Model results of the impact of climate change on agriculture in China

This paper assesses the impact of climate change on China's agricultural production at a cross-provincial level using the Ricardian approach, incorporating a multilevel model with farm-level group data. The farm-level group data includes 13379 farm households, across 316 villages, distributed in 31 provinces. The empirical results show that, firstly, the marginal effects and elasticities of net crop revenue per hectare with respect to climate factors indicated that the annual impact of temperature on net crop revenue per hectare was positive, and the effect of increased precipitation was negative when looking at the national totals; secondly, the total impact of simulated climate change scenarios on net crop revenues per hectare at a Chinese national total level, was an increase of between 79 USD per hectare and 207 USD per hectare for the 2050s, and an increase from 140 USD per hectare to 355 USD per hectare for the 2080s. As a result, climate change may create a potential advantage for the development of Chinese agriculture, rather than a risk, especially for agriculture in the provinces of the Northeast, Northwest and North regions. However, the increased precipitation can lead to a loss of net crop revenue per hectare, especially for the provinces of the Southwest, Northwest, North and Northeast regions.

Biomass of mesozooplankton in the western part of the Black Sea in 1997 during the Cooperative Marine Science Program for the Black Sea (CoMSBlack)

The "15BO1997001" dataset is based on samples collected in the spring of 1997. The whole dataset is composed of 66 samples (from 27 stations of National Monitoring Sampling Grid) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. The collected material was analysed using the method of Dimov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 (based on species specific wet weight). Wet weight values were transformed to dry weight using the equation DW=0.16*WW as suggested by Vinogradov & Shushkina, 1987. The collected material was analysed using the method of Dimov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Asen Konsulov using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972 ). The biomass was estimated as wet weight by Petipa, 1959 ussing standard average weight of each species in mg/m3. WW were converted to DW by equation DW=0.16*WW (Vinogradov ME, Sushkina EA, 1987).