Leveraging big satellite image and animal tracking data for characterizing large mammal habitats

Die zunehmende Verfügbarkeit von Satellitenfernerkundungs- und Wildtier-Telemetriedaten eröffnet neue Möglichkeiten für eine verbesserte Überwachung von Wildtierhabitaten durch Habitatmodelle, doch fehlt es häufig an geeigneten Ansätzen, um dieses Potenzial voll auszuschöpfen. Das übergeordnete Ziel dieser Arbeit bestand in der Konzipierung und Weiterentwicklung von Ansätzen zur Nutzung des Potenzials großer Satellitenbild- und Telemetriedatensätze in Habitatmodellen. Am Beispiel von drei großen Säugetierarten in Europa (Eurasischer Luchs, Rothirsch und Reh) wurden Ansätze entwickelt, um (1) Habitatmodelle mit dem umfangreichsten global und frei verfügbaren Satellitenbildarchiv der Landsat-Satelliten zu verknüpfen und (2) Wildtier-Telemetriedaten über Wildtierpopulationen hinweg in großflächigen Analysen der Habitateignung und -nutzung zu integrieren. Die Ergebnisse dieser Arbeit belegen das enorme Potenzial von Landsat-basierten Variablen als Prädiktoren in Habitatmodellen, die es ermöglichen von statischen Habitatbeschreibungen zu einem kontinuierlichen Monitoring von Habitatdynamiken über Raum und Zeit überzugehen. Die Ergebnisse meiner Forschung zeigen darüber hinaus, wie wichtig es ist, die Kontextabhängigkeit der Lebensraumnutzung von Wildtieren in Habitatmodellen zu berücksichtigen, insbesondere auch bei der Integration von Telemetriedatensätzen über Wildtierpopulationen hinweg. Die Ergebnisse dieser Dissertation liefern neue ökologische Erkenntnisse, welche zum Management und Schutz großer Säugetiere beitragen können. Darüber hinaus zeigt meine Forschung, dass eine bessere Integration von Satellitenbild- und Telemetriedaten eine neue Generation von Habitatmodellen möglich macht, welche genauere Analysen und ein besseres Verständnis von Lebensraumdynamiken erlaubt und so Bemühungen zum Schutz von Wildtieren unterstützen kann.The growing availability of satellite remote sensing and animal tracking data opens new opportunities for an improved monitoring of wildlife habitats based on habitat models, yet suitable approaches for making full use of this potential are commonly lacking. The overarching goal of this thesis was to develop and advance approaches for harnessing the potential of big satellite image and animal tracking data in habitat models. Specifically, using three large mammal species in Europe as an example (Eurasian lynx, red deer, and roe deer), I developed approaches for (1) linking habitat models to the largest global and freely available satellite image record, the Landsat image archive, and (2) for integrating animal tracking datasets across wildlife populations in large-area assessments of habitat suitability and use. The results of this thesis demonstrate the enormous potential of Landsat-based variables as predictors in habitat models, allowing to move from static habitat descriptions to a continuous monitoring of habitat dynamics across space and time. In addition, my research underscores the importance of considering context-dependence in species’ habitat use in habitat models, particularly also when integrating tracking datasets across wildlife populations. The findings of this thesis provide novel ecological insights that help to inform the management and conservation of large mammals and more broadly, demonstrate that a better integration of satellite image and animal tracking data will allow for a new generation of habitat models improving our ability to monitor and understand habitat dynamics, thus supporting efforts to restore and protect wildlife across the globe

Resource pulses and human–wildlife conflicts

Pulsed resources have prominent effects on community and ecosystem dynamics; however, there is little research on how resource pulses affect human–wildlife interactions. Tree masting is a common type of pulsed resource that represents a crucial food for many species and has important bottom-up effects in food webs. In anthropogenic landscapes, years of food shortage after mast years can have negative outcomes for both people and wildlife, for instance when an increased use of anthropogenic foods by animals exacerbates human–wildlife conflicts. Here, we used novel remote sensing indicators of forest productivity and phenology, together with weather cues and ground measures of mast production, to assess whether years of masting and crop failures lead to changes in human–wildlife conflict occurrence. We used a unique 14-year dataset including the production of European beech Fagus sylvatica seeds and brown bear Ursus arctos damage in the northeastern Carpathians as our model system. Linking these data in a panel regression framework, we found that temporal fluctuations in damage occurrence were sensitive to the year-to-year variation in beechnut production. Specifically, the number of damages during bear hyperphagia (i.e., September to December, when bears need to accumulate fat reserves prior to hibernation) was significantly higher in years with low beechnut production than in normal or mast years. Furthermore, we provide evidence that beech masting and failure can be predicted through a combination of remote-sensing, weather, and field indicators of forest productivity and phenology. We demonstrate how pulsed resources, such as tree masting, can percolate through food webs to amplify human–wildlife conflict in human-dominated landscapes. Given the recent range expansion of large carnivores and herbivores in many regions, including Europe, predicting years of natural food shortage can provide a pathway to proactive damage prevention, and thus to foster coexistence between wildlife and people.Peer Reviewe

Humans rather than Eurasian lynx (Lynx lynx) shape ungulate browsing patterns in a temperate forest

The recolonization of human-dominated landscapes by large carnivores has been followed with considerable scientific interest; however, little is known about their interactive effect on ungulate foraging behavior. This study compared the risks imposed by humans and lynx on ungulate foraging behavior by examining the effects of browsing intensity (at two spatial scales), diet quality, and tree species selection. We hypothesized that: (1) in areas with high risk imposed by humans and lynx browsing intensity would be reduced; (2) risk effects would interact with habitat visibility at a fine scale, resulting in contrasting browsing patterns in response to humans versus lynx risk; (3) ungulates compensate for the higher costs incurred in high-risk areas by switching to a higher diet quality, and (4) browse a higher proportion of more-preferred tree species. These hypotheses were tested by measuring browsing intensity along 48 transects located at different distances from human settlements within the hunted and nonhunted areas of the Bavarian Forest. Dung samples were collected and analyzed as a proxy of diet quality (C:N ratio, fiber). The spatial patterns of browsing intensity, diet quality, and tree species selection were then linked to lynx risk, hunting intensity, recreation intensity, and distance to human settlements. Our results showed that (1) browsing intensity strongly decreased with increasing recreational activities, whereas it increased with lynx risk; (2) only in close proximity to human settlements tree browsing was higher in dense habitats and (3) a higher diet quality was obtained. (4) We found a stronger avoidance of the less preferred tree species in high-hunting intensity areas. In conclusion, our results indicate that the risk effects of human activities outweigh those of a natural large carnivore. Thus, highlighting the importance of taking those activities into account in predicting the impacts of large carnivores on ungulates and their plant-food choices.publishedVersio

Frontier metrics for a process-based understanding of deforestation dynamics

Agricultural expansion into tropical and subtropical forests often leads to major social-ecological trade-offs. Yet, despite ever-more detailed information on where deforestation occurs, how agriculture expands into forests remains unclear, which is hampered by a lack of spatially and temporally detailed reconstruction of agricultural expansion. Here, we developed and mapped a novel set of metrics that quantify agricultural frontier processes at unprecedented spatial and temporal detail. Specifically, we first derived consistent annual time series of land-use/cover to, second, describe archetypical patterns of frontier expansion, pertaining to the speed, the diffusion and activity of deforestation, as well as post-deforestation land use. We exemplify this approach for understanding agricultural frontier expansion across the entire South American Chaco (1.1 million km2), a global deforestation hotspot. Our study provides three major insights. First, agricultural expansion has been rampant in the Chaco, with more than 19.3 million ha of woodlands converted between 1985 and 2020, including a surge in deforestation after 2019. Second, land-use trajectories connected to frontier processes have changed in major ways over the 35 year study period we studied, including substantial regional variations. For instance, while ranching expansion drove most of the deforestation in the 1980s and 1990s, cropland expansion dominated during the mid-2000s in Argentina, but not in Paraguay. Similarly, 40% of all areas deforested were initially used for ranching, but later on converted to cropping. Accounting for post-deforestation land-use change is thus needed to properly attribute deforestation and associated environmental impacts, such as carbon emissions or biodiversity loss, to commodities. Finally, we identified major, recurrent frontier types that may be a useful spatial template for land governance to match policies to specific frontier situations. Collectively, our study reveals the diversity of frontier processes and how frontier metrics can capture and structure this diversity to uncover major patterns of human–nature interactions, which can be used to guide spatially-targeted policies.H2020 European Research Councilhttp://dx.doi.org/10.13039/100010663Belgian Federal Science Policy Officehttp://dx.doi.org/10.13039/501100002749Bundesministerium für Bildung und Forschunghttp://dx.doi.org/10.13039/501100002347Deutsche Forschungsgemeinschafthttp://dx.doi.org/10.13039/501100001659Peer Reviewe

Spatial variation in red deer density in a transboundary forest ecosystem

Forests in Europe are exposed to increasingly frequent and severe disturbances. The resulting changes in the structure and composition of forests can have profound consequences for the wildlife inhabiting them. Moreover, wildlife populations in Europe are often subjected to differential management regimes as they regularly extend across multiple national and administrative borders. The red deer Cervus elaphus population in the Bohemian Forest Ecosystem, straddling the Czech-German border, has experienced forest disturbances, primarily caused by windfalls and bark beetle Ips typographus outbreaks during the past decades. To adapt local management strategies to the changing environmental conditions and to coordinate them across the international border, reliable estimates of red deer density and abundance are highly sought-after by policymakers, wildlife managers, and stakeholders. Covering a 1081-km2 study area, we conducted a transnational non-invasive DNA sampling study in 2018 that yielded 1578 genotyped DNA samples from 1120 individual red deer. Using spatial capture-recapture models, we estimated total and jurisdiction-specific abundance of red deer throughout the ecosystem and quantified the role of forest disturbance and differential management strategies in shaping spatial heterogeneity in red deer density. We hypothesised that (a) forest disturbances provide favourable habitat conditions (e.g., forage and cover), and (b) contrasting red deer management regimes in different jurisdictions create a differential risk landscape, ultimately shaping density distributions. Overall, we estimated that 2851 red deer (95% Credible Interval = 2609–3119) resided in the study area during the sampling period, with a relatively even overall sex ratio (1406 females, 95% CI = 1229–1612 and 1445 males, 95% CI = 1288–1626). The average red deer density was higher in Czechia (3.5 km−2, 95% CI = 1.2–12.3) compared to Germany (2 km−2, 95% CI = 0.2–11). The effect of forest disturbances on red deer density was context-dependent. Forest disturbances had a positive effect on red deer density at higher elevations and a negative effect at lower elevations, which could be explained by partial migration and its drivers in this population. Density of red deer was generally higher in management units where hunting is prohibited. In addition, we found that sex ratios differed between administrative units and were more balanced in the non-intervention zones. Our results show that the effect of forest disturbances on wild ungulates is modulated by additional factors, such as elevation and ungulate management practices. Overall density patterns and sex ratios suggested strong gradients in density between administrative units. With climate change increasing the severity and frequency of forest disturbances, population-level monitoring and management are becoming increasingly important, especially for wide-ranging species as both wildlife and global change transcend administrative boundaries.publishedVersio

Prerequisites for coexistence: human pressure and refuge habitat availability shape continental‑scale habitat use patterns of a large carnivore

Context Adjustments in habitat use by large carnivores can be a key factor facilitating their coexistence with people in shared landscapes. Landscape composition might be a key factor determining how large carnivores can adapt to occurring alongside humans, yet broad-scale analyses investigating adjustments of habitat use across large gradients of human pressure and landscape composition are lacking. Objectives Here, we investigate adjustments in habitat use by Eurasian lynx (Lynx lynx) in response to varying availability of refuge habitats (i.e., forests and rugged terrain) and human landscape modifcation. Methods Using a large tracking dataset including 434 individuals from seven populations, we assess functional responses in lynx habitat use across two spatial scales, testing for variation by sex, daytime, and season. Results We found that lynx use refuge habitats more intensively with increasing landscape modifcation across spatial scales, selecting forests most strongly in otherwise open landscapes and rugged terrain in mountainous regions. Moreover, higher forest availability enabled lynx to place their home ranges in more human-modifed landscapes. Human pressure and refuge habitat availability also shaped temporal patterns of lynx habitat use, with lynx increasing refuge habitat use and reducing their use of human-modifed areas during periods of high exposure (daytime) or high vulnerability (postnatal period) to human pressure. Conclusions Our fndings suggest a remarkable adaptive capacity of lynx towards human pressure and underline the importance of refuge habitats across scales for enabling coexistence between large carnivores and people. More broadly, we highlight that the composition of landscapes determines how large carnivores can adapt to human pressure and thus play an important role shaping large carnivore habitat use and distributions.publishedVersio

Integrating animal tracking datasets at a continental scale for mapping Eurasian lynx habitat

Aim: The increasing availability of animal tracking datasets collected across many sites provides new opportunities to move beyond local assessments to enable de-tailed and consistent habitat mapping at biogeographical scales. However, integrating wildlife datasets across large areas and study sites is challenging, as species' varying responses to different environmental contexts must be reconciled. Here, we compare approaches for large-area habitat mapping and assess available habitat for a recolo-nizing large carnivore, the Eurasian lynx (Lynx lynx).Location: Europe.Methods: We use a continental-scale animal tracking database (450 individuals from 14 study sites) to systematically assess modelling approaches, comparing (1) global strategies that pool all data for training versus building local, site-specific models and combining them, (2) different approaches for incorporating regional variation in habi-tat selection and (3) different modelling algorithms, testing nonlinear mixed effects models as well as machine-learning algorithms.Results: Testing models on training sites and simulating model transfers, global and local modelling strategies achieved overall similar predictive performance. Model performance was the highest using flexible machine-learning algorithms and when incorporating variation in habitat selection as a function of environmental variation. Our best-performing model used a weighted combination of local, site-specific habi-tat models. Our habitat maps identified large areas of suitable, but currently unoccu-pied lynx habitat, with many of the most suitable unoccupied areas located in regions that could foster connectivity between currently isolated populations.Main Conclusions: We demonstrate that global and local modelling strategies can achieve robust habitat models at the continental scale and that considering regional variation in habitat selection improves broad-scale habitat mapping. More generally, we highlight the promise of large wildlife tracking databases for large-area habitat mapping. Our maps provide the first high-resolution, yet continental assessment of lynx habitat across Europe, providing a consistent basis for conservation planning for restoring the species within its former range.publishedVersio

Common non-synonymous SNPs associated with breast cancer susceptibility: findings from the Breast Cancer Association Consortium.

Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community’s Seventh Framework Programme under grant agreement n8 223175 (HEALTH-F2–2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program and the Ministry of Economic Development, Innovation and Export Trade of Quebec (PSR-SIIRI-701). Additional support for the iCOGS infrastructure was provided by the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The ABCFS and OFBCR work was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products or organizations imply endorsement t by the US Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow and M.C.S. is a NHMRC Senior Research Fellow. The OFBCR work was also supported by the Canadian Institutes of Health Research ‘CIHR Team in Familial Risks of Breast Cancer’ program. The ABCS was funded by the Dutch Cancer Society Grant no. NKI2007-3839 and NKI2009-4363. The ACP study is funded by the Breast Cancer Research Trust, UK. The work of the BBCC was partly funded by ELAN-Programme of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breakthrough Breast Cancer and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). E.S. is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, UK. Core funding to the Wellcome Trust Centre for Human Genetics was provided by the Wellcome Trust (090532/Z/09/Z). I.T. is supported by the Oxford Biomedical Research Centre. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CECILE study was funded by the Fondation de France, the French National Institute of Cancer (INCa), The National League against Cancer, the National Agency for Environmental l and Occupational Health and Food Safety (ANSES), the National Agency for Research (ANR), and the Association for Research against Cancer (ARC). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital.The CNIO-BCS was supported by the Genome Spain Foundation the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit, CNIO is supported by the Instituto de Salud Carlos III. D.A. was supported by a Fellowship from the Michael Manzella Foundation (MMF) and was a participant in the CNIO Summer Training Program. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398). Collection of cancer incidence e data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. HAC receives support from the Lon V Smith Foundation (LVS39420). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), as well as the Department of Internal Medicine , Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus Bonn, Germany. The HEBCS was supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (132473), the Finnish Cancer Society, The Nordic Cancer Union and the Sigrid Juselius Foundation. The HERPACC was supported by a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by a research grant from Takeda Science Foundation , by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan and by National Cancer Center Research and Development Fund. The HMBCS was supported by short-term fellowships from the German Academic Exchange Program (to N.B), and the Friends of Hannover Medical School (to N.B.). Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, the Stockholm Cancer Foundation and the Swedish Cancer Society. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. kConFab is supported by grants from the National Breast Cancer Foundation , the NHMRC, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia and the Cancer Foundation of Western Australia. The kConFab Clinical Follow Up Study was funded by the NHMRC (145684, 288704, 454508). Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command (DAMD17-01-1-0729), the Cancer Council of Tasmania and Cancer Foundation of Western Australia and the NHMRC (199600). G.C.T. and P.W. are supported by the NHMRC. LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018 and 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. LMBC is supported by the ‘Stichting tegen Kanker’ (232-2008 and 196-2010). The MARIE study was supported by the Deutsche Krebshilfe e.V. (70-2892-BR I), the Federal Ministry of Education Research (BMBF) Germany (01KH0402), the Hamburg Cancer Society and the German Cancer Research Center (DKFZ). MBCSG is supported by grants from the Italian Association ciation for Cancer Research (AIRC) and by funds from the Italian citizens who allocated a 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects ‘5 × 1000’). The MCBCS was supported by the NIH grants (CA122340, CA128978) and a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. The MEC was supported by NIH grants CA63464, CA54281, CA098758 and CA132839. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research (grant CRN-87521) and the Ministry of Economic Development, Innovation and Export Trade (grant PSR-SIIRI-701). MYBRCA is funded by research grants from the Malaysian Ministry of Science, Technology and Innovation (MOSTI), Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation (CARIF). Additional controls were recruited by the Singapore Eye Research Institute, which was supported by a grant from the Biomedical Research Council (BMRC08/1/35/19,tel:08/1/35/19./550), Singapore and the National medical Research Council, Singapore (NMRC/CG/SERI/2010). The NBCS was supported by grants from the Norwegian Research council (155218/V40, 175240/S10 to A.L.B.D., FUGE-NFR 181600/ V11 to V.N.K. and a Swizz Bridge Award to A.L.B.D.). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the Academy of Finland, the University of Oulu, and the Oulu University Hospital. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NLCP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. pKARMA is a combination of the KARMA and LIBRO-1 studies. KARMA was supported by Ma¨rit and Hans Rausings Initiative Against Breast Cancer. KARMA and LIBRO-1 were supported the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linnaeus Centre (Contract ID 70867902) financed by the Swedish Research Council. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SASBAC was supported by funding from the Agency for Science, Technology and Research of Singapore (A∗STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation KC was financed by the Swedish Cancer Society (5128-B07-01PAF). The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The SBCS was supported by Yorkshire Cancer Research S305PA, S299 and S295. Funding for the SCCS was provided by NIH grant R01 CA092447. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by a programme grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the National Medical Research Council Start-up Grant and Centre Grant (NMRC/CG/NCIS /2010). The recruitment of controls by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC) was funded by the Biomedical Research Council (grant number: 05/1/21/19/425). SKKDKFZS is supported by the DKFZ. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. K. J. is a fellow of International PhD program, Postgraduate School of Molecular Medicine, Warsaw Medical University, supported by the Polish Foundation of Science. The TNBCC was supported by the NIH grant (CA128978), the Breast Cancer Research Foundation , Komen Foundation for the Cure, the Ohio State University Comprehensive Cancer Center, the Stefanie Spielman Fund for Breast Cancer Research and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. Part of the TNBCC (DEMOKRITOS) has been co-financed by the European Union (European Social Fund – ESF) and Greek National Funds through the Operational Program ‘Education and Life-long Learning’ of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: ARISTEIA. The TWBCS is supported by the Institute of Biomedical Sciences, Academia Sinica and the National Science Council, Taiwan. The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR). ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. Funding to pay the Open Access publication charges for this article was provided by the Wellcome Trust.This is the advanced access published version distributed under a Creative Commons Attribution License 2.0, which can also be viewed on the publisher's webstie at: http://hmg.oxfordjournals.org/content/early/2014/07/04/hmg.ddu311.full.pdf+htm

The Visual Matrix method in a study of death and dying: Methodological reflections

The Visual Matrix method is designed to elicit imagistic and associative contributions established collectively amongst participants in a group setting. In this article, a hard to-reach area of experience - death and dying - illustrates the production of shared cultural images beyond individual experience. Our dual purpose was to assess the suitability of the method for this challenging topic, and to understand the ways in which death figured in the imagination of the participants. Three theorists, Wilfred Bion, Alfred Lorenzer and Gilles Deleuze, enable us to theorise psychosocial processes of symbolisation beyond cognition

Satellite‐based habitat monitoring reveals long‐term dynamics of deer habitat in response to forest disturbances

Disturbances play a key role in driving forest ecosystem dynamics, but how disturbances shape wildlife habitat across space and time often remains unclear. A major reason for this is a lack of information about changes in habitat suitability across large areas and longer time periods. Here, we use a novel approach based on Landsat satellite image time series to map seasonal habitat suitability annually from 1986 to 2017. Our approach involves characterizing forest disturbance dynamics using Landsat‐based metrics, harmonizing these metrics through a temporal segmentation algorithm, and then using them together with GPS telemetry data in habitat models. We apply this framework to assess how natural forest disturbances and post‐disturbance salvage logging affect habitat suitability for two ungulates, roe deer (Capreolus capreolus) and red deer (Cervus elaphus), over 32 yr in a Central European forest landscape. We found that red and roe deer differed in their response to forest disturbances. Habitat suitability for red deer consistently improved after disturbances, whereas the suitability of disturbed sites was more variable for roe deer depending on season (lower during winter than summer) and disturbance agent (lower in windthrow vs. bark‐beetle‐affected stands). Salvage logging altered the suitability of bark beetle‐affected stands for deer, having negative effects on red deer and mixed effects on roe deer, but generally did not have clear effects on habitat suitability in windthrows. Our results highlight long‐lasting legacy effects of forest disturbances on deer habitat. For example, bark beetle disturbances improved red deer habitat suitability for at least 25 yr. The duration of disturbance impacts generally increased with elevation. Methodologically, our approach proved effective for improving the robustness of habitat reconstructions from Landsat time series: integrating multiyear telemetry data into single, multi‐temporal habitat models improved model transferability in time. Likewise, temporally segmenting the Landsat‐based metrics increased the temporal consistency of our habitat suitability maps. As the frequency of natural forest disturbances is increasing across the globe, their impacts on wildlife habitat should be considered in wildlife and forest management. Our approach offers a widely applicable method for monitoring habitat suitability changes caused by landscape dynamics such as forest disturbance.Federal State of BerlinEuropean Commission http://dx.doi.org/10.13039/501100000780Peer Reviewe