Forest productivity under climate change: a checklist for evaluating model studies

Abstract

Climate change is highly likely to impact on forest productivity over the next century. The direction and magnitude of change are uncertain because many factors are changing simultaneously, such as atmospheric composition, temperature, rainfall, and land use. Simulation models have been widely used to estimate how these interacting factors might combine to alter forest productivity. Such studies have used many different types of models with different underlying assumptions. To evaluate predictions made by such studies, it is essential to understand the type of model and the assumptions used. In this article, we provide a checklist for use when evaluating modeled estimates of climate change impacts on forest productivity. The checklist highlights the assumptions that we believe are critical in determining model outcomes. Models are classified into different general types, and assumptions relating to effects of atmospheric CO 2 concentration, temperature, water availability, nutrient cycling, and disturbance are discussed. Our main aim is to provide a guide to enable correct interpretation of model projections. The article also challenges modelers to improve the quality of information provided about their model assumptions.

Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany)

“…Another source of variation in height growth might be the genetic diversity within Norway spruce [40], though provenances in Bavaria do not seem to differ greatly [41]. Furthermore phosphorus could have a strong influence on growth [42,43]. Phosphorus availability is optimal in the slightly acid to neutral pH range.…”

Growth decline assessment in Pinus sylvestris L. and Pinus nigra Arnold. forest by using 3-PG model.

“…Extreme drought events strongly affect the physiological functioning of forests, and an increase of their intensity and severity will negatively affect tree growth and vigour in sites where these are strongly limited by water availability (Breshears et al 2 index models (Ung et al, 2001). However, efforts at physiological modelling of forest decline in relation to the effects of silviculture on Mediterranean pine and the impact of global change on forest in general are scarce (Fontes et al, 2010;Medlyn et al, 2011). Process-based stand growth simulation models, based on available empirical data or known physiological processes, or both, have been developed to improve our understanding of forest behaviour on the basis of descriptions of plant-soil and carbon-nutrient-water interactions.…”

Potential impacts of regional climate change on site productivity of Larix olgensis plantations in northeast China

“…However, site productivity presents great spatial and temporal variability (Skovsgaard & Vanclay 2013). Climate change directly or indirectly affects forest productivity due to rising atmospheric CO2 concentration and temperatures, changes in the amount and timing of precipitation and the interactions of forest ecosystems (Kirilenko & Sedjo 2007, Medlyn et al 2011. Experiments, observations and models indicate that the forest productivity changes with climate change, but the direction and magnitude of the effects are still uncertain (Medlyn et al 2011).…”

“…Climate change directly or indirectly affects forest productivity due to rising atmospheric CO2 concentration and temperatures, changes in the amount and timing of precipitation and the interactions of forest ecosystems (Kirilenko & Sedjo 2007, Medlyn et al 2011. Experiments, observations and models indicate that the forest productivity changes with climate change, but the direction and magnitude of the effects are still uncertain (Medlyn et al 2011). Using dominant height as a measure of site productivity, Bontemps et al (2009) reported an increase of more than 50% in common beech at the end of the 20 th century in north-eastern France, whereas Badeau et al (1995) found an increase of 27%.…”