine hohe Deckungsgleichheit mit Gebieten hoher Bevölkerungsdichte ergab, deutet die Anwendung eines räumlich expliziten Waldfragmentierungsindexes auf eine starke Korrelation von Waldfragmentierung mit der Art von Waldmanagement sowie mit der Erreichbarkeit von Wald über Straßen hin. Um den Einfluss von Langzeit-Landbedeckungsveränderungen auf Biodiversitätsmuster auf Landschaftsebene für das kenianische Hauptuntersuchungsgebiet quantitativ abzuschätzen wurden drei Datensätze mit biologischen Felderhebungen zur Abundanz von Schlüsselarten/-gruppen verwendet. Zu diesem Zweck wurde die Zeitreihe zunächst um drei weitere Landbedeckungs-Datensätze ergänzt, die aus Luftbildern (1965/67, 1948/(52)) bzw. alten topographischen Karten (1912/13) gewonnen wurden. Zur Vorhersage der raum-zeitlichen Verteilung der Treiberameise Dorylus wilverthi wurden GIS-Operatoren und statistische Tests (OLS bzw. SAR Regressionsmodelle) in einem räumlichen Modellierungsablauf kombiniert. Abundanzdaten von drei sich hinsichtlich ihrer Abhängigkeit von Wald unterscheidenden Vogelgilden wurden direkt auf fünf Waldbedeckungsklassen hochgerechnet, die in der Zeitreihe unterschieden werden konnten. Die Ergebnisse prognostizieren Abundanzabnahmen von 56% für D. wilverthi, von 58% für Ameisen-folgende Vögel und einen Gesamtverlust von 47% für die Vogelgilden, was in allen drei Fällen eine deutliche Überschreitung der Waldverlustrate von 31% darstellt. Zusätzliche Extrapolationen basierend auf Szenarien bestätigten die negativen ökologischen Konsequenzen der Zerteilung zusammenhängender Waldflächen bzw. zeigten andererseits das Potential von Aufforstungen mit einheimischen Arten auf. Die Visualisierung der Analyse- bzw. Modellierungsergebnisse führte zu unterschiedlichen Darstellungen: mit einer Reihe von nebeneinander positionierten Einzelkarten sowie einer Matrix von Einzelkarten, die jeweils Artenverteilungen zeigen, sollen Wissenschaftler und Entscheidungsträger angesprochen werden. Aus den Ergebnissen der Landbedeckungsanalyse für die drei Untersuchungsgebiete wurden Landbedeckungsveränderungstypen generiert und jeweils in einer synthetischen Karte dargestellt, die hauptsächlich für Wissenschaftler gedacht sind. Um die wesentlichen Waldveränderungen auch auf einfache Weise zu den Entscheidungsträgern zu kommunizieren, wurden zusätzliche Karten erstellt, die nur eine aggregierte Klasse „Waldbedeckung“ zeigen und jeweils auf drei Zeitschritte der Zeitreihen begrenzt sind. Zusätzlich wurde ein leicht zu bedienendes Visualisierungstool entwickelt, das für Wissenschaftler, Entscheidungsträger und die lokale Bevölkerung gedacht ist. Für die Zukunft wäre eine umfassendere Abschätzung unter Berücksichtigung zusätzlicher Arten/-gruppen sowie auch Ökosystemfunktionen und –dienstleistungen wünschenswert. Die Verknüpfung einer Applikation zur Landbedeckungsmodellierung mit einer Applikation zur Ausführung von empirischen Extrapolationsmodellen (in stärkerem Maße automatisiert als in dieser Arbeit) könnte im Idealfall in ein GIS-basiertes Tool zur integrativen Bewertung von Waldökosystemen münden, das dann als räumliches Entscheidungsunterstützungssystem verwendet werden könnte

Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest

Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants

A Measurement of the Electric Form Factor of the Neutron through d⃗(e⃗,e′n)p\vec{d}(\vec{e},e'n)p at Q2=0.5Q^2 = 0.5 (GeV/c)2^2

