Zhang, Y., Loreau, M., He, N., Zhang, G. & Han, X. (2017).
Mowing exacerbates the loss of ecosystem stability under nitrogen enrichment in a temperate grassland.
Functional Ecology,
31(8), 1637-1646.
https://doi.org/10.1111/1365-2435.12850
Zhang, Y.
, Jeppesen, E., Liu, X., Qin, B., Shi, K., Zhou, Y., Thomaz, S. M.
& Deng, J. (2017).
Global loss of aquatic vegetation in lakes.
Earth-Science Reviews,
173, 259-265.
https://doi.org/10.1016/j.earscirev.2017.08.013
Zhang, Z., Xu, R., Wang, Z., Dong, M., Cui, B.
& Chen, M. (2017).
Visible Light Neural Stimulation on graphitic-Carbon Nitride/Graphene Photocatalytic Fibers.
A C S Applied Materials and Interfaces,
9(40), 34736–34743.
https://doi.org/10.1021/acsami.7b12733
Zhang, Y., Xiao, X., Zhang, Y., Wolf, S., Zhou, S., Joiner, J., Guanter, L., Verma, M., Sun, Y., Yang, X., Paul-Limoges, E., Gough, C. M., Wohlfahrt, G., Gioli, B., van der Tol, C., Yann, N.
, Lund, M. & de Grandcourt, A. (2018).
On the relationship between sub-daily instantaneous and daily total gross primary production: Implications for interpreting satellite-based SIF retrievals.
Remote Sensing of Environment,
205, 276-289.
https://doi.org/10.1016/j.rse.2017.12.009
Zhang, L., Lyu, T., Zhang, Y., Button, M.
, Arias, C. A., Weber, K. P.
, Brix, H. & Carvalho, P. N. (2018).
Impacts of design configuration and plants on the functionality of the microbial community of mesocosm-scale constructed wetlands treating ibuprofen.
Water Research,
131, 228-238.
https://doi.org/10.1016/j.watres.2017.12.050
Zhang, T., Brantley, S. L.
, Verreault, D., Dhankani, R., Corcelli, S. A. & Allen, H. C. (2018).
Effect of pH and Salt on Surface pKa of Phosphatidic Acid Monolayers.
Langmuir,
34(1), 530-539.
https://doi.org/10.1021/acs.langmuir.7b03579
Zhang, Y., He, N., Loreau, M., Pan, Q. & Han, X. (2018).
Scale dependence of the diversity-stability relationship in a temperate grassland.
Journal of Ecology,
106(3), 1277-1285.
https://doi.org/10.1111/1365-2745.12903
Zhang, L., Carvalho, P. N., Bollmann, U. E., El-taliawy, H., Brix, H. & Bester, K. (2018).
Effects of carbon feeding on pharmaceutical removal from wastewater effluent in a sand filtration.
Zhang, W., Jansson, P.-E., Schurgers, G., Hollesen, J.
, Lund, M., Abermann, J. & Elberling, B. (2018).
Process-Oriented Modeling of a High Arctic Tundra Ecosystem: Long-Term Carbon Budget and Ecosystem Responses to Interannual Variations of Climate.
Journal of Geophysical Research: Biogeosciences,
123(4), 1178-1196.
https://doi.org/10.1002/2017JG003956
Zhang, Q., Calus, M., Bosse, M.
, Sahana, G., Lund, M. S. & Guldbrandtsen, B. (2018).
Human-Mediated Introgression of Haplotypes in a Modern Dairy Cattle Breed.
Genetics,
209(4), 1305-1317.
https://doi.org/10.1534/genetics.118.301143
Zhang, N., Rao, R. S. P., Salvato, F.
, Havelund, J. F., Møller, I. M., Thelen, J. J. & Xu, D. (2018).
MU-LOC: A machine-learning method for predicting mitochondrially localized proteins in plants.
Frontiers in Plant Science,
9, Article 634.
https://doi.org/10.3389/fpls.2018.00634
Zhang, Q., Dong, X., Chen, Y., Yang, X., Xu, M.
, Davidson, T. A. & Jeppesen, E. (2018).
Hydrological alterations as the major driver on environmental change in a floodplain Lake Poyang (China): Evidence from monitoring and sediment records.
Journal of Great Lakes Research,
44(3), 377-387.
https://doi.org/10.1016/j.jglr.2018.02.003
Zhang, L., Lyu, T., Ramírez Vargas, C. A., Arias, C. A., Carvalho, P. N. & Brix, H. (2018).
New insights into the effects of support matrix on the removal of organic micro-pollutants and the microbial community in constructed wetlands.
Environmental Pollution,
240, 699-708.
https://doi.org/10.1016/j.envpol.2018.05.028
Zhang, Y.
, Fox, A. D., Cao, L., Jia, Q., Lu, C., Prins, H. H. T. & de Boer, W. F. (2019).
Effects of ecological and anthropogenic factors on waterbird abundance at a Ramsar site in the Yangtze River floodplain.
Ambio,
48(3), 293–303.
https://doi.org/10.1007/s13280-018-1076-1
Zhang, H., Xu, W., Li, X., Luo, H.
, Liu, A. & Wang, Y. (2018).
