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in EcologyGlobal patterns and climatic controls of forest structural complexity
1.
Ali, A. et al. Impacts of climatic and edaphic factors on the diversity, structure and biomass of species-poor and structurally-complex forests. Sci. Total Environ. 706, 135719 (2020).
ADS CAS PubMed Article Google Scholar
2.
Gauthier, S., Bernier, P., Kuuluvainen, T., Shvidenko, A. Z. & Schepaschenko, D. G. Boreal forest health and global change. Science 349, 819–822 (2015).
ADS CAS PubMed Article Google Scholar3.
Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402 (2017).
ADS Article Google Scholar4.
Penone, C. et al. Specialisation and diversity of multiple trophic groups are promoted by different forest features. Ecol. Lett. 22, 170–180 (2019).
PubMed Article Google Scholar5.
Stein, A., Gerstner, K. & Kreft, H. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. Ecol. Lett. 17, 866–880 (2014).
PubMed Article Google Scholar6.
Gough, C. M., Atkins, J. W., Fahey, R. T. & Hardiman, B. S. High rates of primary production in structurally complex forests. Ecology 100, e02864 (2019).
PubMed Article Google Scholar7.
Stark, S. C. et al. Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment. Ecol. Lett. 15, 1406–1414 (2012).
PubMed Article Google Scholar8.
Ammer, C. et al. Key ecological research questions for Central European forests. Basic Appl. Ecol. 32, 3–25 (2018).
Article Google Scholar9.
Kreft, H. & Jetz, W. Global patterns and determinants of vascular plant diversity. Proc. Natl Acad. Sci. USA 104, 5925–5930 (2007).
ADS CAS PubMed Article Google Scholar10.
Harrison, S., Spasojevic, M. J. & Li, D. Climate and plant community diversity in space and time. Proc. Natl Acad. Sci. USA 117, 4464–4470 (2020).
CAS PubMed Article Google Scholar11.
Ehbrecht, M., Schall, P., Ammer, C. & Seidel, D. Quantifying stand structural complexity and its relationship with forest management, tree species diversity and microclimate. Agric. Meteorol. 242, 1–9 (2017).
Article Google Scholar12.
Seidel, D., Ehbrecht, M., Annighöfer, P. & Ammer, C. From tree to stand-level structural complexity—Which properties make a forest stand complex? Agric. Meteorol. 278, 107699 (2019).
Article Google Scholar13.
Davies, A. B. & Asner, G. P. Advances in animal ecology from 3D-LiDAR ecosystem mapping. Trends Ecol. Evol. 29, 681–691 (2014).
PubMed Article Google Scholar14.
Gough, C. M., Atkins, J. W., Fahey, R. T., Hardiman, B. S. & LaRue, E. A. Community and structural constraints on the complexity of eastern North American forests. Glob. Ecol. Biogeogr. 29, 2107–2118 (2020).15.
MacArthur, R. H. & MacArthur, J. W. On bird species diversity. Ecology 42, 594–598 (1961).
Article Google Scholar16.
Ishii, H. T., Tanabe, S. & Hiura, T. Exploring the relationships among canopy structure, stand productivity, and biodiversity of temperate forest ecosystems. Science 50, 342–355 (2004).
Google Scholar17.
Pretzsch, H. Forest dynamics, growth, and yield. In Forest Dynamics, Growth and Yield: From Measurement to Model (ed. Pretzsch, H.) 1–39 (Springer, 2009).18.
Dassot, M., Constant, T. & Fournier, M. The use of terrestrial LiDAR technology in forest science: application fields, benefits and challenges. Ann. Sci. 68, 959–974 (2011).
Article Google Scholar19.
Ehbrecht, M., Schall, P., Juchheim, J., Ammer, C. & Seidel, D. Effective number of layers: a new measure for quantifying three-dimensional stand structure based on sampling with terrestrial LiDAR. Ecol. Manag. 380, 212–223 (2016).
Article Google Scholar20.
Juchheim, J., Ammer, C., Schall, P. & Seidel, D. Canopy space filling rather than conventional measures of structural diversity explains productivity of beech stands. Ecol. Manag. 395, 19–26 (2017).
Article Google Scholar21.
