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• W4213413702 abstract "Birds are crucial for the functioning of Earth’s ecosystems but bird population declines have been documented worldwide in recent decades. A global assessment of potential causes of population declines is needed. Our goal here was to combine the power of big data and machine learning to identify predictors correlated with bird population declines and to predict population declines for species with unknown population trends on the IUCN Red List. From existing online databases, we gathered detailed species‐level data for 10 964 extant bird species around the world, featuring life history, ecology, distribution, taxonomy and categorical population trend information (i.e. decreasing or not decreasing). For the 10 163 species with known population trends, we split the data into a 75% training set to tune and train a machine‐learning model (Light Gradient Boosting Machine – ‘LightGBM’) and a 25% test set to evaluate the trained model. Our model predicted (i) bird population declines with an ROC AUC score of 0.828, F1 score of 0.748 and average accuracy of 0.747, and (ii) that 47% ( n = 801) of bird species with currently unknown population trends are declining. Correlation analyses suggested that, globally, the top predictor associated with bird population declines was a severely fragmented population, with non‐migratory birds in South American and Southeast Asian tropical and subtropical forests being particularly vulnerable. Despite the lack of long‐term quantitative population trend data for all species worldwide, our study presents big data and machine learning as a useful tool for informing conservation priorities, lending insight, albeit imperfect, into bird population declines on the global scale for the first time." @default.
• W4213413702 created "2022-02-25" @default.
• W4213413702 creator A5022679948 @default.
• W4213413702 creator A5059263187 @default.
• W4213413702 creator A5080058836 @default.
• W4213413702 date "2022-02-23" @default.
• W4213413702 modified "2023-10-16" @default.
• W4213413702 title "Predicting population trends of birds worldwide with big data and machine learning" @default.
• W4213413702 cites W1533083599 @default.
• W4213413702 cites W166408649 @default.
• W4213413702 cites W1690194373 @default.
• W4213413702 cites W1710959950 @default.
• W4213413702 cites W1822956445 @default.
• W4213413702 cites W1932362531 @default.
• W4213413702 cites W1973455929 @default.
• W4213413702 cites W1974540937 @default.
• W4213413702 cites W1977623589 @default.
• W4213413702 cites W1983501589 @default.
• W4213413702 cites W1984239225 @default.
• W4213413702 cites W2002682820 @default.
• W4213413702 cites W2003099502 @default.
• W4213413702 cites W2003232268 @default.
• W4213413702 cites W2004308864 @default.
• W4213413702 cites W2010658250 @default.
• W4213413702 cites W2012310246 @default.
• W4213413702 cites W2029549504 @default.
• W4213413702 cites W2035011659 @default.
• W4213413702 cites W2035898274 @default.
• W4213413702 cites W2037149900 @default.
• W4213413702 cites W2041042028 @default.
• W4213413702 cites W2045093032 @default.
• W4213413702 cites W2052274480 @default.
• W4213413702 cites W2055340966 @default.
• W4213413702 cites W2057732249 @default.
• W4213413702 cites W2060497133 @default.
• W4213413702 cites W2063226628 @default.
• W4213413702 cites W2072441979 @default.
• W4213413702 cites W2075339452 @default.
• W4213413702 cites W2078292792 @default.
• W4213413702 cites W2080384232 @default.
• W4213413702 cites W2085333643 @default.
• W4213413702 cites W2091768902 @default.
• W4213413702 cites W2100135944 @default.
• W4213413702 cites W2108648681 @default.
• W4213413702 cites W2111764341 @default.
• W4213413702 cites W2111863257 @default.
• W4213413702 cites W2112753343 @default.
• W4213413702 cites W2114914918 @default.
• W4213413702 cites W2116889467 @default.
• W4213413702 cites W2130571094 @default.
• W4213413702 cites W2132988311 @default.
• W4213413702 cites W2133356809 @default.
• W4213413702 cites W2140995046 @default.
• W4213413702 cites W2141365420 @default.
• W4213413702 cites W2143029770 @default.
• W4213413702 cites W2144863199 @default.
• W4213413702 cites W2145340043 @default.
• W4213413702 cites W2146096861 @default.
• W4213413702 cites W2152198622 @default.
• W4213413702 cites W2162348455 @default.
• W4213413702 cites W2162579665 @default.
• W4213413702 cites W2163005195 @default.
• W4213413702 cites W2163054910 @default.
• W4213413702 cites W2169286869 @default.
• W4213413702 cites W2170664668 @default.
• W4213413702 cites W2175423925 @default.
• W4213413702 cites W2310483718 @default.
• W4213413702 cites W2547699899 @default.
• W4213413702 cites W2591722381 @default.
• W4213413702 cites W2605420867 @default.
• W4213413702 cites W2619299539 @default.
• W4213413702 cites W2724327356 @default.
• W4213413702 cites W2738705438 @default.
• W4213413702 cites W2748591825 @default.
• W4213413702 cites W2769210209 @default.
• W4213413702 cites W2770745616 @default.
• W4213413702 cites W2789890555 @default.
• W4213413702 cites W2797780449 @default.
• W4213413702 cites W2799437918 @default.
• W4213413702 cites W2810653727 @default.
• W4213413702 cites W2885788938 @default.
• W4213413702 cites W2886499515 @default.
• W4213413702 cites W2894172988 @default.
• W4213413702 cites W2902964238 @default.
• W4213413702 cites W2923655399 @default.
• W4213413702 cites W2926028731 @default.
• W4213413702 cites W2959750635 @default.
• W4213413702 cites W2974449448 @default.
• W4213413702 cites W2983227958 @default.
• W4213413702 cites W2995354239 @default.
• W4213413702 cites W3006345455 @default.
• W4213413702 cites W3010630365 @default.
• W4213413702 cites W3021322626 @default.
• W4213413702 cites W3022177093 @default.
• W4213413702 cites W3038247979 @default.
• W4213413702 cites W3147003967 @default.
• W4213413702 cites W3161796067 @default.
• W4213413702 cites W4206774958 @default.

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