302 research outputs found
Connecting dynamic vegetation models to data - an inverse perspective
No full textDynamic vegetation models provide process-based explanations of the dynamics and the distribution of plant ecosystems. They offer significant advantages over static, correlative modelling approaches, particularly for ecosystems that are outside their equilibrium due to global change or climate change. A persistent problem, however, is their parameterization. Parameters and processes of dynamic vegetation models (DVMs) are traditionally determined independently of the model, while model outputs are compared to empirical data for validation and informal model comparison only. But field data for such independent estimates of parameters and processes are often difficult to obtain, and the desire to include better descriptions of processes such as biotic interactions, dispersal, phenotypic plasticity and evolution in future vegetation models aggravates limitations related to the current parameterization paradigm. In this paper, we discuss the use of Bayesian methods to bridge this gap. We explain how Bayesian methods allow direct estimates of parameters and processes, encoded in prior distributions, to be combined with inverse estimates, encoded in likelihood functions. The combination of direct and inverse estimation of parameters and processes allows a much wider range of vegetation data to be used simultaneously, including vegetation inventories, species traits, species distributions, remote sensing, eddy flux measurements and palaeorecords. The possible reduction of uncertainty regarding structure, parameters and predictions of DVMs may not only foster scientific progress, but will also increase the relevance of these models for policy advice
Species richness-environment relationships of European arthropods at two spatial grains: habitats and countries
No full textWe study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area
Biotic modifiers, environmental modulation and species distribution models
No full textThe ability of species to modulate environmental conditions and resources has long been of interest. In the past three decades the impacts of these biotic modifiers have been investigated as ‘ecosystem engineers’, ‘niche constructors’, ‘facilitators’ and ‘keystone species’. This environmental modulation can vary spatially from extremely local to global, temporally from days to geological time, and taxonomically from a few to a very large number of species. Modulation impacts are pervasive and affect, inter alia, the climate, structural environments, disturbance rates, soils and the atmospheric chemical composition. Biotic modifiers may profoundly transform the projected environmental conditions, and consequently have a significant impact on the predicted occurrence of the focal species in species distribution models (SDMs). This applies especially when these models are projected into different geographical regions or into the future or the past, where these biotic modifiers may be absent, or other biotic modifiers may be present. We show that environmental modulation can be represented in SDMs as additional variables. In some instances it is possible to use the species (e.g. biotic modifiers) in order to reflect the modulation. This would apply particularly to cases where the effect is the result of a single or a small number of species (e.g. elephants transforming woodland to grassland). Where numerous species generate an effect (such as tree species making a forest, or grasses facilitating fire) that modulates the abiotic environment, the effect itself might be a better descriptor for the aggregated action of the numerous species. We refer to this ‘effect’ as the modulator. Much of the information required to incorporate environmental modulation effects in SDMs is already available from remote-sensing data and vegetation models
Data and code from: "How to map biomes: quantitative comparison and review of biome-mapping methods"
No full textOverview
This repository is a supplement to the study: Champreux, A., Saltré, F., Traylor, W., Hickler, T., and Bradshaw, C. How to map biomes: quantitative comparison and review of biome-mapping methods. in prep. This repository contains all input data, output data, and scripts (.R, .m) used in the study by Champreux et al. (in prep)This repository enables full reproducibility of the study. Instructions are included below in the `Usage/How to run` section of the in the README (Code_repository).
This repository also includes an R script to compare any two biome maps (map_Kij/map_kij.R) based on the algorithm shown in Champreux et al. (in prep, Figure 2). Instructions to use this script are included in map_Kij/README.md.
License
Most of the source code of this project is licensed under the GNU General Public License v3.0 or later. The Git repository follows the REUSE standard: Each file has its license information either in a comment at the top or in a separate file of the same name with the extension .license.
The Debian-based Singularity/Apptainer image in singularity.img contains software packages that are all Free Software according to Debian's Social Contract. Each software package has its own license.
The output files themselves can hardly be considered a creative work and thus don't fall under copyright protection. Consider them in the Public Domain under the CC0 1.0 license
Results of parameter estimation for Ambrosia artemisiifolia simulations
No full textThe NetCDF files in this dataset contain annual results of the 100 best "runs" from a Latin-Hupercube-Sampling over the parameter space in North America (NAM) and transferred those results to Europe (EUR). The Excel sheet contains the parameter combination for those.