Atkins, J. W., Fahey, R. T., Hardiman, B. S. & Gough, C. M. Forest canopy structural complexity and light absorption relationships at the subcontinental scale. J. Geophys. Res. Biogeosci. 123, 1387–1405 (2018).
Article Google Scholar22.
Sapijanskas, J., Paquette, A., Potvin, C., Kunert, N. & Loreau, M. Tropical tree diversity enhances light capture through crown plasticity and spatial and temporal niche differences. Ecology 95, 2479–2492 (2014).
Article Google Scholar23.
Fotis, A. T. et al. Forest structure in space and time: Biotic and abiotic determinants of canopy complexity and their effects on net primary productivity. Agric. Meteorol. 250–251, 181–191 (2018).
Article Google Scholar24.
Juchheim, J., Ehbrecht, M., Schall, P., Ammer, C. & Seidel, D. Effect of tree species mixing on stand structural complexity. Int. J. Res. 93, 75–83 (2020).
Google Scholar25.
Zemp, D. C. et al. Mixed-species tree plantings enhance structural complexity in oil palm plantations. Agric. Ecosyst. Environ. 283, 106564 (2019).
Article Google Scholar26.
Jucker, T., Bouriaud, O. & Coomes, D. A. Crown plasticity enables trees to optimize canopy packing in mixed-species forests. Funct. Ecol. 29, 1078–1086 (2015).
Article Google Scholar27.
Morin, X. Species richness promotes canopy packing: a promising step towards a better understanding of the mechanisms driving the diversity effects on forest functioning. Funct. Ecol. 29, 993–994 (2015).
Article Google Scholar28.
McDowell, N. et al. Drivers and mechanisms of tree mortality in moist tropical forests. New Phytol. 851–869 https://doi.org/10.1111/nph.15027@10.1111/(ISSN)1469-8137. (2018).29.
Pretzsch, H. Size-structure dynamics in mixed versus monospecific stands. In Mixed-Species Forests: Ecology and Management (eds. Pretzsch, H., Forrester, D. I. & Bauhus, J.) 211–269 (Springer, 2017).30.
Moncrieff, G. R., Bond, W. J. & Higgins, S. I. Revising the biome concept for understanding and predicting global change impacts. J. Biogeogr. 43, 863–873 (2016).
Article Google Scholar31.
Stegen, J. C. et al. Variation in above-ground forest biomass across broad climatic gradients. Glob. Ecol. Biogeogr. 20, 744–754 (2011).
Article Google Scholar32.
Dubayah, R. et al. The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography. Sci. Remote Sens. 1, 100002 (2020).
Article Google Scholar33.
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
Article Google Scholar34.
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
Article Google Scholar35.
Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on earth a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51, 933–938 (2001).
Article Google Scholar36.
Currie, D. J. et al. Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness. Ecol. Lett. 7, 1121–1134 (2004).
Article Google Scholar37.
Valladares, F. & Niinemets, Ü. Shade tolerance, a key plant feature of complex nature and consequences. Annu. Rev. Ecol. Evol. Syst. 39, 237–257 (2008).
Article Google Scholar38.
Ryan, M. G., Phillips, N. & Bond, B. J. The hydraulic limitation hypothesis revisited. Plant Cell Environ. 29, 367–381 (2006).
PubMed Article Google Scholar39.
Klein, T., Randin, C. & Körner, C. Water availability predicts forest canopy height at the global scale. Ecol. Lett. 18, 1311–1320 (2015).
PubMed Article Google Scholar40.
Asner, G. P. et al. Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation. Science 355, 385–389 (2017).
ADS CAS PubMed Article Google Scholar41.
Schneider, F. D. et al. Mapping functional diversity from remotely sensed morphological and physiological forest traits. Nat. Commun. 8, 1441 (2017).
ADS PubMed PubMed Central Article CAS Google Scholar42.
Thonicke, K. et al. Simulating functional diversity of European natural forests along climatic gradients. J. Biogeogr. 47, 1069–1085 (2020).
Article Google Scholar43.
Willim, K. et al. Assessing understory complexity in beech-dominated Forests (Fagus sylvatica L.) in Central Europe—from managed to primary forests. Sensors 19, 1684 (2019).
