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\u6587\u7ae0\u6765\u6e90\u4e8e\u4e92\u8054\u7f51:AI\u5982\u4f55\u91cd\u5851\u5168\u7403\u751f\u7269\u591a\u6837\u6027\u7814\u7a76\uff0c\u9ea6\u5409\u5c14\u5927\u5b66\u6700\u65b0\u7efc\u8ff0<\/a><\/p>\n

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\u7f16\u8f91 | 2049<\/p>\n

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\u76ee\u524d\u5168\u7403\u7ea6\u6709 870 \u4e07\u79cd\u771f\u6838\u751f\u7269\uff0c\u4f46\u4ec5\u6709\u7ea6 200 \u4e07\u79cd\u5f97\u5230\u6b63\u5f0f\u63cf\u8ff0\u3002\u5373\u4fbf\u662f\u5df2\u77e5\u7269\u79cd\uff0c\u6211\u4eec\u5bf9\u5176\u5206\u5e03\u3001\u79cd\u7fa4\u52a8\u6001\u3001\u751f\u6001\u529f\u80fd\u7b49\u8ba4\u77e5\u4e5f\u5b58\u5728\u5de8\u5927\u7a7a\u767d\u3002<\/p>\n

\u6700\u8fd1\uff0c\u7531\u9ea6\u5409\u5c14\u5927\u5b66\uff08McGill University\uff09\u548c\u5339\u5179\u5821\u5927\u5b66\uff08University of Pittsburgh\uff09\u7275\u5934\uff0c\u8054\u5408\u9ebb\u7701\u7406\u5de5\uff08MIT\uff09\u7b49\u591a\u5bb6\u7814\u7a76\u673a\u6784\u7684\u56e2\u961f\u53d1\u8868\u4e86\u4e00\u7bc7\u7efc\u8ff0\uff0c\u7cfb\u7edf\u63a2\u8ba8\u4e86\u4eba\u5de5\u667a\u80fd\uff08AI\uff09\u6280\u672f\u5982\u4f55\u5e2e\u52a9\u514b\u670d\u8fd9\u4e9b\u8ba4\u77e5\u969c\u788d\u3002<\/p>\n

\u8bba\u6587\u4e0d\u4ec5\u7cfb\u7edf\u603b\u7ed3\u4e86 AI \u5728\u751f\u7269\u591a\u6837\u6027\u7814\u7a76\u4e2d\u7684\u73b0\u72b6\uff0c\u8fd8\u4e3a\u8de8\u5b66\u79d1\u5408\u4f5c\u6307\u660e\u4e86\u65b9\u5411\uff0c\u5bf9\u63a8\u52a8\u751f\u7269\u591a\u6837\u6027\u79d1\u5b66\u53d1\u5c55\u5177\u6709\u91cd\u8981\u7684\u6307\u5bfc\u610f\u4e49\u3002<\/p>\n

\u8be5\u7814\u7a76\u4ee5\u300cHarnessing artificial intelligence to fill global shortpositions in biodiversity knowledge<\/em>\u300d\u4e3a\u9898\uff0c\u4e8e 2025 \u5e74 2 \u6708 20 \u65e5\u53d1\u8868\u5728\u300aNature Reviews Biodiversity<\/em>\u300b\u3002<\/p>\n

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\u8bba\u6587\u94fe\u63a5\uff1ahttps:\/\/www.nature.com\/articles\/s41467-025-56733-w<\/em><\/p>\n

\u751f\u7269\u591a\u6837\u6027\u8ba4\u77e5\u77ed\u677f<\/strong><\/p>\n

\u751f\u7269\u591a\u6837\u6027\u76d1\u6d4b\u4e0e\u4fdd\u62a4\u957f\u671f\u53d7\u9650\u4e8e\u6570\u636e\u83b7\u53d6\u4e0e\u5206\u6790\u80fd\u529b\uff0c\u81ea 1980 \u5e74\u4ee3\u8d77\uff0c\u751f\u6001\u5b66\u754c\u9010\u6b65\u786e\u7acb\u56f0\u6270\u5927\u89c4\u6a21\u751f\u7269\u591a\u6837\u6027\u77e5\u8bc6\u7684\u4e03\u5927\u4e0d\u8db3\uff1a<\/p>\n

