In forested systems throughout the world, climate influences tree growth and aboveground net primary productivity (ANPP). The effects of extreme climate events (i.e., drought) on ANPP can be compounded by biotic factors (e.g., insect outbreaks). Understanding the contribution of each of these influences on growth requires information at multiple spatial scales and is essential for understanding regional forest response to changing climate. The mixed conifer forests of the Lake Tahoe Basin, California and Nevada, provide an opportunity to analyze biotic and abiotic influences on ANPP. Our objective was to evaluate the influence of moisture stress (climatic water deficit, CWD) and bark beetles on basin-wide ANPP from 1987 to 2006, estimated through tree core increments and a landscape simulation model (LANDIS-II). Tree ring data revealed that ANPP increased throughout this period and had a nonlinear relationship to water demand. Simulation model results showed that despite increased complexity, simulations that include moderate moisture sensitivity and bark beetle outbreaks most closely approximated the field-derived ANPP∼CWD relationship. Although bark beetle outbreaks and episodic drought-induced mortality events are often correlated, decoupling them within a simulation model offers insight into assessing model performance, as well as examining how each contributes to total declines in productivity.
Modern software development techniques are largely unknown to ecologists. Typically, ecological models and other software tools are developed for limited research purposes, and additional capabilities are added later, usually in an ad hoc manner. Modern software engineering techniques can substantially increase scientific rigor and confidence in ecological models and tools. These techniques have the potential to transform how ecological software is conceived and developed, improve precision, reduce errors, and increase scientific credibility. We describe our re‐engineering of the forest landscape model LANDIS (LANdscape DIsturbance and Succession) to illustrate the advantages of using common software engineering practices.
Abstract In the coming century, forecast climate changes caused by increasing greenhouse gases may produce dramatic shifts in tree species distributions and the rates at which individual tree species sequester carbon or release carbon back to the atmosphere. The species composition and carbon storage capacity of northern Wisconsin (USA) forests are expected to change significantly as a result. Projected temperature changes are relatively large (up to a 5.8°C increase in mean annual temperature) and these forests encompass a broad ecotone that may be particularly sensitive to climate change. Our objective was to estimate the combined effects of climate change, common disturbances, and species migrations on regional forests using spatially interactive simulations. Multiple scenarios were simulated for 200 years to estimate aboveground live biomass and tree species composition. We used a spatially interactive forest landscape model (LANDIS‐II) that includes individual tree species, biomass accumulation and decomposition, windthrow, harvesting, and seed dispersal. We used data from two global circulation models, the Hadley Climate Centre (version 2) and the Canadian Climate Center (version 1) to generate transient growth and decomposition parameters for 23 species. The two climate change scenarios were compared with a control scenario of continuing current climate conditions. The results demonstrate how important spatially interactive processes will affect the aboveground live biomass and species composition of northern Wisconsin forests. Forest composition, including species richness, is strongly affected by harvesting, windthrow, and climate change, although five northern species ( Abies balsamea , Betula papyrifera , Picea glauca , Pinus banksiana , P. resinosa ) are lost in both climate scenarios regardless of disturbance scenario. Changes in aboveground live biomass over time are nonlinear and vary among ecoregions. Aboveground live biomass will be significantly reduced because of species dispersal and migration limitations. The expected shift towards southern oaks and hickory is delayed because of seed dispersal limitations.
Abstract Many studies have been conducted to quantify the possible ecosystem/landscape response to the anticipated global warming. However, there is a large amount of uncertainty in the future climate predictions used for these studies. Specifically, the climate predictions can be very different based on a variety of global climate models and alternative greenhouse emission scenarios. In this study, we coupled a forest landscape model, LANDIS‐II, and a forest process model, PnET‐II, to examine the uncertainty (that results from the uncertainty in the future climate predictions) in the forest‐type composition prediction for a transitional forest landscape [the Boundary Water Canoe Area]. Using an improved global‐sensitivity analysis technique [Fourier amplitude sensitivity test], we also quantified the amount of uncertainty in the forest‐type composition prediction contributed by different climate variables including temperature, CO 2 , precipitation and photosynthetic active radiation (PAR). The forest landscape response was simulated for the period 2000–2400 ad based on the differential responses of 13 tree species under an ensemble of 27 possible climate prediction profiles (monthly time series of climate variables). Our simulations indicate that the uncertainty in the forest‐type composition becomes very high after 2200 ad , which is close to the time when the current forests are largely removed by windthrow disturbances and natural mortality. The most important source of uncertainty in the forest‐type composition prediction is from the uncertainty in temperature predictions. The second most important source is PAR, the third is CO 2 and the least important is precipitation. Our results also show that if the optimum photosynthetic temperature rises due to CO 2 enrichment, the forest landscape response to climatic change measured by forest‐type composition may be substantially reduced.