Article Google Scholar44.
Eggeling, W. J. Observations on the Ecology of the Budongo Rain Forest, Uganda. J. Ecol. 34, 20–87 (1947).
Article Google Scholar45.
Stephens, S. L. & Gill, S. J. Forest structure and mortality in an old-growth Jeffrey pine-mixed conifer forest in north-western Mexico. Ecol. Manag. 205, 15–28 (2005).
Article Google Scholar46.
Senf, C., Mori, A. S., Müller, J. & Seidl, R. The response of canopy height diversity to natural disturbances in two temperate forest landscapes. Landsc. Ecol. https://doi.org/10.1007/s10980-020-01085-7. (2020)47.
Senf, C. & Seidl, R. Mapping the forest disturbance regimes of Europe. Nat. Sustain. 1–8 https://doi.org/10.1038/s41893-020-00609-y. (2020).48.
Krug, J. H. A. Adaptation of Colophospermum mopane to extra-seasonal drought conditions: site-vegetation relations in dry-deciduous forests of Zambezi region (Namibia). Ecosystems 4, 25 (2017).
Google Scholar49.
Stovall, A. E. L., Shugart, H. & Yang, X. Tree height explains mortality risk during an intense drought. Nat. Commun. 10, 4385 (2019).
ADS CAS PubMed PubMed Central Article Google Scholar50.
Zemp, D. C. et al. Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks. Nat. Commun. 8, 1–10 (2017).
Article CAS Google Scholar51.
Schuldt, B. et al. How adaptable is the hydraulic system of European beech in the face of climate change-related precipitation reduction? N. Phytol. 210, 443–458 (2016).
Article Google Scholar52.
Astrup, R., Bernier, P. Y., Genet, H., Lutz, D. A. & Bright, R. M. A sensible climate solution for the boreal forest. Nat. Clim. Change 8, 11–12 (2018).
ADS Article Google Scholar53.
Trisos, C. H., Merow, C. & Pigot, A. L. The projected timing of abrupt ecological disruption from climate change. Nature 580, 496–501 (2020).
ADS CAS PubMed Article PubMed Central Google Scholar54.
Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389–395 (2002).
ADS CAS PubMed PubMed Central Article Google Scholar55.
Klein, T. & Hartmann, H. Climate change drives tree mortality. Science 362, 758–758 (2018).
ADS CAS PubMed Google Scholar56.
Puettmann, K. J., Coates, K. D. & Messier, C. C. A Critique of Silviculture: Managing for Complexity. (Island Press, 2012).57.
Camarretta, N. et al. Monitoring forest structure to guide adaptive management of forest restoration: a review of remote sensing approaches. New For. https://doi.org/10.1007/s11056-019-09754-5. (2019).58.
Chiarucci, A. & Piovesan, G. Need for a global map of forest naturalness for a sustainable future. Conserv. Biol. 34, 368–372 (2020).
PubMed Article Google Scholar59.
Potapov, P. et al. The last frontiers of wilderness: tracking loss of intact forest landscapes from 2000 to 2013. Sci. Adv. 3, e1600821 (2017).
ADS PubMed PubMed Central Article Google Scholar60.
Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).
ADS CAS PubMed Article PubMed Central Google Scholar61.
Keane, R. E., Holsinger, L. M. & Loehman, R. Bioclimatic modeling of potential vegetation types as an alternative to species distribution models for projecting plant species shifts under changing climates. Ecol. Manag. 477, 118498 (2020).
Article Google Scholar62.
Kier, G. et al. Global patterns of plant diversity and floristic knowledge. J. Biogeogr. 32, 1107–1116 (2005).
Article Google Scholar63.
Schneider, F. D. et al. Towards mapping the diversity of canopy structure from space with GEDI. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/ab9e99. (2020).64.
Campbell, N. A. Biology. (Pearson Education, 1996).65.
Buchwald, E. A hierarchical terminology for more or less natural forests in relation to sustainable management and biodiversity conservation. In Proc. Third Expert Meeting on Harmonizing Forest-related Definitions for Use by Various Stakeholders. Vol. 18 (Food and Agriculture Organization of the United Nations, 2005).66.
