Weather‐driven demography and population dynamics of an endemic perennial plant during a 34‐year period

Lindell, Torbjörn; Ehrlén, Johan; Dahlgren, Johan P.

doi:10.1111/1365-2745.13821

Cited by 8 publications

(12 citation statements)

References 66 publications

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“…Based on the sensitivity analysis we conclude that the most important stage for long-term population growth rates was the survival of large plants, whether vegetative or reproductive ( S6 Appendix ), as has been found for many other long-lived perennial plants (e.g. [ 27 , 81 ]). Even if reproduction by seed was not included in the simulations (seedlings could not reliably be distinguished in the field), one might assume that years of abundant flowering should also influence population growth rate positively and has contributed to the observed long-term stability of F .…”

Section: Discussionmentioning

confidence: 62%

“…Earlier studies have suggested that yearly weather variations can cause variation in flowering propensity in long-lived perennials (e.g. [27]). For F. meleagris, several authors have shown that variation in flowering is related to variation in wetness [18, [28][29][30].…”

Section: Plos Onementioning

confidence: 99%

“…Earlier studies have suggested that yearly weather variations can cause variation in flowering propensity in long-lived perennials (e.g. [ 27 ]). For F .…”

Section: Introductionmentioning

confidence: 99%

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Spatial heterogeneity ensures long-term stability in vegetation and Fritillaria meleagris flowering in Uppsala Kungsäng, a semi-natural meadow

Hytteborn

Carlsson²,

Svensson³

et al. 2023

PLoS ONE

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Semi-natural grasslands are becoming increasingly rare, and their vegetation may be affected by environmental changes and altered management. At Kungsängen Nature Reserve, a wet to mesic semi-natural meadow near Uppsala, Sweden, we analysed long-term changes in the vegetation using data from 1940, 1982, 1995 and 2016. We also analysed the spatial and temporal dynamics in the Fritillaria meleagris population based on countings of flowering individuals in 1938, 1981–1988 and 2016–2021. Between 1940 and 1982 the wet part of the meadow became wetter, which led to an increased cover of Carex acuta and pushed the main area of flowering of F. meleagris up towards the mesic part. Annual variation in the flowering propensity of F. meleagris (in May) was affected by temperature and precipitation in the phenological phases of growth and bud initiation (June in the previous year), shoot development (September in the previous year) and initiation of flowering (March–April). However, the response to weather was in opposite directions in the wet and mesic parts of the meadow, and the flowering population showed large year-to-year variation but no long-term trend. Variation in management (poorly documented) led to changes in different parts of the meadow, but the overall composition of the vegetation, species richness and diversity changed little after 1982. Species richness and species composition of the meadow vegetation, and the long-term stability of the F. meleagris population are maintained by the variation in wetness, highlighting the importance of spatial heterogeneity as an insurance against biodiversity loss in semi-natural grasslands and nature reserves generally.

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Section: Discussionmentioning

confidence: 62%

Section: Plos Onementioning

confidence: 99%

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Spatial heterogeneity ensures long-term stability in vegetation and Fritillaria meleagris flowering in Uppsala Kungsäng, a semi-natural meadow

Hytteborn

Carlsson²,

Svensson³

et al. 2023

PLoS ONE

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“…The result is that spatial replication facilitates the estimation of conspecific and heterospecific effects which can be used to project the effect of indirect climatic effects. Second, climate effects on populations should be modulated by soil conditions (Lindell et al, 2022; Nicolè et al, 2011). Reaching a general understanding on this subject could be achieved by stratifying spatial replicates by soil type, and fitting hierarchical models on the resulting data.…”

Section: Discussionmentioning

confidence: 99%

“…To increase ecological inference, we suggest that researchers explicitly consider the covariates that might mediate demographic responses to climate, such as soil conditions (Lindell et al, 2022; Nicolè et al, 2011) and competitors (Alexander et al, 2015), and examine the roles of these covariates in statistical analyses. We further suggest that spatial replicates should be chosen randomly, as this facilitates our ability to detect spatial autocorrelations that might occur due to unexpected, large-scale processes such as epidemics (Fortin et al, 1989).…”

Section: Discussionmentioning

confidence: 99%

Spatial replication can best advance our understanding of population responses to climate

Compagnoni

Evers

Knight

2022

Preprint

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Understanding the responses of plant populations dynamics to climatic variability is frustrated by the need for long term datasets that capture demographic responses to a range of climates. Here, we advocate for new studies that prioritize spatial over temporal replication, but without inferring the effect of temporal climatic gradients from spatial climatic gradients, as usually done in the so called space for time substitutions. Rather, we advocate to estimate the effects of climate by sampling replicate populations in locations with similar climate. We first use data analysis on spatial locations in the conterminous USA to assess how far apart spatial replicates should be from each other to minimize temporal correlations in climate. We find that spatial locations separated by 250 Km have moderate (0.5) correlations in annual precipitation. Second, we use simulations to demonstrate that spatial replication can lead to substantial gains in the range of climates sampled during a given set of years so long as the climate correlations between the populations are at low to moderate levels. Third, we use simulations to quantify how many spatial replicates would be necessary to achieve the same statistical power of a single-population, long-term data set under different strengths and directions of spatial correlations in climate between spatial replicates. Our results indicate that spatial replication is an untapped opportunity to study the effects of climate on demography and to rapidly fill important knowledge gaps in the field of population ecology.

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High‐resolution data are necessary to understand the effects of climate on plant population dynamics of a forest herb

Christiansen,

Römer,

Dahlgren

et al. 2023

Ecology

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Climate is assumed to strongly influence species distribution and abundance. Although the performance of many organisms is influenced by the climate in their immediate proximity, the climate data used to model their distributions often have a coarse spatial resolution. This is problematic because the local climate experienced by individuals might deviate substantially from the regional average. This problem is likely to be particularly important for sessile organisms like plants, and in environments where small‐scale variation in climate is large. To quantify the effect of local temperature on vital rates and population growth rates, we used temperature values measured at the local scale (in situ logger measures) and integral projection models with demographic data from 37 populations of the forest herb Lathyrus vernus across a wide latitudinal gradient in Sweden. To assess how spatial resolution of temperature data influences assessments of climate effects, we compared effects from models using local data with models using regionally aggregated temperature data at several spatial resolutions (≥1 km). Using local temperature data, we found that spring frost reduced the asymptotic population growth rate in the first of two annual transitions, and influenced survival in both transitions. Only one of the four regional estimates showed a similar negative effect of spring frost on population growth rate. Our results for a perennial forest herb show that analyses using regionally aggregated data often fail to identify effects of climate on population dynamics. This emphasizes the importance of using organism‐relevant estimates of climate when examining effects on individual performance and population dynamics, as well as when modelling species distributions. For sessile organisms that experience the environment over small spatial scales, this will require climate data at high spatial resolutions.This article is protected by copyright. All rights reserved.

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Weather‐driven demography and population dynamics of an endemic perennial plant during a 34‐year period

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 8 publications

References 66 publications

Spatial heterogeneity ensures long-term stability in vegetation and Fritillaria meleagris flowering in Uppsala Kungsäng, a semi-natural meadow

Spatial heterogeneity ensures long-term stability in vegetation and Fritillaria meleagris flowering in Uppsala Kungsäng, a semi-natural meadow

Spatial replication can best advance our understanding of population responses to climate

High‐resolution data are necessary to understand the effects of climate on plant population dynamics of a forest herb

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