Linnaean\uff08\u5206\u7c7b\u63cf\u8ff0\uff09\u3001Prestonian\uff08\u4e30\u5ea6\u7684\u4f30\u8ba1\u548c\u6a21\u5f0f\uff09\u3001Wallacean\uff08\u751f\u7269\u5730\u7406\u7269\u79cd\u5206\u5e03\uff09\u3001Hutchinsonian\uff08\u975e\u751f\u7269\u8010\u53d7\u6027\u548c\u57fa\u672c\u751f\u6001\u4f4d\uff09\u3001Raunkiaeran\uff08\u529f\u80fd\u6027\u58ee\u53d8\u5f02\uff09\u3001Darwinian\uff08\u8fdb\u5316\u5173\u7cfb\uff09 \u548c Eltonian shortfalls\uff08\u7269\u79cd\u76f8\u4e92\u4f5c\u7528\uff09\u3002<\/p>\n

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\u56fe\u793a\uff1a\u751f\u7269\u591a\u6837\u6027\u77e5\u8bc6\u7684\u4e03\u4e2a\u4e0d\u8db3\u3002\uff08\u6765\u6e90\uff1a\u8bba\u6587\uff09<\/p>\n

\u8fd9\u4e9b\u7cfb\u7edf\u6027\u7f3a\u9677\u4e25\u91cd\u5236\u7ea6\u7740\u300a\u6606\u660e-\u8499\u7279\u5229\u5c14\u5168\u7403\u751f\u7269\u591a\u6837\u6027\u6846\u67b6\u300b\uff08GBF\uff092030 \u5e74\u76ee\u6807\u7684\u5b9e\u73b0\u3002<\/p>\n

\u76f8\u5173\u94fe\u63a5\uff1ahttps:\/\/www.cbd.int\/gbf<\/p>\n

\u4f20\u7edf\u76d1\u6d4b\u624b\u6bb5\u5728\u7269\u79cd\u5206\u5e03\u8ffd\u8e2a\uff08Wallacean \u7f3a\u53e3\uff09\u548c\u79cd\u7fa4\u52a8\u6001\u76d1\u6d4b\uff08Prestonian \u7f3a\u53e3\uff09\u65b9\u9762\u5b58\u5728\u65f6\u7a7a\u5206\u8fa8\u7387\u4f4e\u3001\u8986\u76d6\u8303\u56f4\u6709\u9650\u7b49\u7f3a\u9677\uff0c\u800c\u65b0\u5174\u4f20\u611f\u5668\u7f51\u7edc\u4ea7\u751f\u7684\u591a\u6a21\u6001\u6570\u636e\uff08\u56fe\u50cf\u3001\u97f3\u9891\u3001DNA \u7b49\uff09\u4e9f\u9700\u65b0\u578b\u5206\u6790\u65b9\u6cd5\u3002<\/p>\n

AI \u6280\u672f\u7279\u522b\u662f\u6df1\u5ea6\u5b66\u4e60\uff08Deep Learning\uff09\u5728\u8ba1\u7b97\u673a\u89c6\u89c9\uff08Computer Vision\uff09\u548c\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08Natural Language Processing\uff0cNLP\uff09\u9886\u57df\u7684\u7a81\u7834\uff0c\u4e3a\u6574\u5408\u5f02\u6784\u6570\u636e\u3001\u63d0\u5347\u751f\u6001\u6a21\u578b\u9884\u6d4b\u80fd\u529b\u63d0\u4f9b\u4e86\u65b0\u8303\u5f0f\u3002<\/p>\n

