Modeling vegetation fires and fire emissions

Fire is the most important ecological and forest disturbance agent worldwide, is a major way by which carbon is transferred from the land to the atmosphere, and is globally a significant source of greenhouse gases and aerosols. Wildfires across all major biome types globally consume about 5% of net annual terrestrial primary production per annum, and release about 2-4 Pg C per annum, of which approximately 0.6 Pg C comes from tropical deforestation and below-ground peat fires. The global figure is equivalent to about 20-30% of global emissions from fossil fuels. Tropical savannas comprise the largest areas burned and greatest emissions sources from vegetation wildfires. Fires in Mediterranean forests and shrublands, tropical forests and boreal forests are also significant sources of emissions because they are generally characterised by much higher fuel loads per unit area compared with grasslands. Improved satellite data and sophisticated biogeochemical modeling enables emis-sions assessments on a global scale with fine spatial and temporal resolution. Emissions estimates are still comparable to those based on older inventory-based techniques, but uncertainties remain large. Fires increase during El Niño periods because parts of the tropics where humans use fire as a tool for deforestation experience drought conditions. These spikes contribute to the inter-annual variability of CO2 and CH4 observed in the atmosphere. Recently developed dynamic fire-vegetation models are capable of simulating the extent of wildfires as well as their emissions of CO2 and other greenhouse gases for ambient as well as for projected climatic conditions. The performance of fire-vegetation models however needs to be strongly improved and validated

Approaching the potential of model-data comparisons of global land carbon storage

Abstract Carbon storage dynamics in vegetation and soil are determined by the balance of carbon influx and turnover. Estimates of these opposing fluxes differ markedly among different empirical datasets and models leading to uncertainty and divergent trends. To trace the origin of such discrepancies through time and across major biomes and climatic regions, we used a model-data fusion framework. The framework emulates carbon cycling and its component processes in a global dynamic ecosystem model, LPJ-GUESS, and preserves the model-simulated pools and fluxes in space and time. Thus, it allows us to replace simulated carbon influx and turnover with estimates derived from empirical data, bringing together the strength of the model in representing processes, with the richness of observational data informing the estimations. The resulting vegetation and soil carbon storage and global land carbon fluxes were compared to independent empirical datasets. Results show model-data agreement comparable to, or even better than, the agreement between independent empirical datasets. This suggests that only marginal improvement in land carbon cycle simulations can be gained from comparisons of models with current-generation datasets on vegetation and soil carbon. Consequently, we recommend that model skill should be assessed relative to reference data uncertainty in future model evaluation studies

Fire-vegetation interactions during the last 11,000 years in boreal and cold temperate forests of Fennoscandia

The long-term ecological interactions between fire and the composition of dominant trees and shrubs in boreal and cold temperate Fennoscandian forests are still under discussion. We hypothesized that fire-prone taxa should abound during periods and regions characterized by higher fire disturbance, while fire-intolerant taxa should dominate when and where fire activity is low. Biomass burning (BB) is here investigated based on 69 sedimentary charcoal records. For the same sites, the relative contribution of pollen-based reconstructions of dominant vegetation cover divided into three different fire-sensitivity classes is explored by means of a statistical approach. The overall patterns found across Fennoscandia suggest that Ericaceae (mainly Calluna), Pinus, Betula and Populus are strongly positively correlated with multi-millennial variability of BB in both boreal and cold temperate forests, confirming their fire-prone character (taxa adapted/favoured by burning). Positive but much weaker (and not always significant) relationships also exist between long-term trends in BB and Fagus, Quercus, Corylus, Alnus, Juniperus, Carpinus and Salix, fire-tolerant taxa that survive low/moderate intense fires because of specific functional traits or their rapid, enhanced regeneration after fire. A strong negative significant correlation is instead detected between BB and Picea, Ulmus Tilia, Fraxinus, which are fire-intolerant taxa and can locally disappear for a short time after a fire. This large-scale analysis supports our initial hypothesis that tree and shrub dominance was closely linked to biomass burning since the onset of the Holocene in the study regions. Fire was an important ecosystem disturbance in Fennoscandia influencing long-term vegetation dynamics and composition over the last 11,000 years, although human activities probably altered the strength of fire-vegetation interactions during more recent millennia

Earlier occurrence and increased explanatory power of climate for the first incidence of potato late blight caused by Phytophthora infestans in Fennoscandia

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Climate change impacts on long-term forest productivity might be driven by species turnover rather than by changes in tree growth

