The pyrogeography of eastern boreal Canada from 1901 to 2012 simulated with the LPJ-LMfire model

Wildland fires are the main natural disturbance shaping forest structure and composition in eastern boreal Canada. On average, more than 700 000 ha of forest burns annually and causes as much as CAD 2.9 million worth of damage. Although we know that occurrence of fires depends upon the coincidence of favourable conditions for fire ignition, propagation, and fuel availability, the interplay between these three drivers in shaping spatiotemporal patterns of fires in eastern Canada remains to be evaluated. The goal of this study was to reconstruct the spatiotemporal patterns of fire activity during the last century in eastern Canada's boreal forest as a function of changes in lightning ignition, climate, and vegetation. We addressed this objective using the dynamic global vegetation model LPJ-LMfire, which we parametrized for four plant functional types (PFTs) that correspond to the prevalent tree genera in eastern boreal Canada (Picea, Abies, Pinus, Populus). LPJ-LMfire was run with a monthly time step from 1901 to 2012 on a 10 km2 resolution grid covering the boreal forest from Manitoba to Newfoundland. Outputs of LPJ-LMfire were analyzed in terms of fire frequency, net primary productivity (NPP), and aboveground biomass. The predictive skills of LPJ-LMfire were examined by comparing our simulations of annual burn rates and biomass with independent data sets. The simulation adequately reproduced the latitudinal gradient in fire frequency in Manitoba and the longitudinal gradient from Manitoba towards southern Ontario, as well as the temporal patterns present in independent fire histories. However, the simulation led to the underestimation and overestimation of fire frequency at both the northern and southern limits of the boreal forest in Québec. The general pattern of simulated total tree biomass also agreed well with observations, with the notable exception of overestimated biomass at the northern treeline, mainly for PFT Picea. In these northern areas, the predictive ability of LPJ-LMfire is likely being affected by the low density of weather stations, which leads to underestimation of the strength of fire- weather interactions and, therefore, vegetation consumption during extreme fire years. Agreement between the spatiotemporal patterns of fire frequency and the observed data across a vast portion of the study area confirmed that fire therein is strongly ignition limited. A drier climate coupled with an increase in lightning frequency during the second half of the 20th century notably led to an increase in fire activity. Finally, our simulations highlighted the importance of both climate and fire in vegetation: despite an overarching CO2- induced enhancement of NPP in LPJ-LMfire, forest biomass was relatively stable because of the compensatory effects of increasing fire activity

FIRE REGIMES IN DRYLAND LANDSCAPES

International audienc

Tipping point interactions may also generate weakening cascades

The paper written by D. I. A. McKay et al. represents an interesting milestone for understanding the Earth's climate, and has stimulated public interest in such global issues. However, as researchers engaged in climatology and biome responses, we have some concerns about its findings. In this response, we posit five technical and conceptual arguments that question the assumptions of this work. McKay et al.'s paper provides a detailed analysis of the possible tipping points (TPs, with their associated thresholds) that the Earth may experience

Tipping point interactions may also generate weakening cascades

The paper written by D. I. A. McKay et al. represents an interesting milestone for understanding the Earth's climate, and has stimulated public interest in such global issues. However, as researchers engaged in climatology and biome responses, we have some concerns about its findings. In this response, we posit five technical and conceptual arguments that question the assumptions of this work. McKay et al.'s paper provides a detailed analysis of the possible tipping points (TPs, with their associated thresholds) that the Earth may experience

Tipping point interactions may also generate weakening cascades

The paper written by D. I. A. McKay et al. represents an interesting milestone for understanding the Earth's climate, and has stimulated public interest in such global issues. However, as researchers engaged in climatology and biome responses, we have some concerns about its findings. In this response, we posit five technical and conceptual arguments that question the assumptions of this work. McKay et al.'s paper provides a detailed analysis of the possible tipping points (TPs, with their associated thresholds) that the Earth may experience

Tipping point interactions may also generate weakening cascades

The paper written by D. I. A. McKay et al. represents an interesting milestone for understanding the Earth's climate, and has stimulated public interest in such global issues. However, as researchers engaged in climatology and biome responses, we have some concerns about its findings. In this response, we posit five technical and conceptual arguments that question the assumptions of this work. McKay et al.'s paper provides a detailed analysis of the possible tipping points (TPs, with their associated thresholds) that the Earth may experience

Understanding Ecosystem Complexity via Application of a Process-Based State Space rather than a Potential Surface

International audienceEcosystems are complex objects, simultaneously combining biotic, abiotic, and human components and processes. Ecologists still struggle to understand ecosystems, and one main method for achieving an understanding consists in computing potential surfaces based on physical dynamical systems. We argue in this conceptual paper that the foundations of this analogy between physical and ecological systems are inappropriate and aim to propose a new method that better reflects the properties of ecosystems, especially complex, historical nonergodic systems, to which physical concepts are not well suited. As an alternative proposition, we have developed rigorous possibilistic, process-based models inspired by the discrete-event systems found in computer science and produced a panel of outputs and tools to analyze the system dynamics under examination. e state space computed by these kinds of discrete ecosystem models provides a relevant concept for a holistic understanding of the dynamics of an ecosystem and its abovementioned properties. Taking as a specific example an ecosystem simplified to its process interaction network, we show here how to proceed and why a state space is more appropriate than a corresponding potential surface

Climate and vegetation: Simulating the African humid period

International audienceThe outputs of the climate simulated by two General Circulation Models (GCMs), (IPSL and UGAMP) have been used to force a vegetation model (LPJ-GUESS) to analyze the Holocene African humid period (AHP) and related vegetation changes over the 18°W-35°E, 5°S-25°N region. At the continental scale, simulations with the two models confirm the intensified African monsoon during the Holocene as compared to now, and the early but gradual termination of the AHP in eastern regions as compared to western regions. At the regional scale, the two GCMs results present important differences in the timing of the AHP, its spatial extent and the summer rainfall amplitude. Consequently, the vegetation model simulates changes that are globally in agreement with pollen data, but with large differences according to the region and the model considered. During the AHP, the IPSL climate induced proper vegetation changes in the eastern Sahara and in the Sahel, whereas the UGAMP climate induced correct changes in the western Sahara and in the equatorial zone

Classification des grands incendies dans le sud-est de la France pour adapter la stratégie de suppression

Large wildfires keep on developing in the French Mediterranean region, regularly threatening responders. We tested if these large fires could be classified into types, and if these types were representative of different environmental drivers. To proceed, we established a database comprising 153 of the largest fires from the last 25 years. For each fire we collected three datasets to describe the environment, the fire behaviour and the control operations. We performed a hierarchical clustering analysis followed by a predictive analysis with Bootstrap Regression Trees. Fires were classified in 8 types that could a posteriori be reduced to 5 types. The One-way type was featured by moderate environmental parameters, the Multi-way type was featured by slope, the Winding and Rapid types were featured by wind, while the Very large type was featured by the drought code. Moreover, the probability of having vehicles trapped in a large fire was primarily correlated with the number of vehicles assigned for suppression. This study provides the basis for upcoming trainings of Fire Analyst in France. It paves the way for further research on predictive wildfire danger mapping