Center for Biodiversity and Conservation, American Museum of Natural History, Central Park West at 79th Street, New York, New York, 10024, USA.
Ecol Appl. 2018 Jun;28(4):967-977. doi: 10.1002/eap.1702. Epub 2018 Apr 26.
Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawaii. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawaii. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the state of Hawaii. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a fine scale relevant to biocultural conservation initiatives.
在持续和预计的气候变化威胁下，太平洋岛屿社区面临着调整文化和生活方式以适应景观变化的挑战。很少有模型可以有效地预测生物文化生计可能受到的影响。在这里，我们研究了环境和人为因素如何影响夏威夷栽培芋头（Colocasia esculenta）实现生态位的生态位模型（ENM）。我们创建并调整了两套 ENM：一套仅使用环境变量，另一套同时使用夏威夷的环境和文化特征。这些模型根据 2070 年政府间气候变化专门委员会（IPCC）的两种代表性浓度途径（RCP）进行了预测。使用平均遗漏率和接收者操作特征曲线（AUC）下的面积来选择和评估模型。我们通过比较使用 Schoener 的 D 统计量预测的芋头图块的百分比与测量的 ENM 重叠来比较最佳模型预测。仅包含环境变量的模型包括 19 个 Worldclim 生物气候变量，以及坡度、海拔、到常年溪流的距离、土壤蒸发和土壤湿度。包含环境变量加人为特征的最佳模型还包括一个道路密度变量（我们假设其为城市化的代理）和一个表示对夏威夷州重要的农业用地的变量。基于遗漏率、AUC 和空间预测的审查，包含人为特征的模型比仅包含环境的模型表现更好。这两个模型在预期未来气候变化下芋头的空间预测也有所不同。我们的结果表明，包含人为特征的 ENM 可以预测哪些地区最适合未来种植栽培物种，以及这些地区在各种气候预测下可能发生的变化。这些预测可能为生物文化保护的优先事项和倡议提供信息。此外，我们还讨论了当传统的 ENM 理论应用于其分布已受到人类干预显著影响的物种时出现的不一致性，特别是在与生物文化保护倡议相关的精细尺度上。
