Historically calibrated predictions of butterfly species' range shift using global change as a pseudo-experiment HEATHER M. KHAROUBA,1 ADAM C. ALGAR, AND JEREMY T. KERR2Department of Biology, University of Ottawa, 30 Marie Curie, P.O. Box 450 Station A, Ottawa, Ontario K1N6N5 Canada
全球變遷具有造成大滅絕的潛力。預知物種對於可預測的改變會如何反應使有效保護他們並降低滅絕率的先決條件。物種棲位模型在這類預測中被廣泛應用，然而在長期尺度上的可靠性則具有變化。然而，北半球國家的氣候與土地利用改變為預測未來情形的模型可靠度提供了假性實驗測試，物種分布與環境狀況的歷史資料均可取得。運用最大熵原理，一個重要的模擬技術，我們可以重建橫跨加拿大地區蝴蝶物種的歷史分布模型，然後用此模型模擬出現今物種分布範圍以和實際情形對照，得知其預測的準確度。對大多數的蝴蝶物種而言，我們所預測物種的推估會對已知的氣候變化有反應，與物種反應的觀測值一致(平均自迴歸 R2 ¼ 0.70)。此一致性在來自北方的物種與廣佈種中下降。作者的結果顯示，至少有一部分的物種會隨著氣候變遷而在廣大的地理區中改變分布範圍，且其改變可以藉由棲位模型被準確預測。然而，作者也發現儘管在模型運算時有很高的空間模型準確度、某些物種在此模型中隨著時間預測仍是失敗的，突現出在基本經營管理決策上所需應是物種的組成、而非單一物種。
Abstract.
Global changes have the potential to cause a mass extinction. Predicting how species will respond to anticipated changes is a necessary prerequisite to effectively conserving them and reducing extinction rates. Species niche models are widely used for such predictions, but their reliability over long time periods is known to vary. However, climate and land use changes in northern countries provide a pseudo-experiment to test model reliability for predicting future conditions, provided historical data on both species distributions and environmental conditions are available. Using maximum entropy, a prominent modeling technique, we constructed historical models of butterfly species’ ranges across Canada and then ran the models forward to present-day to test how well they predicted the current ranges of species. For the majority of species, projections of how we predicted species would respond to known climate changes corresponded with species’ observed responses (mean autoregressive R2 ¼ 0.70). This correspondence declined for northerly and very widely distributed species. Our results demonstrate that at least some species are tracking shifting climatic conditions across very large geographic areas and that these shifts can be predicted accurately using niche models. We also found, however, that models for some species fail when projected through time despite high spatial model accuracies during model training, highlighting the need to base management decisions on species assemblages, not individual species.
Key words: butterflies; Canada; climate change; land use change; macroecology; maximum entropy;range shifts; space-for-time substitution; species assemblages; species niche models.
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