## 1 Introduction  
### A Brief History of Forest Ecosystem Models  
For millenia, timber harvest for economic, militaristic, and social gain was the primary--if not sole--objective of forestry. This focus changed only slightly in the 18 th century with the emergence of sustained-yield forest management in Leipzig, Germany (then within the Electorate of Saxony, Holy Roman Empire) [1]. For the first time, controlling the effects of management intensity on land productivity over time was given primary consideration. This followed a history of deforestation extending back to the loss of _Cedrus_ forests across the Middle East, as described in the _Epic of Gilgamesh_ in the third millennium BCE [2; 3]. While sustained-yield forest management was designed to maximize timber production indefinitely, under the spurious assumption that sustained yield is possible solely through in situ silvicultural treatments, the concept broadly inspired sustainability science, resilience theory [4], and subsequent work on complex adaptive systems [5]. From its inception, sustainability regarded matters economic, social, and ecological in nature [6]. Yet, economic-focused timber production likely accelerated with increased mechanization in the mid-20 th century. As our understanding of abiotic and biotic forest interactions expanded, the core assumptions of stationarity underpinning sustained-yield management lost support. The importance of fire ecology [7], structural complexity [8], trophic interactions [9], and their relation to climate, soil, and ecosystem functioning was soon uncovered. Research on climate impacts on regeneration [10; 11] further showed that species compositional changes are likely under current climate trajectories, requiring proactive strategies to sustain yields from extant forests. Research along this line inspired the concepts of adaptive migration [12], assisted gene flow [13], and precise gene editing of trees with CRISPR/Cas9 [14]. Ecological forestry or sustainable forest management is now the dominant management paradigm, where the focus is on emulating natural processes of succession, disturbance, and migration [15]. Mirroring changes in management, modeling forest ecosystems also underwent a paradigm shift from focusing on sustained yield to ecological forestry and multiple-use management. This has required a remarkable increase in the size and complexity of forest ecosystem models in order to simulate a suite of new complex processes. Forest models likely began 350 years ago in China with yield tables known as the Lung Ch'uan codes, invented by a women of the [PERSON] family in Suichuan county, Jiangxi [16]. It was not until the 20 th century that the first complex mathematical models of forests emerged. Long restricted to simple models developed with mechanical calculators, digital computers enabled researchers to explicitly model forest dynamics. Following the development of matrix models [17] and empirical growth-and-yield models such as Prognosis [18; 19], a vast array of gap [20], forest landscape [21; 22; 23; 24; 25], and terrestrial biosphere models [26; 27; 28] have been developed. Models of forest ecosystems vary substantially in application, abstraction, and system detail. While some models may be entirely statistical or mechanistic, others combine statistical and systems-theoretic process models in a hybrid modeling approach [29; 30]. Representation of canopy geometry varies from implicit to a single 'big-leaf' and detailed three-dimensional crown and root geometry (e.g., modern gap models such as MAESPA [31] and LES [32]). Models of growth range from simple allometric equations (e.g., growth-and-yield models) to light-use efficiency models [33] and first-principles mechanistic models of photosynthesis [34]. Belowground process models similarly vary in structure, from simple stoichiometric relations to carbon and nitrogen cycling with microbial dynamics to a fully mechanistic representation of energetic and biogeochemical processes based on thermodynamics.