Spatial weed distribution models under climate change: a short review
暂无分享,去创建一个
[1] J. Wan,et al. Implications of climate change for environmental niche overlap between five Cuscuta pest species and their two main Leguminosae host crop species , 2022, Weed Science.
[2] A. Arneth,et al. Summary for Policymakers , 2022, The Ocean and Cryosphere in a Changing Climate.
[3] R. Early,et al. Comparing, evaluating, and combining statistical Species Distribution Models and CLIMEX to forecast the distributions of emerging crop pests. , 2021, Pest management science.
[4] K. Walker,et al. Characterizing the environmental drivers of the abundance and distribution of Alopecurus myosuroides at a national scale. , 2021, Pest management science.
[5] Yaqin Fang,et al. Predicting the invasive trend of exotic plants in China based on the ensemble model under climate change: A case for three invasive plants of Asteraceae. , 2020, The Science of the total environment.
[6] I. Somodi,et al. The way bioclimatic variables are calculated has impact on potential distribution models , 2020, Methods in Ecology and Evolution.
[7] L. Kumar,et al. Invasive weed species’ threats to global biodiversity: Future scenarios of changes in the number of invasive species in a changing climate , 2020, Ecological Indicators.
[8] Junmin Li,et al. Predicting the potential distribution of the parasitic Cuscuta chinensis under global warming , 2019, BMC Ecology.
[9] Chunjing Wang,et al. Determining key monitoring areas for the 10 most important weed species under a changing climate. , 2019, The Science of the total environment.
[10] F. Yu,et al. Effects of occurrence record number, environmental variable number, and spatial scales on MaxEnt distribution modelling for invasive plants , 2019, Biologia.
[11] Joy R. Petway,et al. Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models , 2019, Nature Conservation.
[12] P. Tiffin,et al. Species distribution models throughout the invasion history of Palmer amaranth predict regions at risk of future invasion and reveal challenges with modeling rapidly shifting geographic ranges , 2019, Scientific Reports.
[13] G. J. de la Vega,et al. Predicting the distribution of harmful species and their natural enemies in agricultural, livestock and forestry systems: an overview , 2018, International Journal of Pest Management.
[14] Haiyan Song,et al. Tourism and Economic Globalization: An Emerging Research Agenda , 2018 .
[15] G. Mace,et al. Insights from modeling studies on how climate change affects invasive alien species geography , 2018, Ecology and evolution.
[16] S. Dullinger,et al. Climate warming drives invasion history of Ambrosia artemisiifolia in central Europe , 2018 .
[17] Nicholas E. Korres,et al. Cultivars to face climate change effects on crops and weeds: a review , 2016, Agronomy for Sustainable Development.
[18] Guishuang Li,et al. Modeling habitat distribution of Cornus officinalis with Maxent modeling and fuzzy logics in China , 2016 .
[19] Gul Hassan,et al. Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling , 2015, Global change biology.
[20] P. Hulme. Invasion pathways at a crossroad: policy and research challenges for managing alien species introductions , 2015 .
[21] B. Gallardo,et al. The Importance of the Human Footprint in Shaping the Global Distribution of Terrestrial, Freshwater and Marine Invaders , 2015, PloS one.
[22] Marleen M. P. Cobben,et al. Robustness and accuracy of Maxent niche modelling for Lactuca species distributions in light of collecting expeditions , 2014, Plant Genetic Resources.
[23] B. Gerowitt,et al. Impact of climate change on weeds in agriculture: a review , 2014, Agronomy for Sustainable Development.
[24] C. Wirth,et al. Disentangling the environmental-heterogeneity--species-diversity relationship along a gradient of human footprint. , 2014, Ecology.
[25] J. González-Andújar,et al. Potential distribution of Avena sterilis L. in Europe under climate change , 2014 .
[26] J. Elith. Predicting distributions of invasive species , 2013, 1312.0851.
[27] Boris Schröder,et al. The importance of correcting for sampling bias in MaxEnt species distribution models , 2013 .
[28] Matthew J. Smith,et al. Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates , 2013, bioRxiv.
[29] Andrew M. Liebhold,et al. Live plant imports: the major pathway for forest insect and pathogen invasions of the US , 2012 .
[30] Paul Chinowsky,et al. Climate change: comparative impact on developing and developed countries , 2011 .
[31] M. Araújo,et al. Biotic and abiotic variables show little redundancy in explaining tree species distributions , 2010 .
[32] P. Hulme. Trade, transport and trouble: managing invasive species pathways in an era of globalization , 2009 .
[33] J. Elith,et al. Sensitivity of predictive species distribution models to change in grain size , 2007 .
[34] H. Mooney,et al. Invasive Alien Species in an Era of Globalization , 2007 .
[35] R. Pearson,et al. Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar , 2006 .
[36] P. Newton,et al. Agroecosystems in a Changing Climate , 2006 .
[37] A. Townsend Peterson,et al. Novel methods improve prediction of species' distributions from occurrence data , 2006 .
[38] D. Kriticos,et al. The potential distribution of Chromolaena odorata (Siam weed) in relation to climate , 2005 .
[39] C. Hackney,et al. Distribution ofJuncus roemerianus in North Carolina tidal marshes: The importance of physical and biotic variables , 1997, Wetlands.
[40] M. Y. Wu,et al. [Chemical constituents of ragweed (Ambrosia artemisiifolia L.)]. , 1993, Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica.
[41] J A Swets,et al. Measuring the accuracy of diagnostic systems. , 1988, Science.
[42] E. L. Rice,et al. MECHANISM OF SEED DORMANCY IN AMBROSIA ARTEMISIIFOLIA , 1972 .
[43] J. Wan,et al. CONTRIBUTION OF ENVIRONMENTAL FACTORS TOWARD DISTRIBUTION OF TEN MOST DANGEROUS WEED SPECIES GLOBALLY , 2019, Applied Ecology and Environmental Research.
[44] L. Klimek,et al. Ambrosia (Ambrosia artemisiifolia) , 2014 .
[45] J. S. C. García,et al. Las plantas con flor: apuntes sobre su origen, clasificación y diversidad , 2012 .
[46] Stephen B. Powles,et al. Glyphosate-Resistant Crops and Weeds: Now and in the Future , 2009 .
[47] David M. Richardson,et al. Alien plant invasions in South Africa: driving forces and the human dimension , 2004 .
[48] Hugh J. Beckie,et al. Transgenic crops : new weed problems for Canada? , 1999 .
[49] F. Bazzaz. Ecophysiology of Ambrosia Artemisiifolia: A Successional Dominant , 1974 .