{'fraction_non_alphanumeric': 0.022664835164835164, 'fraction_numerical': 0.0, 'mean_word_length': 5.985611510791367, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Global and regional modelling of Arctic–boreal vegetation distribution and its sensitivity to altered forcing

Understanding the distribution and function of Arctic and boreal ecosystems under current conditions and their vulnerability to altered forcing is crucial to our assessment of future global environmental change. Such efforts can be facilitated by the development and application of ecological models that simulate realistic patterns of vegetation change at high latitudes. This paper reviews three classes of ecological models that have been implemented to extrapolate vegetation information in space (e.g. across the Arctic and adjacent domains) and over historical and future periods (e.g. under altered climate and other forcings). These are: (i) equilibrium biogeographical models; (ii) frame‐based transient ecosystem models, and (iii) dynamic global vegetation models (DGVMs). The equilibrium response of high‐latitude vegetation to scenarios of increased surface air temperatures projected by equilibrium biogeographical models is for tundra to be replaced by a northward shift of boreal woodland and forests. A frame‐based model (ALFRESCO) indicates the same directional changes, but illustrates how response time depends on rate of temperature increase and concomitant changes in moisture regime and fire disturbance return period. Key disadvantages of the equilibrium models are that they do not simulate time‐dependent responses of vegetation and the role of disturbance is omitted or highly generalized. Disadvantages of the frame‐based models are that vegetation type is modelled as a set unit as opposed to an association of individually simulated plant functional types and that the role of ecosystem biogeochemistry in succession is not explicitly considered. DGVMs explicitly model disturbance (e.g. fire), operate on plant functional types, and incorporate constraints of nutrient availability on biomass production in the simulation of vegetation dynamics. Under changing climate, DGVMs detail conversion of tundra to tree‐dominated boreal landscapes along with time‐dependent responses of biomass, net primary production, and soil organic matter turnover–‐which all increase with warming. Key improvements to DGVMs that are needed to portray behaviour of arctic and boreal ecosystems adequately are the inclusion of anaerobic soil processes for inundated landscapes, permafrost dynamics, and moss‐lichen layer biogeochemistry, as well as broader explicit accounting of disturbance regimes (including insect outbreaks and land management). Transient simulation of these landscapes can be further tailored to high‐latitude processes and issues by spatially interactive, gridded application of arctic/boreal frame‐based models and development of dynamic regional vegetation models (DRVMs) utilizing plant functional type schemes that capture the variety of high‐latitude environments.