Frey, J., Asbeck, T. & Bauhus, J. Predicting tree-related microhabitats by multisensor close-range remote sensing structural parameters for the selection of retention elements. Remote Sens. 12, 867 (2020).
ADS Article Google Scholar67.
Ehbrecht, M., Schall, P., Ammer, C., Fischer, M. & Seidel, D. Effects of structural heterogeneity on the diurnal temperature range in temperate forest ecosystems. Ecol. Manag. 432, 860–867 (2019).
Article Google Scholar68.
Ehbrecht et al. ehbrechtetal/Stand-structural-complexity-index–SSCI: R-code to compute the stand structural complexity index (SSCI). https://doi.org/10.5281/zenodo.4295910. (2017).69.
Trabucco, A. & Zomer, R. Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2. https://doi.org/10.6084/m9.figshare.7504448.v3. (2019)70.
Hengl, T. et al. SoilGrids250m: Global gridded soil information based on machine learning. PLoS ONE 12, e0169748 (2017).
PubMed PubMed Central Article CAS Google Scholar71.
Wieder, W. R., Boehnert, J., Bonan, G. B. & Langseth, M. Regridded Harmonized World Soil Database v1.2. ORNL DAAC. https://doi.org/10.3334/ORNLDAAC/1247 (2014).72.
Fehrmann, L. et al. A unified framework for land cover monitoring based on a discrete global sampling grid (GSG). Environ. Monit. Assess. 191, 46 (2019).
PubMed Article Google Scholar More200 Shares189 Views
in EcologyEffects of a commercially formulated glyphosate solutions at recommended concentrations on honeybee (Apis mellifera L.) behaviours
1.
Gallai, N., Salles, J., Settele, J. & Vaissière, B. E. Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecol. Econ. 68, 810–821 (2009).
Article Google Scholar
2.
Carreck, N. L. & Ratnieks, F. L. W. The dose makes the poison: have “field realistic” rates of exposure of bees to neonicotinoid insecticides been overestimated in laboratory studies?. J. Apicult. Res. 53, 607–614 (2014).
Article Google Scholar3.
Gross, M. New fears over bee declines. Curr. Biol. 21, 137–139 (2011).
Article CAS Google Scholar4.
Lundin, O., Smith, H. G., Fries, I. & Bommarco, R. Neonicotinoid insecticides and their impacts on bees: A systematic review of research approaches and identification of knowledge gaps. PLoS ONE 10, 2 (2015).
Google Scholar5.
Rucker, R. R., Thurman, W. N. & Burgett, M. Honey bee pollination markets and the internalization of reciprocal benefits. Am. J. Agr. Econ. 94, 956–977 (2012).
Article Google Scholar6.
Kremen, C., Williams, N. M. & Thorp, R. W. Crop pollination from native bees at risk from agricultural intensification. Proc. Natl. Acad. Sci. USA. 99, 16812–16816 (2002).
ADS CAS PubMed Article PubMed Central Google Scholar7.
Koh, I., Lonsdorf, E. V., Artz, D. R., Pitts-Singer, T. L. & Ricketts, T. H. Ecology and economics of using native managed bees for almond pollination. J. Econ. Entomol. 111, 16–25 (2018).
PubMed Article PubMed Central Google Scholar8.
Stein, K. et al. Bee pollination increases yield quantity and quality of cash crops in Burkina Faso, West Africa. Sci. Rep.-UK 7, 17610–17691 (2017).
Article CAS Google Scholar9.
Claudianos, C. et al. A deficit of detoxification enzymes: Pesticide sensitivity and environmental response in the honeybee. Insect Mol. Biol. 15, 615–636 (2006).
CAS PubMed PubMed Central Article Google Scholar10.
Abraham, J. et al. Commercially formulated glyphosate can kill non-target pollinator bees under laboratory conditions. Entomol. Exp. Appl. 166, 695–702 (2018).
CAS Article Google Scholar11.
Polyzou, A., Froment, M., Masson, P. & Belzunces, L. P. Absence of a protective effect of the oxime 2-PAM toward paraoxon-poisoned honey bees: Acetylcholinesterase reactivation not at fault. Toxicol. Appl. Pharm. 152, 184–192 (1998).
CAS Article Google Scholar12.
