Gap models across micro- to mega-scales of time and space: examples of Tansley’s ecosystem concept

Abstract

Background: Gap models are individual-based models for forests. They simulate dynamic multispecies assemblages over multiple tree-generations and predict forest responses to altered environmental conditions. Their development emphases designation of the significant biological and ecological processes at appropriate time/space scales. Conceptually, they are with consistent with A.G. Tansley's original definition of "the ecosystem". Results: An example microscale application inspects feedbacks among terrestrial vegetation change, air-quality changes from the vegetation's release of volatile organic compounds (VOC), and climate change effects on ecosystem production of VOC's. Gap models can allocate canopy photosynthate to the individual trees whose leaves form the vertical leaf-area profiles. VOC release depends strongly on leaf physiology by species of these trees. Leaf-level VOC emissions increase with climate-warming. Species composition change lowers the abundance of VOC-emitting taxa. In interactions among ecosystem functions and biosphere/atmosphere exchanges, community composition responses can outweigh physiological responses. This contradicts previous studies that emphasize the warming-induced impacts on leaf function. As a mesoscale example, the changes in climate (warming) on forests including pest-insect dynamics demonstrates changes on the both the tree and the insect populations. This is but one of many cases that involve using a gap model to simulate changes in spatial units typical of sampling plots and scaling these to landscape and regional levels. As this is the typical application scale for gap models, other examples are identified. The insect/climatechange can be scaled to regional consequences by simulating survey plots across a continental or subcontinental zone. Forest inventories at these scales are often conducted using independent survey plots distributed across a region. Model construction that mimics this sample design avoids the difficulties in modelling spatial interactions, but we also discuss simulation at these scales with contagion effects. Conclusions: At the global-scale, successful simulations to date have used functional types of plants, rather than tree species. In a final application, the fine-scale predictions of a gap model are compared with data from micrometeorological eddy-covariance towers and then scaled-up to produce maps of global patterns of evapotranspiration, net primary production, gross primary production and respiration. New active-remote-sensing instruments provide opportunities to test these global predictions.

Towards understanding predictability in ecology: A forest gap model case study

“…Linearly increasing posterior estimates for the process covariance matrix degrees of freedom over time (Figure 4 left) provided evidence that the estimation of the process covariance matrix was increasingly constrained over time and could continue to be constrained by a longer time series of data. The values associated with the biomass of each species, along the diagonal of the process covariance matrix, were estimated to be small (Table 3 column 3), indicating that annual species biomass accumulation process was well represented by the forest gap model (Shugart et al, 2020), once we accounted for uncertainty in the data. Similarly, the species correlations in the process covariance matrix were estimated to be small with the most significant correlation between species being a small negative relationship between beech and red oak (correlation = −0.125, Figure 4).…”

Effectiveness of plants and green infrastructure utilization in ambient particulate matter removal

“…Another issue is the emission of BVOCs. A highly complex species richness and vertical diversity through the forest canopy is required to prevent leaves from overheating and increasing BVOC production [ 194 ].…”

Bridging implementation gaps to connect large ecological datasets and complex models

“…University of Virginia Forest Model Enhanced (UVAFME) is a forest gap model that was originally developed as an enhancement for alpine and boreal forests on previous forest gap models (Shugart et al, 2020 ). The basic principle underlying UVAFME is competition for light, water, and nutrients between individual trees.…”