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordAim: Climate change impacts forest functioning and services through two inter-related effects. First, it impacts tree growth, with effects, for example, on biomass production. Second, climate change might also reshuffle community composition, with further effects on forest functioning. However, the relative importance of these two effects has rarely been studied. Here, we developed a novel modelling approach to investigate such importance for forest productivity. Location: 11 forest sites in central Europe. Time period: Historical (years 1901-1990) and end-of the-century (2070-2100) climatic conditions. We simulated 2000 years of forest dynamics for each condition. Major taxa studied: 25 common tree species in European temperate forests. Methods: We coupled species distribution models and a forest succession model, working at complementary spatial and temporal scales, to simulate the climatic filtering shaping potential tree species pools, the biotic filtering shaping realized communities, and the functioning of these realized communities in the long term. Results: Under an average temperature increase (relative to 1901-1990) of between 1.5 ºC and 1.7 ºC, changes in simulated forest productivity were mostly caused by changes in the growth of persisting tree species. With an average temperature increase of 3.6 ºC – 4.0 ºC, changes in simulated productivity at currently climatically mild sites were again predominantly caused by changes in tree species growth. However, at the currently warmest and coldest sites, productivity changes were mostly related to shifts in species composition. In general, at the coldest sites, forest productivity is likely to be enhanced by climate change, and at the warmest sites productivity might increase or decrease depending on the future regime of precipitation. Main conclusions: Combining two complementary modelling approaches that address questions at the interface between biogeography, community ecology, and ecosystem functioning, reveals that climate change-driven community reshuffling in the long term might be critically important for ecosystem functioning.ANRERA‐Net BiodivERsAFun2Fun projectDRESS projec

The effect of fire on tree–grass coexistence in savannas: a simulation study

The savanna biome has the greatest burned area globally. Whereas the global distribution of most biomes can be predicted successfully from climatic variables, this is not so for savannas. Attempts to dynamically model the distribution of savannas, including a realistically varying tree : grass ratio are fraught with difficulties. In a simulation study using the dynamic vegetation model LPJ-GUESS we investigate the effect of fire on the tree : grass ratios as well as the biome distribution on the African continent. We performed simulations at three spatial scales: locally, at four sites inside Kruger National Park (South Africa); regionally, along a precipitation gradient; and for the African continent. We evaluated the model using results of a fire experiment and found that the model underestimates the effect of fire on tree cover slightly. On a regional scale, high frequencies were able to prevent trees from outcompeting grasses in mesic regions between ~700 and 900 mm mean annual precipitation. Across the African continent, incorporation of fire improved notably the simulated distribution of the savanna biome. Our model results confirm the role of fire in determining savanna distributions, a notion that has been challenged by competing theories of tree–grass coexistence

Музично-етнографічні польові дослідження (на прикладі обстеження історичної Хотинщини)

The author of the article researches the approaches of musical-ethnographic work, its methods and goals, as well as the choice of the specific territory and its exploration defined by them. The author comments on his intention to examine the area of Khotyn, which now is a part of Chernivtsy region; explains the methods of examining the territory. Pluses and minuses of the existing song collections dedicated to the given district are under consideration in this article. In conclusion short information about Northern Bessarabia and its population is given

Turnover of plant trait hierarchies in simulated community assembly in response to fertility and disturbance

Plant ecologists have placed increasing emphasis on a functional understanding of vegetation. One way to gain insight into the assemblage of vegetation communities is to investigate plant trait responses to environmental gradients or experimental treatments. We present simulations of responses of suites of traits to treatments differing in soil resources and disturbance intensity, in order to construct a functional response hierarchy of traits. We focus on the traits specific leaf area (SLA), plant height, seed mass and life cycle. Though only four traits are varied, these traits are connected to other traits either through trade-offs (e.g. SLA with leaf life span and relative growth rate, seed mass with seed number) or allometric rules (e.g. above-ground biomass scales positively with below-ground biomass). Thus a wide range of plant life history is represented in the simulations. We simulated the assemblage of plant types composed of these traits at two fertility levels and four disturbance treatments, i.e. every 7 years, annually, or monthly mown, and annually ploughed. We present the results of a simulation using LEGOMODEL, an individual-based, spatially explicit, ecological field model and develop a novel method to construct a functional response hierarchy of traits. A competitive ranking of plant types is constructed and subsequently translated into a functional response hierarchy of traits on the basis of the variability of trait states within the plant type ranking. The competitive superior trait states as well as the functional hierarchy change between different treatments. Except for deeply disturbed conditions, perennial plants are always superior. Tall canopy height is superior on fertile soil, as long as it is not mown monthly. High SLA is advantageous at fertile or ploughed sites. Life cycle and canopy height are always at the first two ranks of the functional hierarchy of traits. Our results concerning the advantageous trait states are in line with published field studies, except for the trait seed mass. Here LEGOMODEL predicts competitive advantage of small seeds under any treatment. The functional response hierarchy of traits presents a hypothesis to be refined by further field research as we know of no field study addressing this question. (C) 2006 Elsevier B.V. All rights reserved

High-resolution global population projections dataset developed with CMIP6 RCP and SSP scenarios for year 2010–2100

We present a novel, global 30 arc seconds (∼1 km at the equator) population projection dataset covering each year from 2010 to 2100 that is consistent with both country level population and gridded urban fractions from the Coupled Model Intercomparison Project 6 (CMIP6). While IPCC population projections until 2100 are available at country level for Socio-Economic Pathways (SSPs), land cover (including the urban fraction) is only available for Representative Concentration Pathways (RCPs). To perform simulations of e.g., future supply and demand for agricultural products, fine scale projections of population density are needed for combinations of SSPs and RCPs. Therefore, we generated a 30 arc seconds dataset consistent with both SSPs and RCPs within the framework of the IPCC. This data set is useful in applications where spatially explicit projections of aspects of global change are investigated at a fine spatial scale. For example, if a link function between night-time lights and population density is found based on current satellite images and recent population density data, a projection of night-time light lights can be generated by using this link function with our projected population density. Such a projection can for example be used to evaluate the potential for future light pollution