Stanley, J., Sah, K., Jain, S. K., Bhatt, J. C. & Sushil, S. N. Evaluation of pesticide toxicity at their field recommended doses to honeybees, Apis cerana and A. mellifera through laboratory, semi-field and field studies. Chemosphere 119, 668–674 (2015).
ADS CAS PubMed Article PubMed Central Google Scholar13.
Christen, V. & Fent, K. Exposure of honey bees (Apis mellifera) to different classes of insecticides exhibit distinct molecular effect patterns at concentrations that mimic environmental contamination. Environ. Pollut. 226, 48–59 (2017).
CAS PubMed Article PubMed Central Google Scholar14.
Friol, P. S., Catae, A. F., Tavares, D. A., Malaspina, O. & Roat, T. C. Can the exposure of Apis mellifera (Hymenoptera, Apiadae) larvae to a field concentration of thiamethoxam affect newly emerged bees?. Chemosphere 185, 56–66 (2017).
ADS CAS PubMed Article PubMed Central Google Scholar15.
Fulton, C. A. et al. An assessment of pesticide exposures and land use of honey bees in Virginia. Chemosphere 222, 489–493 (2019).
ADS CAS PubMed Article PubMed Central Google Scholar16.
Report, C. R. I. Glyphosate industry overview in China, 2011–2020 (CRI, Shanghai, 2018).
Google Scholar17.
Herbert, L. T., Vazquez, D. E., Arenas, A. & Farina, W. M. Effects of field-realistic doses of glyphosate on honeybee appetitive behaviour. J. Exp. Biol. 217, 3457–3464 (2014).
PubMed Article PubMed Central Google Scholar18.
Motta, E. V. S., Raymann, K. & Moran, N. A. Glyphosate perturbs the gut microbiota of honey bees. Proc. Natl. Acad. Sci. USA. 115, 10305–10310 (2018).
CAS PubMed Article PubMed Central Google Scholar19.
Rahimian, Y. Effect of glyphosate on honey bee (Apis mellifera) performance. Arthropods. 7, 77–81 (2018).
Google Scholar20.
Thompson, H. M. et al. Evaluating exposure and potential effects on honeybee brood (Apis mellifera) development using glyphosate as an example. Integr. Environ. Asses. 10, 463–470 (2014).
ADS CAS Article Google Scholar21.
FAO, China at a glance. http://www.fao.org/china/fao-in-china/china-at-a-glance/en/. (2019) Available.22.
Hou, J. H. Path construction for the reform of the rural land property system. J. Huaiyin Inst. Technol. (2019).23.
Zhang, C. et al. Health effect of agricultural pesticide use in China: Implications for the development of GM crops. Sci. Rep.-UK 6, 2 (2016).
Article CAS Google Scholar24.
Michalková, V. & Pekár, S. How glyphosate altered the behaviour of agrobiont spiders (Araneae: Lycosidae) and beetles (Coleoptera: Carabidae). Biol. Control. 51, 444–449 (2009).
Article CAS Google Scholar25.
Janssens, L. & Stoks, R. Stronger effects of Roundup than its active ingredient glyphosate in damselfly larvae. Aquat. Toxicol. 193, 210–216 (2017).
CAS PubMed Article Google Scholar26.
García-Espiñeira, M., Tejeda-Benitez, L. & Olivero-Verbel, J. Toxicity of atrazine- and glyphosate-based formulations on Caenorhabditis elegans. Ecotox. Environ. Safe. 156, 216–222 (2018).
Article CAS Google Scholar27.
Tierney, K. B., Singh, C. R., Ross, P. S. & Kennedy, C. J. Relating olfactory neurotoxicity to altered olfactory-mediated behaviors in rainbow trout exposed to three currently-used pesticides. Aquat. Toxicol. 81, 55–64 (2007).
CAS PubMed Article PubMed Central Google Scholar28.
Tierney, K. B., Ross, P. S., Jarrard, H. E., Delaney, K. R. & Kennedy, C. J. Changes in juvenile coho salmon electro-olfactogram during and after short-term exposure to current-use pesticides. Environ. Toxicol. Chem. 25, 2809–2817 (2006).
CAS PubMed Article PubMed Central Google Scholar29.