We report the first measurement of the neutron electric form factor $G_E^n$ via $\vec{d}(\vec{e},e'n)p$ using a solid polarized target. $G_E^n$ was determined from the beam-target asymmetry in the scattering of longitudinally polarized electrons from polarized deuterated ammonia, $^{15}$ND$_3$. The measurement was performed in Hall C at Thomas Jefferson National Accelerator Facility (TJNAF) in quasi free kinematics with the target polarization perpendicular to the momentum transfer. The electrons were detected in a magnetic spectrometer in coincidence with neutrons in a large solid angle segmented detector. We find $G_E^n = 0.04632\pm0.00616 (stat.) \pm0.00341 (syst.)$ at $Q^2 = 0.495$ (GeV/c)$^2$.Comment: Latex2e 5 pages, 3 figure

Knowledge Architecture for the wise governance of Sustainability Transitions

The need for sustainability transitions is widely recognised, along with a concurrent need for the evolution of knowledge systems to inform more effective policy action. Although there are many new policy targets relating to net zero emissions and other sustainability challenges, cities, regional and national governments are struggling to rapidly develop transformational policies to achieve them. As academics and practitioners who work at the science-policy interface, we identify specific knowledge and competency needs for governing sustainability transitions related to the interlinked phases of envisioning, implementing and evaluating. In short, coordinated reforms of both policy and knowledge systems are urgently needed to address the speed and scale of sustainability challenges. These include embedding systems thinking literacy, mainstreaming participatory policy making, expanding the capacity to undertake transdisciplinary research, more adaptive governance and continuous organisational learning. These processes must guide further knowledge development, uptake and use as part of an iterative and holistic process. Such deep-seated change in policy-knowledge systems will be disruptive and presents challenges for traditional organisational models of knowledge delivery, but is essential for successful sustainability transformatio

Meta-Analysis of Genomewide Association Studies Reveals Genetic Variants for Hip Bone Geometry

Hip geometry is an important predictor of fracture. We performed a meta-analysis of GWAS studies in adults to identify genetic variants that are associated with proximal femur geometry phenotypes. We analyzed four phenotypes: (i) femoral neck length; (ii) neck-shaft angle; (iii) femoral neck width, and (iv) femoral neck section modulus, estimated from DXA scans using algorithms of hip structure analysis. In the Discovery stage, 10 cohort studies were included in the fixed-effect meta-analysis, with up to 18,719 men and women ages 16 to 93 years. Association analyses were performed with ∼2.5 million polymorphisms under an additive model adjusted for age, body mass index, and height. Replication analyses of meta-GWAS significant loci (at adjusted genomewide significance [GWS], threshold p ≤ 2.6 × 10 –8 ) were performed in seven additional cohorts in silico. We looked up SNPs associated in our analysis, for association with height, bone mineral density (BMD), and fracture. In meta-analysis (combined Discovery and Replication stages), GWS associations were found at 5p15 (IRX1 and ADAMTS16); 5q35 near FGFR4; at 12p11 (in CCDC91); 11q13 (near LRP5 and PPP6R3 (rs7102273)). Several hip geometry signals overlapped with BMD, including LRP5 (chr. 11). Chr. 11 SNP rs7102273 was associated with any-type fracture (p = 7.5 × 10 –5 ). We used bone transcriptome data and discovered several significant eQTLs, including rs7102273 and PPP6R3 expression (p = 0.0007), and rs6556301 (intergenic, chr.5 near FGFR4) and PDLIM7 expression (p = 0.005). In conclusion, we found associations between several genes and hip geometry measures that explained 12% to 22% of heritability at different sites. The results provide a defined set of genes related to biological pathways relevant to BMD and etiology of bone fragility

Climate change and the emergence of vector-borne diseases in Europe: Case study of dengue fever

Background: Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios. Methods. We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence. Results: The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy. Conclusions: This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world

Common variants near MC4R are associated with fat mass, weight and risk of obesity.

To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 x 10(-6)) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 x 10(-15)) and 5,988 children aged 7-11 (0.13 Z-score units; P = 1.5 x 10(-8)). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 x 10(-11)). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 x 10(-4)). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits