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  • Journal article
    Neafsey DE, Waterhouse RM, Abai MR, Aganezov SS, Alekseyev MA, Allen JE, Amon J, Arca B, Arensburger P, Artemov G, Assour LA, Basseri H, Berlin A, Birren BW, Blandin SA, Brockman AI, Burkot TR, Burt A, Chan CS, Chauve C, Chiu JC, Christensen M, Costantini C, Davidson VLM, Deligianni E, Dottorini T, Dritsou V, Gabriel SB, Guelbeogo WM, Hall AB, Han MV, Hlaing T, Hughes DST, Jenkins AM, Jiang X, Jungreis I, Kakani EG, Kamali M, Kemppainen P, Kennedy RC, Kirmitzoglou IK, Koekemoer LL, Laban N, Langridge N, Lawniczak MKN, Lirakis M, Lobo NF, Lowy E, MacCallum RM, Mao C, Maslen G, Mbogo C, McCarthy J, Michel K, Mitchell SN, Moore W, Murphy KA, Naumenko AN, Nolan T, Novoa EM, O Loughlin S, Oringanje C, Oshaghi MA, Pakpour N, Papathanos PA, Peery AN, Povelones M, Prakash A, Price DP, Rajaraman A, Reimer LJ, Rinker DC, Rokas A, Russell TL, Sagnon NF, Sharakhova MV, Shea T, Simao FA, Simard F, Slotman MA, Somboon P, Stegniy V, Struchiner CJ, Thomas GWC, Tojo M, Topalis P, Tubio JMC, Unger MF, Vontas J, Walton C, Wilding CS, Willis JH, Wu Y-C, Yan G, Zdobnov EM, Zhou X, Catteruccia F, Christophides GK, Collins FH, Cornman RS, Crisanti A, Donnelly MJ, Emrich SJ, Fontaine MC, Gelbart W, Hahn MW, Hansen IA, Howell PI, Kafatos FC, Kellis M, Lawson D, Louis C, Luckhart S, Muskavitch MAT, Ribeiro JM, Riehle MA, Sharakhov IV, Tu Z, Zwiebel LJ, Besansky NJet al., 2015,

    Highly evolvable malaria vectors: The genomes of 16 Anopheles mosquitoes

    , Science, Vol: 347
  • Journal article
    Gill RJ, Raine NE, 2014,

    Chronic impairment of bumblebee natural foraging behaviour induced by sublethal pesticide exposure

    , FUNCTIONAL ECOLOGY, Vol: 28, Pages: 1459-1471, ISSN: 0269-8463
  • Journal article
    Batsaikhan N, Buuveibaatar B, Chimed B, Enkhtuya O, Galbrakh D, Ganbaatar O, Lkhagvasuren B, Nandintsetseg D, Berger J, Calabrese JM, Edwards AE, Fagan WF, Fuller TK, Heiner M, Ito TY, Kaczensky P, Leimgruber P, Lushchekina A, Milner-Gulland EJ, Mueller T, Murray MG, Olson KA, Reading R, Schaller GB, Stubbe A, Stubbe M, Walzer C, Von Wehrden H, Whitten Tet al., 2014,

    Conserving the World's Finest Grassland Amidst Ambitious National Development

    , CONSERVATION BIOLOGY, Vol: 28, Pages: 1736-1739, ISSN: 0888-8892
  • Journal article
    Clements T, Suon S, Wilkie DS, Milner-Gulland EJet al., 2014,

    Impacts of Protected Areas on Local Livelihoods in Cambodia

    , WORLD DEVELOPMENT, Vol: 64, Pages: S125-S134, ISSN: 0305-750X
  • Journal article
    Ahmed SE, Lees AC, Moura NG, Gardner TA, Barlow J, Ferreira J, Ewers RMet al., 2014,

    Road networks predict human influence on Amazonian bird communities

    , PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 281, ISSN: 0962-8452
  • Journal article
    Carrasco LR, Larrosa C, Milner-Gulland EJ, Edwards DPet al., 2014,