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\u56fe\u793a\uff1a\u4eba\u5de5\u667a\u80fd\u5728\u586b\u8865\u751f\u7269\u591a\u6837\u6027\u77e5\u8bc6\u7a7a\u767d\u548c\u4e0b\u6e38\u5e94\u7528\u65b9\u9762\u7684\u6f5c\u5728\u4f5c\u7528\u3002\uff08\u6765\u6e90\uff1a\u8bba\u6587\uff09<\/p>\n

\u6280\u672f\u8def\u7ebf\u6f14\u8fdb\u4e0e\u6838\u5fc3\u6311\u6218<\/strong><\/p>\n

\u5f53\u524d\u4eba\u5de5\u667a\u80fd\uff08AI\uff09\u5728\u751f\u7269\u591a\u6837\u6027\u7814\u7a76\u4e2d\u7684\u6280\u672f\u8fdb\u5c55\u4e3b\u8981\u4f53\u73b0\u5728\u4e09\u4e2a\u65b9\u9762\uff1a\u57fa\u4e8e\u4f20\u611f\u5668\u7f51\u7edc\u7684\u81ea\u52a8\u5316\u76d1\u6d4b\u7cfb\u7edf\uff08\u5982\u65e0\u4eba\u673a\u4e0e\u58f0\u5b66\u8bb0\u5f55\u4eea\uff09\u3001\u591a\u6a21\u6001\u6570\u636e\u878d\u5408\u5efa\u6a21\uff08\u6574\u5408\u56fe\u50cf\u3001DNA\u4e0e\u9065\u611f\u6570\u636e\uff09\uff0c\u4ee5\u53ca\u751f\u7269\u6027\u72b6\u91cf\u5316\u5206\u6790\uff08\u5982\u5f62\u6001\u4e0e\u529f\u80fd\u6027\u72b6\u63d0\u53d6\uff09\u3002<\/p>\n

\u5728\u7269\u79cd\u8bc6\u522b\u9886\u57df\uff0c\u89c6\u89c9\u8bed\u8a00\u6a21\u578b\uff08Vision-Language Models\uff0cVLMs\uff09\u901a\u8fc7\u8de8\u6a21\u6001\u5bf9\u6bd4\u5b66\u4e60\uff0c\u6210\u529f\u5b9e\u73b0\u8de8\u7269\u79cd\u56fe\u50cf\u7279\u5f81\u63d0\u53d6\uff0c\u5c55\u73b0\u51fa\u5728\u5927\u89c4\u6a21\u5206\u7c7b\u4efb\u52a1\u4e2d\u7684\u6f5c\u529b\u3002<\/p>\n

\u8054\u5408\u7269\u79cd\u5206\u5e03\u6a21\u578b\uff08Joint Species Distribution Models\uff0cJSDMs\uff09\u5219\u7a81\u7834\u4f20\u7edf\u5355\u7269\u79cd\u5efa\u6a21\u5c40\u9650\uff0c\u6574\u5408\u536b\u661f\u9065\u611f\u3001\u73af\u5883 DNA\uff08eDNA\uff09\u548c\u516c\u6c11\u79d1\u5b66\u89c2\u6d4b\u6570\u636e\uff0c\u663e\u8457\u63d0\u5347\u4e86\u7269\u79cd\u5206\u5e03\u9884\u6d4b\u7684\u7a7a\u95f4\u7cbe\u5ea6\u3002<\/p>\n

\u7136\u800c\u6280\u672f\u6f14\u8fdb\u9762\u4e34\u4e09\u91cd\u6838\u5fc3\u6311\u6218\uff1a<\/p>\n