Cattani, D. et al. Developmental exposure to glyphosate-based herbicide and depressive-like behavior in adult offspring: implication of glutamate excitotoxicity and oxidative stress. Toxicology 387, 67–80 (2017).
CAS PubMed Article PubMed Central Google Scholar30.
Zaluski, R., Kadri, S. M., Alonso, D. P., Martins Ribolla, P. E. & de Oliveira, O. R. Fipronil promotes motor and behavioral changes in honey bees (Apis mellifera) and affects the development of colonies exposed to sublethal doses. Environ. Toxicol. Chem. 34, 1062–1069 (2015).
CAS PubMed Article PubMed Central Google Scholar31.
El Hassani, A. K. et al. Effects of sublethal doses of acetamiprid and thiamethoxam on the behavior of the honeybee (Apis mellifera). Arch. Environ. Con. Tox. 54, 653–661 (2008).
Article CAS Google Scholar32.
Balbuena, M. S. et al. Effects of sublethal doses of glyphosate on honeybee navigation. J. Exp. Biol. 218, 2799–2805 (2015).
PubMed Article PubMed Central Google Scholar33.
Company, Monsanto. Material safety data sheet for Roundup Original Herbicide. https://www.fumigationzone.com/files/53/Roundup+Original+-+EPA. (2006).34.
Decourtye, A., Lacassie, E. & Pham-Delègue, M. Learning performances of honeybees (Apis mellifera L.) are differentially affected by imidacloprid according to the season. Pest. Manag. Sci. 59, 269–278 (2003).
CAS PubMed Article PubMed Central Google Scholar35.
Haydak, M. H. Honey bee nutrition. Annu. Rev. Entomol. 15, 143–156 (1970).
Article Google Scholar36.
Winston, M. L. The biology of the honey bee. Q. Rev. Biol. 27, 239–243 (1987).
Google Scholar37.
Wang, N. et al. Influence of sediment on the fate and toxicity of a polyethoxylated tallowamine surfactant system (MON 0818) in aquatic microcosms. Chemosphere 59, 545–551 (2005).
ADS CAS PubMed Article PubMed Central Google Scholar38.
Brausch, J. M., Beall, B. & Smith, P. N. Acute and sub-lethal toxicity of three POEA surfactant formulations to Daphnia magna. Bull. Environ. Contam. Toxicol. 78, 510–514 (2007).
CAS PubMed Article PubMed Central Google Scholar39.
Brausch, J. M., Brausch, J. M., Smith, P. N. & Smith, P. N. Toxicity of three polyethoxylated tallowamine surfactant formulations to laboratory and field collected fairy shrimp Thamnocephalus platyurus. Arch. Environ. Con. Tox. 52, 217–221 (2007).
CAS Article Google Scholar40.
Benachour, N. & Seralini, G. Glyphosate formulations induce apoptosis and necrosis in human umbilical, embryonic, and placental cells. Chem. Res. Toxicol. 22, 97–105 (2009).
CAS PubMed Article PubMed Central Google Scholar41.
Gasnier, C. et al. Dig1 protects against cell death provoked by glyphosate-based herbicides in human liver cell lines. J. Occup. Med. Toxicol. 5, 29 (2010).
PubMed PubMed Central Article CAS Google Scholar42.
Tsui, M. T. K. & Chu, L. M. Aquatic toxicity of glyphosate-based formulations: Comparison between different organisms and the effects of environmental factors. Chemosphere 52, 1189–1197 (2003).
ADS CAS PubMed Article PubMed Central Google Scholar43.
Marc, J. et al. A glyphosate-based pesticide impinges on transcription. Toxicol. Appl. Pharm. 203, 1–8 (2005).
CAS Article Google Scholar44.
Defarge, N. et al. Co-Formulants in glyphosate-based herbicides disrupt aromatase activity in human cells below toxic levels. Int. J. Env. Res. Pub. He. 13, 264 (2016).
Article CAS Google Scholar45.
NPIC., Techincal fact sheet for glyphosate. http://npic.orst.edu/factsheets/archive/glyphotech.html (2011).46.
Mengoni, G. C. & Farina, W. M. Impaired associative learning after chronic exposure to pesticides in young adult honey bees. J. Exp. Biol. 221, 2 (2018).