    Tropical crops: cautious optimism Response

    , SCIENCE, Vol: 346, Pages: 928-928, ISSN: 0036-8075
  • Journal article
    Milner-Gulland EJ, Baillie J, Washington H, Waterman Cet al., 2014,

    A framework for evaluating the effectiveness of conservation attention at the species level

    , Oryx, ISSN: 1365-3008

    It is essential to understand whether conservation interventions are having the desired effect, particularly in light of increasing pressures on biodiversity and because of requirements by donors that project success be demonstrated. Whilst most evaluations look at effectiveness at a project or organizational level, local efforts need to be connected to an understanding of the effectiveness of conservation directed at a species as a whole, particularly as most metrics of conservation success are at the level of species. We present a framework for measuring the effectiveness of conservation attention at a species level over time, based on scoring eight factors essential for species conservation (engaging stakeholders, management programme, education and awareness, funding and resource mobilization, addressing threats, communication, capacity building and status knowledge), across input, output and outcome stages, in relation to the proportion of the species’ range where each factor attains its highest score. The framework was tested using expert elicitation for 35 mammal and amphibian species on the Zoological Society of London's list of Evolutionarily Distinct and Globally Endangered species. Broad patterns in the index produced by the framework could suggest potential mechanisms underlying change in species status. Assigning an uncertainty score to information demonstrates not only where gaps in knowledge exist, but discrepancies in knowledge between experts. This framework could be a useful tool to link local and global scales of impact on species conservation, and could provide a simple and visually appealing way of tracking conservation over time.

  • Journal article
    Tessarolo G, Rangel TF, Araujo MB, Hortal Jet al., 2014,

    Uncertainty associated with survey design in Species Distribution Models

    , DIVERSITY AND DISTRIBUTIONS, Vol: 20, Pages: 1258-1269, ISSN: 1366-9516
  • Journal article
    Lim J, Crawley MJ, De Vere N, Rich T, Savolainen Vet al., 2014,

    A phylogenetic analysis of the British flora sheds light on the evolutionary and ecological factors driving plant invasions

    , ECOLOGY AND EVOLUTION, Vol: 4, Pages: 4258-4269, ISSN: 2045-7758
  • Journal article
    Tang CQ, Humphreys AM, Fontaneto D, Barraclough TGet al., 2014,

    Effects of phylogenetic reconstruction method on the robustness of species delimitation using single-locus data

    , Methods in Ecology and Evolution, Vol: 5, Pages: 1086-1094, ISSN: 2041-210X

    1. Coalescent-based species delimitation methods combine population genetic and phylogenetic theory to provide an objective means for delineating evolutionarily significant units of diversity. The generalised mixed Yule coalescent (GMYC) and the Poisson tree process (PTP) are methods that use ultrametric (GMYC or PTP) or non-ultrametric (PTP) gene trees as input, intended for use mostly with single-locus data such asDNAbarcodes. 2. Here, we assess how robust the GMYC and PTP are to different phylogenetic reconstruction and branch smoothingmethods.We reconstruct over 400 ultrametric trees using up to 30 different combinations of phylogenetic and smoothing methods and perform over 2000 separate species delimitation analyses across 16 empirical data sets. We then assess how variable diversity estimates are, in terms of richness and identity, with respect to species delimitation, phylogenetic and smoothing methods. 3. The PTP method generally generates diversity estimates that are more robust to different phylogenetic methods. The GMYC is more sensitive, but provides consistent estimates for BEAST trees. The lower consistency of GMYC estimates is likely a result of differences among gene trees introduced by the smoothing step. Unresolved nodes (real anomalies or methodological artefacts) affect both GMYC and PTP estimates, but have a greater effect on GMYC estimates. Branch smoothing is a difficult step and perhaps an underappreciated source of bias that may be widespread among studies of diversity and diversification. 4. Nevertheless, careful choice of phylogenetic method does produce equivalent PTP and GMYC diversity estimates. We recommend simultaneous use of the PTP model with any model-based gene tree (e.g. RAxML) and GMYCapproaches with BEAST trees for obtaining species hypotheses.

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