Specialty Grand Challenge Article Grand Challenges in Population Dynamics the Multidimensionality of Population Dynamics the Spatial Dimension of Population Dynamics Theoretical Models and Empirical Studies Ecology and Evolution
Specialty Grand Challenge Article Grand Challenges in Population Dynamics the Multidimensionality of Population Dynamics the Spatial Dimension of Population Dynamics Theoretical Models and Empirical Studies Ecology and Evolution
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专业大挑战文章 人口动态的重大挑战 人口动态的多维性 人口动态的空间维度 理论模型和实证研究 生态学与进化
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通讯作者：
Stefano Allesina
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作者：
D. Oro;Stefano Allesina
大多数多细胞生物（无论是后生动物还是植物）在连续的空间分布中分组，在那里它们共享基因和共同的环境特征。这些聚集体--其规模在空间和时间上波动--被称为种群。尽管种群动态在历史上吸引了许多科学家的兴趣，但我们仍然远远没有理解自然生态系统中种群如何以及为什么波动。主要原因是，种群是复杂的系统，具有不可能通过其部分的总和来确定的涌现特性。人口动态的组成部分，包括进程和模式，有许多方面，涉及多个层面。在这里，我将强调其中的一些--当然，以一种主观的方式。一个种群的大小综合了许多因素，从个体到生态系统的水平，如行为，生理，宿主-寄生虫和捕食者-猎物的相互作用，疾病，营养等。这些过程还与物理驱动器（例如，气候）影响基本的健身组成部分：生存，繁殖和传播。在大多数情况下，这些主题都是以简单的方式独立研究的;例如，可以从两个竞争物种之间的成对相互作用中理解种群的动态吗？因此，由于遗传、生物和物理相互作用的综合复杂性导致了种群动态，因此，解开影响种群波动的众多因素中每一个因素的影响仍然是一个巨大的挑战。挑战甚至更大，因为大多数研究处理的是平均物种水平值，而个体变异以及这种变异如何转化为种群动态还远未得到很好的理解（Bjørnstad等人，1994年）。直接与健身组件一起工作，以及它们的方差，同时随着时间的推移对种群规模进行稳健的估计，可能会部分克服这些挑战，但挑战随后转移到耗时的现场监测工作上。微观层面的实验是一种有效的替代方法，主要用于测试特定的假设，但它们并没有解决以整体方式理解人口波动的挑战，因为实验代表了现实的简化和改变版本。与种群随时间的波动相比，种群动态的空间尺度在历史上一直被忽视，因为它会使研究变得非常复杂。收集具有空间结构的人口数据要求很高，但研究空间尺度所固有的人口进程至关重要，因为世界在空间上是不可避免的异质性（Tilman和Kareiva，1997年）。对简单捕食者-被捕食者系统的开创性研究已经强调，一个不完整的、细分的环境是维持共存的必要条件。
Most multicellular organisms (either metazoan or plants) are grouped in contiguous spatial distributions, where they share genes and common environmental features. These aggregations—the size of which fluctuates in space and time— are called populations. Despite the fact that population dynamics has historically attracted the interest of many scientists, we are still far from understanding how and why populations fluctuate in natural ecosystems. The main reason is that populations are complex systems, with emergent properties that are impossible to determine by the sum of their parts. The components of population dynamics, including processes and patterns , are numerous and have multifaceted dimensions. Here, I will highlight some of them—unavoidably, in a subjective manner. The size of a population integrates many factors, from the individual to the ecosystem levels, such as behavior, physiology, host-parasite and predator-prey interactions , diseases, nutrients, among others. Those processes also interact with physical drivers (e.g., climate) to influencing basic fitness components: survival, reproduction and dispersal. In most cases, these topics have been studied independently and in a simple manner; for instance, can the dynamics of a population be understood from pairwise interactions between two competing species? Thus, disentangling the influence of each of the numerous factors influencing population fluctuations remains a great challenge , due to the complexity of integrating the genetic, biotic and physical interactions giving raise to population dynamics. The challenge is even greater because most studies deal with mean-species-level-values, whereas individual variation and how this variance translates into population dynamics is far from being well-understood (Bjørnstad et al., 1994). Working directly with fitness components, together with their variance, and simultaneously having robust estimates of population size over time may partially overcome those challenges, but the challenge is then shifted to time-consuming field monitoring work. Experiments at the microcosm-level are a valid alternative mainly to test specific hypotheses, but they do not solve the challenge of understanding population fluctuations in a holistic manner, given that experiments represent a simplified and altered version of reality. Compared to population fluctuations over time, the spatial scale of population dynamics has historically been ignored because it can greatly complicate research. Collecting spatially-structured population data is highly demanding, but studying population processes that are inherent to the spatial scale are crucial, because the world is unavoidably spatially heterogeneous (Tilman and Kareiva, 1997). Pioneering studies on simple predator-prey systems already stressed that a patchy, subdivided environment is necessary to maintain coexistence …