Transferability of 34 red-listed peatland plant species models across boreal vegetation zone

Rana, Parvez; Tolvanen, Anne

doi:10.1016/j.ecolind.2021.107950

Cited by 6 publications

(10 citation statements)

References 83 publications

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Section: Clarifying Some Previous Results Regarding Resolution In The...mentioning

confidence: 98%

“…It also means that an upscaling procedure that works in one region might not work in a different one, especially if environmental gradients are steeper in one of them. This may also help explain the fact that some models seem to be perfectly transferable from one region to another, while others are not (Rana & Tolvanen, 2021; Randin et al, 2006), and why the choice of predictors has such a large influence on model transferability (Petitpierre et al, 2017). Studying the rates of change of the environmental gradients driving SDMs of the species of interest, especially at intermediate probability values, might be an interesting venue to predict model transferability between regions.…”

Section: Discussionmentioning

confidence: 99%

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A theoretical framework for upscaling species distribution models

Meynard,

Piou,

Kaplan

2023

Methods Ecol Evol

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Species distribution models (SDM) have become one of the most popular predictive tools in ecology. With the advent of new computation and remote sensing technology, high‐resolution environmental data sets are becoming more and more common predictors in these modelling efforts. Understanding how scaling affects their outputs is therefore fundamental to understand their applicability. Here, we develop a theoretical basis to understand the consequences of aggregating occurrence and environmental data at different resolutions. We provide a theoretical framework, along with numerical simulations and a real‐world case study, to show how these scaling rules influence predictive outputs. We show that the properties of the environment–occurrence relationships change when the data are aggregated: the mean probability of occurrence and species prevalence increases, the optimal environmental values shift and classification rates increase at coarser resolutions up to a certain level. Furthermore, and contrary to the widespread expectation that high‐resolution data would produce better predictions, we show here that model performance may increase using coarser resolution data sets rather than the inverse. Finally, we also show that model performance depends not only on the environment–occurrence relationship but also on the interaction between this and the geography and distribution of the available environment. This theoretical framework helps understanding previously incoherent results regarding SDM upscaling and model performance, and illustrates how theoretical and empirical results can provide important feedbacks to advance in understanding scaling issues in macroecology. The interaction between the shape of the environment–occurrence relationship and the rates of change of the environment is fundamental to understand the effects of upscaling in model performance, and may explain why some models are more difficult to transfer to different regions. Most importantly, we argue that there are conceptual choices related to scaling and SDM fitting that require expert knowledge and further explorations between theory and practice in macroecology.

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Section: Clarifying Some Previous Results Regarding Resolution In The...mentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

A theoretical framework for upscaling species distribution models

Meynard,

Piou,

Kaplan

2023

Methods Ecol Evol

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“…Our results and interpretations are based on the current mire extent in the SMC. Land use changes are known to alter ecosystem patterning in forest landscapes (Rana & Tolvanen, 2021; Sallinen et al., 2019). However, the SMC is sparsely populated, with settlements and agriculture concentrated on coastal and river areas (Sävarån and Täfteån).…”

Section: Discussionmentioning

confidence: 99%

Topography and Time Shape Mire Morphometry and Large‐Scale Mire Distribution Patterns in the Northern Boreal Landscape

Ehnvall,

Ratcliffe,

Nilsson

et al. 2024

JGR Earth Surface

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Peatlands are major terrestrial soil carbon stores, and open mires in boreal landscapes hold a considerable fraction of the global peat carbon. Despite decades of study, large‐scale spatiotemporal analyses of mire arrangement have been scarce, which has limited our ability to scale‐up mire properties, such as carbon accumulation to the landscape level. Here, we use a land‐uplift mire chronosequence in northern Sweden spanning 9,000 years to quantify controls on mire distribution patterns. Our objectives include assessing changes in the spatial arrangement of mires with land surface age, and understanding modifications by upland hydrotopography. Characterizing over 3,000 mires along a 30 km transect, we found that the time since land emergence from the sea was the dominant control over mire coverage, especially for the establishment of large mire complexes. Mires at the youngest end of the chronosequence were small with heterogenous morphometry (shape, slope, and catchment‐to‐mire areal ratios), while mires on the oldest surfaces were variable in size, but included larger mires with more complex shapes and smaller catchment‐to‐mire ratios. In general, complex topography fragmented mires by constraining the lateral expansion, resulting in a greater number of mires, but reduced total mire area regardless of landscape age. Mires in this study area occurred on slopes up to 4%, indicating a hydrological boundary to peatland expansion under local climatic conditions. The consistency in mire responses to spatiotemporal controls illustrates how temporal limitation in peat initiation and accumulation, and topographic constraints to mire expansion together have shaped present day mire distribution patterns.

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“…Total precipitation during the growing season was comparable between the 2 years (474.7 mm in 2017 and 485 mm in 2021), but was distributed differently over time (Figure 2d, Table 3). As precipitation alone does not reflect the actual amount of moisture available for the vegetation (Skov & Swenning, 2004), we applied a commonly used simple model to calculate the potential water balance as the difference between precipitation and monthly potential evapotranspiration, which is based on the monthly mean temperature (Rana & Tolvanen, 2021; Skov & Swenning, 2004; Stephenson, 1998). At our site, this showed a water deficit during the early growing season (May) in 2017, and during the peak growing season (June and July) in 2021 (Table 3).…”

Section: Methodsmentioning

confidence: 99%

“…Total tree biomass (t ha we applied a commonly used simple model to calculate the potential water balance as the difference between precipitation and monthly potential evapotranspiration, which is based on the monthly mean temperature (Rana & Tolvanen, 2021;Skov & Swenning, 2004;Stephenson, 1998). At our site, this showed a water deficit during the early growing season (May) in 2017, and during the peak growing season (June and July) in 2021 (Table 3).…”

Section: Mean Wt Nmentioning

confidence: 99%

Water level drawdown makes boreal peatland vegetation more responsive to weather conditions

Köster,

Chapman,

Barel

et al. 2023

Global Change Biology

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Climate warming and projected increase in summer droughts puts northern peatlands under pressure by subjecting them to a combination of gradual drying and extreme weather events. The combined effect of those on peatland functions is poorly known. Here, we studied the impact of long‐term water level drawdown (WLD) and contrasting weather conditions on leaf phenology and biomass production of ground level vegetation in boreal peatlands. Data were collected during two contrasting growing seasons from a WLD experiment including a rich and a poor fen and an ombrotrophic bog. Results showed that WLD had a strong effect on both leaf area development and biomass production, and these responses differed between peatland types. In the poor fen and the bog, WLD increased plant growth, while in the rich fen, WLD reduced the growth of ground level vegetation. Plant groups differed in their response, as WLD reduced the growth of graminoids, while shrubs and tree seedlings benefited from it. In addition, the vegetation adjusted to the lower WTs, was more responsive to short‐term climatic variations. The warmer summer resulted in a greater maximum and earlier peaking of leaf area index, and greater biomass production by vascular plants and Sphagnum mosses at WLD sites. In particular, graminoids benefitted from the warmer conditions. The change towards greater production in the WLD sites in general and during the warmer weather in particular, was related to the observed transition in plant functional type composition towards arboreal vegetation.

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Transferability of 34 red-listed peatland plant species models across boreal vegetation zone

Cited by 6 publications

References 83 publications

A theoretical framework for upscaling species distribution models

A theoretical framework for upscaling species distribution models

Topography and Time Shape Mire Morphometry and Large‐Scale Mire Distribution Patterns in the Northern Boreal Landscape

Water level drawdown makes boreal peatland vegetation more responsive to weather conditions

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