Over the course of a year, vegetation and temperature have strong phenological and seasonal patterns, respectively, and many species have adapted to these patterns. High inter-annual variability in the phenology of vegetation and in the seasonality of temperature pose a threat for biodiversity. However, areas with high spatial variability likely have higher ecological resilience where inter-annual variability is high, because spatial variability indicates presence of a range of resources, microclimatic refugia, and habitat conditions. The integration of inter-annual and spatial variability is thus important for biodiversity conservation. Areas where spatial variability is low and inter-annual variability is high are likely to limit resilience to disturbance. In contrast, areas of high spatial variability may be high priority candidates for protection. Our goal was to develop spatio-temporal remotely sensed indices to identify hotspots of biodiversity conservation concern. We generated indices that capture the inter-annual and spatial variability of vegetation greenness and land surface temperature and integrated them to identify areas of high, medium, and low biodiversity conservation concern. We applied our method in Argentina (2.8 million km²), a country with a wide range of climates and biomes. To generate the inter-annual variability indices, we analyzed MODIS Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) time series from 2001 to 2018, fitted curves to obtain annual phenological and seasonal metrics, and calculated their inter-annual variability. To generate the spatial variability indices, we calculated standard deviation image texture of Landsat 8 EVI and LST. When we integrated our inter-annual and spatial variability indices, areas in the northeast and parts of southern Argentina were the hotspots of highest conservation concern. High inter-annual variability poses a threat in these areas, because spatial variability is low. These are areas where management efforts could be valuable. In contrast, areas in the northwest and central-west are where protection should be strongly considered because the high spatial variability may confer resilience to disturbance, due to the variety of conditions and resources within close proximity. We developed remotely sensed indices to identify hotspots of high and low conservation concern at scales relevant to biodiversity conservation, which can be used to target management actions in order to minimize biodiversity loss.

在一年的时间里，植被和温度分别具有强烈的物候和季节模式，许多物种已经适应了这些模式。植被物候和温度季节性的高年际变化对生物多样性构成威胁。但是，具有高空间变异性的区域可能具有较高的生态适应力，其中年际变异性较高，因为空间变异性表明存在各种资源，小气候避难所和栖息地条件。因此，年际和空间变异性的整合对于保护生物多样性很重要。空间变异性低且年际变异性高的区域很可能会限制抗干扰能力。相比之下，空间变异性大的区域可能是保护的高优先级候选对象。我们的目标是开发时空遥感索引，以识别关注生物多样性的热点地区。我们生成了捕获植被绿色度和土地表面温度的年际和空间变化的指数，并对它们进行了整合，以识别生物多样性保护关注程度高，中和低的区域。我们在阿根廷（280万公里^2个），一个拥有广泛的气候和生物群落的国家。为了生成年际变化指数，我们分析了2001年至2018年的MODIS增强植被指数（EVI）和地表温度（LST）时间序列，拟合了曲线以获取年度物候和季节指标，并计算了它们的年际变化。为了生成空间变异性指数，我们计算了Landsat 8 EVI和LST的标准差图像纹理。当我们整合年际和空间变化指数时，东北和阿根廷南部部分地区是人们最关注的保护热点。年际高变异性在这些地区构成了威胁，因为空间变异性很低。在这些领域中，管理工作可能会很有价值。相比之下，在西北和中西部地区，应该强烈考虑进行保护，因为由于附近条件和资源的多样性，高的空间变异性可能赋予抗干扰能力。我们开发了遥感指数，以与生物多样性保护相关的规模来识别高和低保护关注的热点，这些热点可用于确定管理行动，以最大程度地减少生物多样性的损失。