A bird's view of new conservation hotspots in China

Hu, Ruocheng; Cheng, Wu; Gu, Yiyun; Wang, Hao; Gu, Ling; Shi, Xiangying; Zhong, Jia; Wei, Ming; He, Fei; Lü, Zhi

doi:10.1016/j.biocon.2017.03.033

Cited by 44 publications

(48 citation statements)

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“…To avoid overfitting and high -variability predictions, we used two criteria: 1) bird species with fewer than five independent localities were excluded [ 44 ]; 2) if localities are highly concentrated for a species (the distance between any two localities is less than one arc-minute), the excess localities were randomly removed (presence thinning). This data cleaning process has been proven to effectively match the results of the MaxEnt model and improve model performance [ 36 , 39 , 45 – 47 ]. Finally, we used 161,004 independent localities to create modeled distribution range maps for 1,042 bird species (for details, see S1 Table ).…”

Section: Methodsmentioning

confidence: 99%

“…In China, where historical occurrence data are scarce and difficult to digitize [ 36 ], citizen science methods such as birdwatching have provided much more occurrence data than scientific papers, including for threatened and rare species [ 37 ]. These citizen science datasets have been widely and independently used in national-scale studies of China to explain issues such as the effects of climate change on biogeography and conservation planning for both individual species and multiple species [ 23 , 36 , 38 , 39 ]. Although such data may show observation bias, reporting bias, and geographic bias due to lack of a standardized field protocol [ 40 ], these useful large-scale and full-taxon data can be used with data cleaning and correction [ 41 ].…”

Section: Introductionmentioning

confidence: 99%

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Shifts in bird ranges and conservation priorities in China under climate change

Gu²,

Luo

et al. 2020

PLoS ONE

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Climate change is one of the most significant causes of species range shift and extinction. Based on a citizen science dataset of birds in China, the Bird Report, we developed a highresolution map of bird species richness in China, and simulated the range shifts and area changes of the 1,042 birds through the year 2070 using three different General Circulation Models and two different Representative Concentration Pathways (RCPs, including RCP 2.6 and RCP 8.5). It was found that 241-244 (under different scenarios) bird species would lose a portion of their distribution ranges; and that most species in China would move to either higher elevations or northward. The other 798-801 species would experience range expansion. Compared to resident species (n = 516), migratory birds (n = 526) may undergo more limited range expansion but a longer range shift distance on average. The species diversity of birds will considerably increase in areas higher than 1,500 m in elevation under both RCPs. Conservation priorities with higher species richness were also identified using the Zonation model. The existing national nature reserves are not sufficient for protecting important bird habitats, especially after range shifts. Significant gaps in protected areas were observed in the northern Xinjiang, southern Tibet, Greater Khingan, Sanjiang Plain, Songnen Plain, northern Bohai Rim, and southeastern coastline areas. Many of these areas are characterized by high human populations and intensive development, and establishing sizable protected areas has become difficult. Inclusive conservation mechanisms that include restoring habitats in urban parks and sharing habitats in farmland areas, may be a feasible solution.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Shifts in bird ranges and conservation priorities in China under climate change

Gu²,

Luo

et al. 2020

PLoS ONE

Self Cite

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“…The VS-2 & VS-3 represent scenarios where bioclimatic variables are excluded to conserve the finer grain size of BPV. All input data layers were re-sampled using nearest neighbour (for discrete variables) and bilinear interpolation (for continuous variables) resampling techniques 35 – 37 . Collinearity among predictor variables negatively impacts the model due to the substantial amount of information shared between collinear variables.…”

Section: Methodsmentioning

confidence: 99%

Species distribution model transferability and model grain size – finer may not always be better

Manzoor

Griffiths

Lukáč

2018

Sci Rep

110

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Species distribution models have been used to predict the distribution of invasive species for conservation planning. Understanding spatial transferability of niche predictions is critical to promote species-habitat conservation and forecasting areas vulnerable to invasion. Grain size of predictor variables is an important factor affecting the accuracy and transferability of species distribution models. Choice of grain size is often dependent on the type of predictor variables used and the selection of predictors sometimes rely on data availability. This study employed the MAXENT species distribution model to investigate the effect of the grain size on model transferability for an invasive plant species. We modelled the distribution of Rhododendron ponticum in Wales, U.K. and tested model performance and transferability by varying grain size (50 m, 300 m, and 1 km). MAXENT-based models are sensitive to grain size and selection of variables. We found that over-reliance on the commonly used bioclimatic variables may lead to less accurate models as it often compromises the finer grain size of biophysical variables which may be more important determinants of species distribution at small spatial scales. Model accuracy is likely to increase with decreasing grain size. However, successful model transferability may require optimization of model grain size.

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“…Data to assess biodiversity distribution in China's farmlands is overall very limited. However, blooming citizen science approaches on bird species resulted in the most comprehensive nationwide avian database with fineresolution and up-to-date information on species occurrences collectively compiled by over 7,000 bird watchers 11 . Although abundance data remain insufficient in the citizen science database, regional study in Europe has reported congruent trends of avian richness and abundance influenced by different farmland management regimes 12 .…”

Section: High Biodiversity In China's Farmlandsmentioning

confidence: 99%