Variability in multicomponent ecological systems: its behavior, general determinants, and a test of a new framework

我们最近对实验室生态系统、自然水生微观世界和北部湖泊的实验和观测数据进行的理论研究和分析使我们得出这样的观点：任何生态相关变量的时空差异都是完全相关的，因此是可以互换的。这是因为空间变化和时间变化可以定量地联系在一起（新的重要结果）。这一发现开启了一个令人兴奋的前景，即人们可以从空间差异（通常很难获得）中预测时间差异（通常很容易获得），并将其应用于关键问题，如人口、生态系统和景观保护或全球范围内农业生态系统的可变性（以及，例如，粮食生产的可靠性）。拟议的研究旨在测试这种关系的几个方面：(1)我们将在最初的试点工作之外测试其理论基础：我们将使用实验室实验来测试已知环境变化对潜在方程预测能力的影响。(2)我们将测试这种关系所暗示的模式在自然界中是否可检测和重要，以及在什么条件下：我们将通过操纵自然微观世界系统中的连通性和间接的栖息地变异性来实现这一目标。最后，(3)我们将通过进行“概念验证”探索来测试研究结果的重要性：我们将模型应用于原始和改良景观（黄石国家公园及其邻近地区）的卫星数据，以及全球粮食生产和全球农业生态系统属性（按国家划分），如生态条件（例如，降水、破碎、肥料使用）。后两种调查方法应该对景观变化的各个方面提供重要的实际见解，这些方面没有得到系统的调查，但可能对保护和管理以及揭示区域（按大陆）粮食生产的脆弱性（变异性）及其决定因素非常重要。

Our recent theoretical work and analyses of experimental and observational data from laboratory ecosystems, natural aquatic microcosms, and northern lakes led us to the idea that spatial and temporal variances of any ecologically relevant variable are exactly related and thus interchangeable. This is because variation in space and variation in time can be quantitatively linked (new important result). The finding opens an exciting prospect that one could predict temporal variance (usually difficult to obtain) from spatial variance (often available or much easier to obtain) and apply it to crucial problems such as population, ecosystem, and landscape conservation or variability of agroecosystems at a global scale (and, for example, reliability of food production). The proposed research aims at testing several aspects of the relationship: (1) we will test its theoretical foundations beyond the initial pilot work: he we will use laboratory experiments which will test for the effects of known environmental variation on the predictive power of the underlying equation. (2) We will test whether the patterns suggested by the relationship are detectable and important in nature and under what conditions: we will do so by manipulating connectivity and, indirectly, habitat variability in a system of natural microcosms. Finally, (3) we will test the significance of findings by performing 'proof-of-concept' exploration: we will apply the model to satellite data on pristine and modified landscapes (Yellowstone National Park and adjacent area) and to global food production and attributes of global agroecosystem (by country) such as ecological conditions (e.g., precipitation, fragmentation, fertilizer use). The latter two lines of investigation should provide significant practical insights into aspects of landscape change that were not systematically investigated but may prove very important to conservation and management as well as to uncovering vulnerabilities (variability) in regional (by continent) food production and their determinants.