Leiblein-Wild, M. C., Steinkamp, J., Hickler, T. and Tackenberg, O.: Modelling the potential distribution, net primary production and phenology of common ragweed with a physiological model, J. Biogeogr., 43(3), 544–554, doi:10.1111/jbi.12646, 2016.
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Why would plant species become extinct locally if growing conditions improve?
No full textwo assumptions underlie current models of the geographical ranges of perennial plant species: 1. current ranges are in equilibrium with the prevailing climate, and 2. changes are attributable to changes in macroclimatic factors, including tolerance of winter cold, the duration of the growing season, and water stress during the growing season, rather than to biotic interactions. These assumptions allow model parameters to be estimated from current species ranges. Deterioration of growing conditions due to climate change, e.g. more severe drought, will cause local extinction. However, for many plant species, the predicted climate change of higher minimum temperatures and longer growing seasons means, improved growing conditions. Biogeographical models may under some circumstances predict that a species will become locally extinct, despite improved growing conditions, because they are based on an assumption of equilibrium and this forces the species range to match the species-specific macroclimatic thresholds. We argue that such model predictions should be rejected unless there is evidence either that competition influences the position of the range margins or that a certain physiological mechanism associated with the apparent improvement in growing conditions negatively affects the species performance. We illustrate how a process-based vegetation model can be used to ascertain whether such a physiological cause exists. To avoid potential modelling errors of this type, we propose a method that constrains the scenario predictions of the envelope models by changing the geographical distribution of the dominant plant functional type. Consistent modelling results are very important for evaluating how changes in species areas affect local functional trait diversity and hence ecosystem functioning and resilience, and for inferring the implications for conservation management in the face of climate change
Global quantitative synthesis of ecosystem functioning across climatic zones and ecosystem types
No full textAim
Providing a quantitative overview of ecosystem functioning in a three‐dimensional space defined by ecosystem stocks, fluxes and rates, across major ecosystem types and climatic zones.
Location
Global.
Time period
1966–2019.
Major taxa studied
Ecosystem‐level measurements (all organism types).
Methods
We conducted a global quantitative synthesis of a wide range of ecosystem variables related to carbon stocks and fluxes. We gathered a total of 4,479 values from 1,223 individual sites (unique geographical coordinates) reported in the literature (604 studies), covering ecosystem variables including biomass and detritus stocks, gross primary production, ecosystem respiration, detritus decomposition and carbon uptake rates, across eight major aquatic and terrestrial ecosystem types and five broad climatic zones (arctic, boreal, temperate, arid and tropical). We analysed the relationships among variables emerging from the comparisons of stocks, fluxes and rates across ecosystem types and climates.
Results
Within our three‐dimensional functioning space, average ecosystems align along a gradient from fast rates–low fluxes and stocks (freshwater and pelagic marine ecosystems) to low rates–high fluxes and stocks (forests), a gradient that we hypothesize results mainly from variation in primary producer characteristics. Moreover, fluxes and rates decrease from warm to colder climates, consistent with the metabolic theory of ecology. However, the strength of climatic effects differs among variables and ecosystem types, resulting, for instance, in opposing effects on net ecosystem production between terrestrial and freshwater ecosystems (positive versus negative effects).
Main conclusions
This large‐scale synthesis provides a first quantified cross‐ecosystem and cross‐climate comparison of multivariate ecosystem functioning. This gives a basis for a mechanistic understanding of the interdependency of different aspects of ecosystem functioning and their sensitivity to global change. To anticipate responses to change at the ecosystem level, further work should investigate potential feedbacks between ecosystem variables at finer scales, which involves site‐level quantifications of multivariate functioning and theoretical developments
Structural diversity underpins carbon storage in Australian temperate forests
No full textAbstract
Aim
Forest carbon storage is the result of a multitude of interactions among biotic and abiotic factors. Our aim was to use an integrative approach to elucidate mechanistic relationships of carbon storage with biotic and abiotic factors in the natural forests of temperate Australia, a region that has been overlooked in global analyses of carbon‐biodiversity relations.
Location
South‐eastern Australia.
Time period
2010–2015.
Major taxa studied
Forest trees in 732 plots.