1\u3001\u957f\u5c3e\u5206\u5e03\u56f0\u5883<\/strong>\u2014\u2014\u7a00\u6709\u7269\u79cd\u5728\u8bad\u7ec3\u6570\u636e\u4e2d\u5360\u6bd4\u4e0d\u8db3\uff0c\u5bfc\u81f4\u6a21\u578b\u5728\u5b9e\u9a8c\u5ba4\u4e0e\u91ce\u5916\u573a\u666f\u7684\u8bc6\u522b\u6027\u80fd\u5dee\u5f02\u663e\u8457\uff1b<\/p>\n

2\u3001\u5730\u7406\u6cdb\u5316\u74f6\u9888<\/strong>\u2014\u2014\u6a21\u578b\u5728\u4e0d\u540c\u5730\u7406\u573a\u666f\u4e0b\u7684\u6027\u80fd\u8870\u51cf\u663e\u8457\uff1b<\/p>\n

3\u3001\u751f\u6001\u8bed\u4e49\u9694\u9602<\/strong>\u2014\u2014\u73b0\u6709\u673a\u5668\u5b66\u4e60\u6846\u67b6\u96be\u4ee5\u7f16\u7801\u79cd\u7fa4\u52a8\u6001\u65b9\u7a0b\u7b49\u751f\u6001\u8fc7\u7a0b\u673a\u5236\uff0c\u9650\u5236\u4e86\u5176\u5728\u751f\u6001\u7814\u7a76\u4e2d\u7684\u5e94\u7528\u3002<\/p>\n

\u5173\u952e\u6280\u672f\u7a81\u7834\u4e0e\u9a8c\u8bc1<\/strong><\/p>\n

\u7a81\u7834\u6027\u8fdb\u5c55\u4f53\u73b0\u5728\u591a\u6a21\u6001\u878d\u5408\u4e0e\u77e5\u8bc6\u5f15\u5bfc\u5b66\u4e60\u9886\u57df\u3002<\/p>\n

1\u3001\u591a\u6a21\u6001\u6570\u636e\u878d\u5408\u2014\u2014\u57fa\u4e8e\u5bf9\u6bd4\u5b66\u4e60\u6846\u67b6\u7684\u591a\u6a21\u6001\u6a21\u578b\uff0c\u901a\u8fc7\u8054\u5408\u7f16\u7801 DNA \u6761\u5f62\u7801\u4e0e\u663e\u5fae\u56fe\u50cf\u6570\u636e\uff0c\u663e\u8457\u63d0\u5347\u4e86\u7269\u79cd\u5206\u7c7b\u7684\u51c6\u786e\u6027\u3002\u8fd9\u79cd\u65b9\u6cd5\u5728\u751f\u7269\u591a\u6837\u6027\u7814\u7a76\u4e2d\u5c55\u73b0\u4e86\u8de8\u6a21\u6001\u8868\u5f81\u5bf9\u9f50\u7684\u6f5c\u529b\uff0c\u7279\u522b\u662f\u5728\u5904\u7406\u590d\u6742\u6570\u636e\u96c6\u65f6\u8868\u73b0\u51fa\u8272\u3002<\/p>\n

2\u3001\u751f\u6001\u7f51\u7edc\u5efa\u6a21\u2014\u2014<\/strong>\u5728 Eltonian\uff08\u7269\u79cd\u76f8\u4e92\u4f5c\u7528\uff09\u7814\u7a76\u4e2d\uff0c\u56fe\u795e\u7ecf\u7f51\u7edc\uff08Graph Neural Networks, GNNs\uff09\u88ab\u7528\u4e8e\u6784\u5efa\u751f\u6001\u7f51\u7edc\u6a21\u578b\uff0c\u80fd\u591f\u66f4\u51c6\u786e\u5730\u9884\u6d4b\u7269\u79cd\u76f8\u4e92\u4f5c\u7528\u5173\u7cfb\u3002\u76f8\u6bd4\u4f20\u7edf\u65b9\u6cd5\uff0cGNNs \u5728\u6355\u6349\u590d\u6742\u751f\u6001\u7f51\u7edc\u7ed3\u6784\u65b9\u9762\u8868\u73b0\u51fa\u66f4\u5f3a\u7684\u80fd\u529b\u3002<\/strong><\/p>\n