Genetic analysis of skinfold thickness and its association with body condition score, and milk production traits in Chinese Holstein population. Abstract from ICAR Conference and World Congress on Genetics Applied to Livestock Production 2018, Auckland, New Zealand.
Zhang, Y., Biao, H.
, Thomsen, M., Sabel, C. E., Hess, F., Hu, W. & Tian, K. (2018).
One overlooked source from phthalate exposure - oral intake from vegetables produced in plastic greenhouses in China.
Science of the Total Environment,
642, 1127-1135.
https://doi.org/10.1016/j.scitotenv.2018.06.112
Zhang, Y., Lyu, T., Zhang, L., Button, M.
, Arias, C. A., Weber, K. P., Shi, J., Chen, Z.
, Brix, H. & Carvalho, P. N. (2019).
Microbial community metabolic profiles in saturated constructed wetlands treating iohexol and ibuprofen.
Science of the Total Environment,
651, 1926-1934.
https://doi.org/10.1016/j.scitotenv.2018.10.103
Zhang, Z., Zhang, Q., Xiao, Q., Sun, H.
, Gao, H., Yang, Y., Chen, J., Li, Z., Xue, M., Ma, P., Yang, H., Xu, N., Wang, Q. & Pan, Y. (2018).
Distribution of runs of homozygosity in Chinese and Western pig breeds evaluated by reduced-representation sequencing data.
Animal Genetics,
49(6), 579-591.
https://doi.org/10.1111/age.12730
Zhang, Q., Sahana, G., Su, G., Guldbrandtsen, B., Lund, M. S. & Calus, M. P. L. (2018).
Impact of rare and low-frequency sequence variants on reliability of genomic prediction in dairy cattle.
Genetics Selection Evolution,
50(1), Article 62.
https://doi.org/10.1186/s12711-018-0432-8
Zhang, H., Liu, A., Li, X., Xu, W., Shi, R., Luo, H.
, Su, G., Dong, G.
, Guo, G. & Wang, Y. (2019).
Genetic analysis of skinfold thickness and its association with body condition score and milk production traits in Chinese Holstein population.
Journal of Dairy Science,
102(3), 2347-2352.
https://doi.org/10.3168/jds.2018-15180
Zhang, H., Lopez, P. C., Holland, C., Lunde, A.
, Ambye-Jensen, M., Felby, C. & Thomsen, S. T. (2018).
The multi-feedstock biorefinery – Assessing the compatibility of alternative feedstocks in a 2G wheat straw biorefinery process.
GCB Bioenergy,
10(12), 946-959.
https://doi.org/10.1111/gcbb.12557
Zhang, Z., Kargo, M., Liu, A., Thomasen, J. R., Pan, Y.
& Su, G. (2019).
Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model.
Heredity,
123(2), 202-214.
https://doi.org/10.1038/s41437-019-0192-4
Zhang, Q., Dong, X., Yang, X.
, Odgaard, B. V. & Jeppesen, E. (2019).
Hydrologic and anthropogenic influences on aquatic macrophyte development in a large, shallow lake in China.
Freshwater Biology,
64(4), 799-812.
https://doi.org/10.1111/fwb.13263
Zhang, P.
, Wang, Z., Liu, L., Klausen, L. H., Wang, Y., Mi, J. & Dong, M. (2019).
Modulation the electronic property of 2D monolayer MoS2 by amino acid.
Applied Materials Today,
14(March), 151-158.
https://doi.org/10.1016/j.apmt.2018.12.003
Zhang, W., Jansson, P. E., Sigsgaard, C., McConnell, A., Jammet, M. M., Westergaard-Nielsen, A.
, Lund, M., Friborg, T., Michelsen, A. & Elberling, B. (2019).
Model-data fusion to assess year-round CO
2
fluxes for an arctic heath ecosystem in West Greenland (69°N).
Agricultural and Forest Meteorology,
272-273(July), 176-186.
https://doi.org/10.1016/j.agrformet.2019.02.021
Zhang, W., Zhou, Y.
, Jeppesen, E., Wang, L., Tan, H. & Zhang, J. (2019).
Linking heterotrophic bacterioplankton community composition to the optical dynamics of dissolved organic matter in a large eutrophic Chinese lake.
Science of the Total Environment,
679, 136-147.
https://doi.org/10.1016/j.scitotenv.2019.05.055
Zhang, T.
, Gao, H., Sahana, G., Zan, Y., Fan, H., Liu, J., Shi, L., Liu, J., Du, L., Wang, L. & Zhao, F. (2019).
Genome-wide association studies revealed candidate genes for tail fat deposition and body size in the Hulun Buir sheep.
Journal of Animal Breeding and Genetics,
136(5), 362-370.
https://doi.org/10.1111/jbg.12402
Zhang, M., Zheng, T.
, Sheng, B., Wu, F., Zhang, Q., Wang, W., Shen, J., Zhou, N. & Sun, Y. (2019).
Mn
2+
complex-modified polydopamine- and dual emissive carbon dots based nanoparticles for in vitro and in vivo trimodality fluorescent, photothermal, and magnetic resonance imaging.
Chemical Engineering Journal,
373, 1054-1063.
https://doi.org/10.1016/j.cej.2019.05.107