Methods
We used the most comprehensive forest inventory database available for south‐eastern Australia and structural equation models to assess carbon‐storage relationships with biotic factors (species or functional diversity, community‐weighted mean (CWM) trait values, structural diversity) and abiotic factors (climate, soil, fire history). To assess the consistency of relationships at different environmental scales, our analyses involved three levels of data aggregation: six forest types, two forest groups (representing different growth environments), and all forests combined.
Results
Structural diversity was consistently the strongest independent predictor of carbon storage at all levels of data aggregation, whereas relationships with species‐ and functional‐diversity indices were comparatively weak. CWMs of maximum height and wood density were also significant independent predictors of carbon storage in most cases. In comparison, climate, soil, and fire history had only minor and mainly indirect effects via biotic factors on carbon storage.
Main conclusions
Our results indicate that carbon storage in our temperate forests was underpinned by tree structural diversity (representing efficient utilisation of space) and by CWM trait values (representing selection effects) more so than by tree species richness or functional diversity. Abiotic effects were comparatively weak and mostly indirect via biotic factors irrespective of the environmental range. Our study highlights the importance of managing forests for functionally important species and to maintain and enhance their structural complexity in order to support carbon storage
Global biome patterns of the Middle and Late Pleistocene
No full textOur primary aim was to assess the hypothesis that distinctive features of the patterns of vegetation change during successive Quaternary glacial–interglacial cycles reflect climatic differences arising from forcing differences. We addressed this hypothesis using 207 half-degree resolution global biome pattern simulations, for time slices between 800 ka and 2 ka, made using the LPJ-GUESS dynamic global vegetation model. Simulations were driven using ice-core atmospheric CO2 concentrations, Earth's obliquity, and outputs from a pre-industrial and 206 palaeoclimate experiments; four additional simulations were driven using projected future CO2 concentrations. Climate experiments were run using HadCM3. Using a rule-based approach, above-ground biomass and leaf area index of LPJ-GUESS plant functional types were used to infer each grid cell's biome. The hypothesis is supported by the palaeobiome simulations.
To enable comparisons with the climatic forcing, multivariate analyses were performed of global vegetation pattern dissimilarities between simulations. Results showed generally similar responses to glacial–interglacial climatic variations during each cycle, although no two interglacials or glacials had identical biome patterns. Atmospheric CO2 concentration was the strongest driver of the dissimilarity patterns. Dissimilarities relative to the time slice with the lowest atmospheric CO2 concentration show the log–linear relationship to atmospheric CO2 concentration expected of an index of ecocarbon sensitivity.
For each simulation, extent and total above-ground biomass of each biome were calculated globally and for three longitudinal segments corresponding to the major continental regions. Mean and minimum past extents of forest biomes, notably Temperate Summergreen Forest, in the three major continental regions strongly parallel relative tree diversities, hence supporting the hypothesis that past biome extents played an important role in determining present diversity.
Albeit that they reflect the climatic consequences only of the faster Earth system components, simulated potential future biome patterns are unlike any during the past 800 ky, and likely will continue to change markedly for millennia if projected CO2 concentrations are realised.Adobe Acrobat or another .pdf viewer is needed to view 'slideshow'. Other files can all be opened using a simple text file editor (e.g. Wordpad).Funding provided by: Leverhulme TrustCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000275Award Number: RPG-2014-338See Allen et al. (2020), Huntley et al. (2021) and Huntley et al. (2023):
Allen, J.R.M., Forrest, M., Hickler, T., Singarayer, J.S., Valdes, P.J. & Huntley, B. (2020). Global vegetation patterns of the past 140,000 years. Journal of Biogeography, 47, 2073-2090. doi 10.1111/jbi.13930
Huntley, B., Allen, J.R.M., Forrest, M., Hickler, T., Ohlemüller, R., Singarayer, J.S. & Valdes, P.J. (2021). Projected climatic changes lead to biome changes in areas of previously constant biome. Journal of Biogeography, 48, 2418-2428. doi 10.1111/jbi.14213
Huntley, B., Allen, J.R.M., Forrest, M., Hickler, T., Ohlemüller, R., Singarayer, J.S. & Valdes, P.J. (2023). Global biome patterns of the Middle and Late Pleistocene. Journal of Biogeography. doi 10.1111/jbi.1461
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