3\u3001\u79cd\u7fa4\u52a8\u6001\u9884\u6d4b\u2014\u2014<\/strong>\u6574\u5408\u673a\u7406\u77e5\u8bc6\uff08\u5982 Leslie \u77e9\u9635\uff09\u4e0e\u6570\u636e\u9a71\u52a8\u6a21\u578b\uff08\u5982LSTM\uff09\u7684\u6df7\u5408\u65b9\u6cd5\uff0c\u5728\u79cd\u7fa4\u52a8\u6001\u9884\u6d4b\u4e2d\u8868\u73b0\u51fa\u66f4\u9ad8\u7684\u7a33\u5b9a\u6027\u548c\u51c6\u786e\u6027\u3002\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u6a21\u578b\u7684\u9884\u6d4b\u7cbe\u5ea6\uff0c\u8fd8\u589e\u5f3a\u4e86\u6a21\u578b\u5728\u957f\u65f6\u5e8f\u9884\u6d4b\u4e2d\u7684\u53ef\u9760\u6027\u3002<\/strong><\/p>\n

\u5f00\u653e\u95ee\u9898\u4e0e\u672a\u6765\u7a81\u7834\u65b9\u5411<\/strong><\/p>\n

\u57fa\u7840\u6a21\u578b\uff08Foundation Models\uff09\u7684\u751f\u6001\u9002\u914d\u6027\u6210\u4e3a\u653b\u575a\u91cd\u70b9\uff1a<\/p>\n

1\u3001\u673a\u7406-\u6570\u636e\u878d\u5408\u67b6\u6784<\/strong>\u2014\u2014\u5c06 Lotka-Volterra \u65b9\u7a0b\u7b49\u751f\u6001\u52a8\u529b\u5b66\u6a21\u578b\u5d4c\u5165\u9012\u5f52\u795e\u7ecf\u7f51\u7edc\uff08Recurrent Neural Networks, RNNs\uff09\uff0c\u5728\u751f\u6001\u7cfb\u7edf\u6a21\u62df\u4e2d\u5c55\u73b0\u51fa\u6f5c\u529b\uff0c\u663e\u8457\u63d0\u5347\u4e86\u957f\u671f\u9884\u6d4b\u7684\u7a33\u5b9a\u6027\u548c\u51c6\u786e\u6027\u3002<\/p>\n

2\u3001\u5c0f\u6837\u672c\u5b66\u4e60\u8303\u5f0f<\/strong>\u2014\u2014\u57fa\u4e8e\u5143\u5b66\u4e60\uff08Meta-learning\uff09\u7684 Few-shot \u5206\u7c7b\u5668\u5728\u5c0f\u6837\u672c\u751f\u7269\u591a\u6837\u6027\u76d1\u6d4b\u4e2d\u8868\u73b0\u51fa\u8272\uff0c\u4e3a\u7a00\u6709\u7269\u79cd\u7684\u8de8\u533a\u57df\u8bc6\u522b\u63d0\u4f9b\u4e86\u6709\u6548\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n

3\u3001\u8fb9\u7f18\u8ba1\u7b97\u90e8\u7f72<\/strong>\u2014\u2014\u8f7b\u91cf\u5316\u6a21\u578b\u5728\u667a\u80fd\u76f8\u673a\u9677\u9631\u7b49\u8fb9\u7f18\u8ba1\u7b97\u8bbe\u5907\u4e2d\u964d\u4f4e\u4e86\u529f\u8017\uff0c\u4f46\u5728\u70ed\u5e26\u6f6e\u6e7f\u7b49\u6781\u7aef\u73af\u5883\u4e0b\u7684\u8bbe\u5907\u9002\u5e94\u6027\u4ecd\u9700\u8fdb\u4e00\u6b65\u4f18\u5316\u3002<\/p>\n

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