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Dynamics of Weeds in the Soil Seed Bank: A Hidden Markov Model to Estimate Life History Traits from Standing Plant Time Series.

Borgy B, Reboud X, Peyrard N, Sabbadin R, Gaba S - PLoS ONE (2015)

Bottom Line: However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes.Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values.There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal).

View Article: PubMed Central - PubMed

Affiliation: INRA, UMR1347 Agroécologie, Dijon, France; Centre National de Recherche Scientifique, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, Montpellier, France.

ABSTRACT
Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies.

No MeSH data available.


Related in: MedlinePlus

Life history traits and IndVal of weed species with the four crop types.Species survival rates (s), germination rates (σ) and seed production per plant (φ) are presented by black, red and green polygons for four crop types, respectively (WC = winter cereals, OR = oilseed rape, M = maize and SF = sunflower). Values are scaled by dividing each value by the maximum value with the four crop types. For each species, each scaled Life History Trait (LHT) varies between 0 and 1 and the polygon is shifted in the direction of the crop(s) where it has its highest estimated success. Dashed polygons represent values equal to 1 for the three life history traits, i.e., maximum value for all species for each LHT. Blue polygons represent the indicator values (IndVal) of species with the four crop types (scaled by the maximum value of species with the four crop types).
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pone.0139278.g003: Life history traits and IndVal of weed species with the four crop types.Species survival rates (s), germination rates (σ) and seed production per plant (φ) are presented by black, red and green polygons for four crop types, respectively (WC = winter cereals, OR = oilseed rape, M = maize and SF = sunflower). Values are scaled by dividing each value by the maximum value with the four crop types. For each species, each scaled Life History Trait (LHT) varies between 0 and 1 and the polygon is shifted in the direction of the crop(s) where it has its highest estimated success. Dashed polygons represent values equal to 1 for the three life history traits, i.e., maximum value for all species for each LHT. Blue polygons represent the indicator values (IndVal) of species with the four crop types (scaled by the maximum value of species with the four crop types).

Mentions: We observed the expected relationships between the estimated values of LHT and both the indicator values (IndVal) and the functional traits. For all crop types, the relative establishment rate of the species was highly positively correlated with the species IndVal (Figs 2 and 3). The estimated average seed production (φa) was not correlated with seed mass (Spearman’s correlation unilateral test, n = 18, ρ = -0.31, P-value = 0.104). Conversely, the estimated average seed survival rate (sa) was positively correlated with the seed coat thickness (Spearman’s correlation unilateral test, n = 9, ρ = 0.73, P-value = 0.015) even though the sample size was small (seed coat thickness values were only available for half of the species; S4 Fig).


Dynamics of Weeds in the Soil Seed Bank: A Hidden Markov Model to Estimate Life History Traits from Standing Plant Time Series.

Borgy B, Reboud X, Peyrard N, Sabbadin R, Gaba S - PLoS ONE (2015)

Life history traits and IndVal of weed species with the four crop types.Species survival rates (s), germination rates (σ) and seed production per plant (φ) are presented by black, red and green polygons for four crop types, respectively (WC = winter cereals, OR = oilseed rape, M = maize and SF = sunflower). Values are scaled by dividing each value by the maximum value with the four crop types. For each species, each scaled Life History Trait (LHT) varies between 0 and 1 and the polygon is shifted in the direction of the crop(s) where it has its highest estimated success. Dashed polygons represent values equal to 1 for the three life history traits, i.e., maximum value for all species for each LHT. Blue polygons represent the indicator values (IndVal) of species with the four crop types (scaled by the maximum value of species with the four crop types).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4591344&req=5

pone.0139278.g003: Life history traits and IndVal of weed species with the four crop types.Species survival rates (s), germination rates (σ) and seed production per plant (φ) are presented by black, red and green polygons for four crop types, respectively (WC = winter cereals, OR = oilseed rape, M = maize and SF = sunflower). Values are scaled by dividing each value by the maximum value with the four crop types. For each species, each scaled Life History Trait (LHT) varies between 0 and 1 and the polygon is shifted in the direction of the crop(s) where it has its highest estimated success. Dashed polygons represent values equal to 1 for the three life history traits, i.e., maximum value for all species for each LHT. Blue polygons represent the indicator values (IndVal) of species with the four crop types (scaled by the maximum value of species with the four crop types).
Mentions: We observed the expected relationships between the estimated values of LHT and both the indicator values (IndVal) and the functional traits. For all crop types, the relative establishment rate of the species was highly positively correlated with the species IndVal (Figs 2 and 3). The estimated average seed production (φa) was not correlated with seed mass (Spearman’s correlation unilateral test, n = 18, ρ = -0.31, P-value = 0.104). Conversely, the estimated average seed survival rate (sa) was positively correlated with the seed coat thickness (Spearman’s correlation unilateral test, n = 9, ρ = 0.73, P-value = 0.015) even though the sample size was small (seed coat thickness values were only available for half of the species; S4 Fig).

Bottom Line: However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes.Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values.There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal).

View Article: PubMed Central - PubMed

Affiliation: INRA, UMR1347 Agroécologie, Dijon, France; Centre National de Recherche Scientifique, Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, Montpellier, France.

ABSTRACT
Predicting the population dynamics of annual plants is a challenge due to their hidden seed banks in the field. However, such predictions are highly valuable for determining management strategies, specifically in agricultural landscapes. In agroecosystems, most weed seeds survive during unfavourable seasons and persist for several years in the seed bank. This causes difficulties in making accurate predictions of weed population dynamics and life history traits (LHT). Consequently, it is very difficult to identify management strategies that limit both weed populations and species diversity. In this article, we present a method of assessing weed population dynamics from both standing plant time series data and an unknown seed bank. We use a Hidden Markov Model (HMM) to obtain estimates of over 3,080 botanical records for three major LHT: seed survival in the soil, plant establishment (including post-emergence mortality), and seed production of 18 common weed species. Maximum likelihood and Bayesian approaches were complementarily used to estimate LHT values. The results showed that the LHT provided by the HMM enabled fairly accurate estimates of weed populations in different crops. There was a positive correlation between estimated germination rates and an index of the specialisation to the crop type (IndVal). The relationships between estimated LHTs and that between the estimated LHTs and the ecological characteristics of weeds provided insights into weed strategies. For example, a common strategy to cope with agricultural practices in several weeds was to produce less seeds and increase germination rates. This knowledge, especially of LHT for each type of crop, should provide valuable information for developing sustainable weed management strategies.

No MeSH data available.


Related in: MedlinePlus