Google Scholar47.
Balbuena, M. S., Arenas, A. & Farina, W. M. Floral scents learned inside the honeybee hive have a long-lasting effect on recruitment. Anim. Behav. 84, 77–83 (2012).
Article Google Scholar48.
Goyret, J. & Farina, W. M. Non-random nectar unloading interactions between foragers and their receivers in the honeybee hive. Sci. Nat.-Heidelberg. 92, 440–443 (2005).
CAS Article Google Scholar49.
Faita, M. R., Oliveira, E. D. M., Alves, V. V., Orth, A. I. & Nodari, R. O. Changes in hypopharyngeal glands of nurse bees (Apis mellifera) induced by pollen-containing sublethal doses of the herbicide Roundup. Chemosphere 211, 566–572 (2018).
ADS CAS PubMed Article PubMed Central Google Scholar50.
Mesnage, R. et al. Glyphosate exposure in a farmer’s family. J. Environ. Prot. 03, 1001–1003 (2012).
CAS Article Google Scholar51.
Samsel, A. & Seneff, S. Glyphosate’s suppression of cytochrome p450 enzymes and amino acid biosynthesis by the gut microbiome: pathways to modern diseases. Entropy-Switz. 15, 1416–1463 (2013).
ADS CAS Article Google Scholar52.
Ying, C. Brief analysis on the application technique of Roundup. Forest Investig. Des. 2, 39–40 (2007).
MathSciNet Google Scholar53.
Jing, X., Qi, J. & Yang, H. Pesticide residue level and dietary exposure risk assessment of Lycium barbarum in Golmud. Ecol. Environ. 28, 1007–1012 (2019).
Google Scholar54.
Decourtye, A. et al. Comparative sublethal toxicity of nine pesticides on olfactory learning performances of the honeybee Apis mellifera. Arch. Environ. Con. Tox. 48, 242–250 (2005).
CAS Article Google Scholar More38 Shares159 Views
in EcologyBeneath the glacier
The frigid environment under glaciers is inhospitable to all but the most intrepid of microscopic life. To eke out a living, these microbes must do without sunlight and the photosynthetically fixed carbon that fuels most other ecosystems on Earth. Instead, such ecosystems are likely supported by chemosynthetic primary production that capitalizes on energy from inorganic reactions to produce biomass, but the exact mechanisms enabling such chemosynthetic life under the ice are unknown.
Eric Dunham, from Montana State University, USA, and colleagues collected sediments from a glacial system in Iceland that overlays a silicate mineral-rich basaltic catchment, conditions that are prevalent across glacial systems. High concentrations of the reductant hydrogen (H2) were detected, which likely formed when silicate minerals pulverized by the glacier reacted with water. In microcosms seeded with the sediments and amended with H2 and 14CO2, subglacial microbes could oxidize H2, using the resulting energy for chemosynthetic carbon fixation. Metagenomic sequencing from enrichment cultures revealed two prominent autotrophic hydrogenotroph populations, one likely restricted to H2-based chemoautotrophy and one with genomic potential for mixotrophy. The populations exhibited rates of H2 oxidation and carbon fixation approximately tenfold higher than those taken from a Canadian glacier overlying carbonate and shale, suggesting specialization to H2-rich conditions in basalt-glacier systems.
Credit: Natthawat/Getty Images
Interactions between glaciers and rock that can turn an otherwise inhospitable environment into a home for microbes could have implications beyond present-day Earth. Icy H2-dependent primary production could have sustained life during Snowball Earth episodes in our planet’s distant past, or could pave the way for life to evolve on Saturn’s frozen moon Enceladus. More
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in EcologyDevelopmental stages of peach, plum, and apple fruit influence development and fecundity of Grapholita molesta (Lepidoptera: Tortricidae)
Stage development and survival rates
Egg duration of G. molesta was not affected by fruit species (F = 0.54, df = 2, 261, P = 0.581), by collection date (F = 0.06, df = 2, 261, P = 0.941), or by fruit species by collection date interaction (F = 0.24, df = 4, 261, P = 0.914) (Table 1). Durations of other life stages were all significantly affected by fruit species (larva F = 28.16, df = 2, 144, P More