Planning for the extraction of aggregates is typically dealt with at a case to case basis, without assessing environmental impacts strategically. In this study we assess the impact of sand mining in Poyang Lake, where dredging began in 2001 after sand mining in the Yangtze River had been banned. In April 2008 concern over the impact on the biodiversity led to a ban on sand mining in Poyang Lake until further plans could be developed. Planning will require consideration of both sand extraction in relation to available sediment resources and also environmental impacts within the context of future demand for sand in the lower Yangtze Valley. We used pairs of near-infrared (NIR) Aster satellite imagery to estimate the number of vessels leaving the lake. Based on this we calculated a rate of sand extraction of 236 million m 3 year -1 in [2005][2006]. This corresponds to 9% of the total Chinese demand for sand. It qualifies Poyang Lake as probably the largest sand mining operation in the world. It also indicates that sand extraction currently dominates the sediment balance of the lower Yangtze River. A positive relation between demand for sand and GDP, revealed by historic data from the USA, suggests that the current per capita demand for sand in China might increase in the near future from 2 to 4 m 3 year -1 . We review various environmental impacts and question whether it will be possible to preserve the rich biodiversity of the lake, while continuing at the same time satisfying the increasing Chinese demand for sand. Finally we review alternative options for sand mining, in order to relieve the pressure from the Poyang Lake ecosystem.

SummaryFollowing an abnormal flood in 2010 at China’s Poyang Lake, we observed wintering Siberian Cranes Leucogeranus leucogeranus switch from foraging in the shallow-water wetlands they typically use to grassland habitats. These previously undocumented habitat selection patterns raised questions whether differences in crane behaviour such as foraging success existed between the two habitats and how those differences might affect this critically endangered species. Over two winters, we used the density of customary food items (tubers of Vallisneria spp.) obtained from long-term monitoring efforts, Siberian Cranes flock behaviours, individual foraging success and estimated total flock foraging effort across both habitats. Novel foraging patterns by Siberian Cranes were associated with low densities of Vallisneria tubers across multiple sub-lakes within Poyang Lake National Nature Reserve (PLNR). Foraging success was higher in grasslands than in wetlands in winter 2010–2011, but higher in wetlands following a recovery of Vallisneria in 2011–2012. Subsequent to upland foraging during the winter of 2010–2011, we observed lower juvenile to adult ratio of Siberian Cranes at a fall migratory stopover location in north-eastern China despite indications of average environmental conditions in the nesting areas from 2010 to 2012. While grasslands adjacent to shallow-water habitats may be important refugia for wintering Siberian Cranes when Vallisneria is absent or inaccessible, and should be included in protected areas, multi-year dependence on grasslands for foraging could negatively impact population levels. Eliminating crab farming in protected areas and extending protection to shallow water areas sheltered from flooding by dykes could also help secure high quality foraging habitat under a variety of hydrological regimes. Novel foraging patterns by wintering Siberian Cranes represent a new challenge to the conservation efforts for this species that focus on shallow-water wetlands, and may be indicative of broader changes within Poyang’s ecosystem.

Poyang Lake is a very important wintering place for cranes in China and East Asia. Two crane surveys were conducted at Poyang Lake during the 2011/2012 winter, the first on 18-19 December 2011 and the second on 18-19 February 2012. The survey covered the entire Poyang Lake basin, as well as two main lakes in Jiujiang (Saicheng Hu and Chi Hu), i.e., a total of 85 sub-lakes were surveyed. Both surveys recorded four species of cranes. The first survey on 18-19 December 2011 recorded 4577 Siberian Cranes (Grus leucogeranus), mostly in Bang Hu, Sha Hu and Dahu Chi, 302 Hooded Cranes (G. monacha), 885 White-naped Cranes (G. vipio) and 8408 Eurasian Cranes (G. grus), for the most part in the center of the lake basin. The second survey on 18-19 February 2012 recorded 3335 Siberian Cranes (mostly in Poyang Lake National Nature Reserve (PLNR) and its surrounding areas), 110 Hooded Cranes (largely in PLNR and its surrounding areas), 283 White-naped Cranes (86% in Bang Hu) and 2205 Eurasian Cranes (particularly in Duchang and Nanjishan NNR). The number of Siberian Cranes enumerated in December was 1000 more than the second count in February 2012. It is not possible to rule out double counting due to the close proximity of the main sites of the Siberian Cranes. During winters from 1998 to 2009, the average of the highest counts each winter was 3091, ranging from 2345 in 1996 to 4004 in 2002. By comparison with counts taken at other times, we therefore estimate a wintering population of Siberian Cranes of ~3800-4000 at Poyang Lake. Additional evidence will be needed to raise the world population estimate. Our more recent surveys indicate a continuing decline in the number of White-naped Cranes and an increase in Eurasian Cranes.

Poyang Lake, the largest freshwater wetland in China, provides critical habitat for wintering waterbirds from the East Asian Flyway; however, landscape drivers of non-uniform bird diversity and abundance are not yet well understood. Using a winter 2006 waterbird survey, we examined the relationships among metrics of bird community diversity and abundance and landscape characteristics of 51 wetland sub-lakes derived by an object-based classification of Landsat satellite data. Relative importance of predictors and their sets was assessed using information-theoretic model selection and the Akaike Information Criterion. Ordinary least squares regression models were diagnosed and corrected for spatial autocorrelation using spatial autoregressive lag and error models. The strongest and most consistent landscape predictors included Normalized Difference Vegetation Index for mudflat (negative effect) and emergent grassland (positive effect), total sub-lake area (positive effect), and proportion of submerged vegetation (negative effect). Significant spatial autocorrelation in linear regression was associated with local clustering of response and predictor variables, and should be further explored for selection of wetland sampling units and management of protected areas. Overall, results corroborate the utility of remote sensing to elucidate potential indicators of waterbird diversity that complement logistically challenging ground observations and offer new hypotheses on factors underlying community distributions.