scholarly journals The Ecology of Palm Genomes: Repeat-associated genome size expansion is constrained by aridity

2021 ◽  
Author(s):  
Rowan J. Schley ◽  
Jaume Pellicer ◽  
Xue-Jun Ge ◽  
Craig F. Barrett ◽  
Sidonie Bellot ◽  
...  
Keyword(s):  
Genome Size ◽  
Community Dynamics ◽  
Linear Models ◽  
Repetitive Element ◽  
Climatic Data ◽  
Ecological Communities ◽  
Stress Response Genes ◽  
Palm Species ◽  
Size Diversity ◽  
Size Limits

Genome size varies 2,400-fold across plants, influencing their evolution through changes in cell size and cell division rates which impact plants' environmental stress tolerance. Repetitive element expansion explains much genome size diversity, and the processes structuring repeat 'communities' are analogous to those structuring ecological communities. However, which environmental stressors influence repeat community dynamics has not yet been examined from an ecological perspective. We measured genome size and leveraged climatic data for 91% of genera within the ecologically diverse palm family (Arecaceae). We then generated genomic repeat profiles for 141 palm species, and analysed repeats using phylogenetically-informed linear models to explore relationships between repeat dynamics and environmental factors. We show that palm genome size and repeat 'community' composition are best explained by aridity. Specifically, EnSpm CACTA repeats were more abundant in palm species from wetter environments, which generally had larger genomes (>2.15Gbp/1C), suggesting amplification. In contrast, Ty1-copia Angela elements were more abundant in drier environments. Our results suggest water stress inhibits the expansion of repeats through selection on upper genome size limits. However, Ty1-copia Angela elements, which may associate with stress-response genes, have amplified in arid-adapted palm species. Overall, we provide novel evidence of climate influencing the assembly of repeat 'communities'.

First estimates of genome size in ribbon worms (phylum Nemertea) using flow cytometry and Feulgen image analysis densitometry

2014 ◽  
Vol 92 (10) ◽  
pp. 847-851 ◽  
Author(s):  
Kelly L. Mulligan ◽  
Terra C. Hiebert ◽  
Nicholas W. Jeffery ◽  
T. Ryan Gregory
Keyword(s):  
Flow Cytometry ◽  
Image Analysis ◽  
Body Size ◽  
Genome Size ◽  
Positive Relationship ◽  
Nuclear Dna ◽  
Nuclear Dna Content ◽  
Size Estimation ◽  
Size Diversity ◽  
Size Estimates

Ribbon worms (phylum Nemertea) are among several animal groups that have been overlooked in past studies of genome-size diversity. Here, we report genome-size estimates for eight species of nemerteans, including representatives of the major lineages in the phylum. Genome sizes in these species ranged more than fivefold, and there was some indication of a positive relationship with body size. Somatic endopolyploidy also appears to be common in these animals. Importantly, this study demonstrates that both of the most common methods of genome-size estimation (flow cytometry and Feulgen image analysis densitometry) can be used to assess genome size in ribbon worms, thereby facilitating additional efforts to investigate patterns of variability in nuclear DNA content in this phylum.

scholarly journals Seasonal dynamics of a generalist and a specialist predator on a single prey

2021 ◽  
pp. 1-20
Author(s):  
Noah Bolohan ◽  
Victor LeBlanc ◽  
Frithjof Lutscher
Keyword(s):  
Seasonal Variation ◽  
Community Dynamics ◽  
Alternative Prey ◽  
Ecological Communities ◽  
Season Length ◽  
Simplified Models ◽  
Hunting Behaviour ◽  
Temporal Averaging ◽  
Invasion Analysis ◽  
Insight Into

In ecological communities, the behaviour of individuals and the interaction between species may change between seasons, yet this seasonal variation is often not represented explicitly in mathematical models. As global change is predicted to alter season length and other climatic aspects, such seasonal variation needs to be included in models in order to make reasonable predictions for community dynamics. The resulting mathematical descriptions are nonautonomous models with a large number of parameters, and are therefore challenging to analyze. We present a model for two predators and one prey, whereby one predator switches hunting behaviour to seasonally include alternative prey when available. We use a combination of temporal averaging and invasion analysis to derive simplified models and determine the behaviour of the system, in particular to gain insight into conditions under which the two predators can coexist in a changing climate. We compare our results with numerical simulations of the temporally varying model.

Neural Models for Rainfall Forecasting

2010 ◽  
pp. 353-369
Author(s):  
A. Moreno ◽  
E. Soria ◽  
J. García ◽  
J. D. Martín ◽  
R. Magdalena
Keyword(s):  
Vegetation Cover ◽  
Linear Models ◽  
Moving Average ◽  
Network Models ◽  
Climatic Data ◽  
Neural Models ◽  
Rainfall Forecasting ◽  
Precipitation Regime ◽  
Neural Network Models ◽  
The Status

This chapter is focused on obtaining an optimal forecast of one month lagged rainfall in Spain. It is assessed by analyzing 22 years of both satellite observations of vegetation activity (e.g. NDVI) and climatic data (precipitation, temperature). The specific influence of non-spatial climatic indices such as NAO and SOI is also addressed. The approaches considered for rainfall forecasting include classical Auto-Regressive Moving-Average with Exogenous Inputs (ARMAX) models and Artificial Neural Networks (ANN), the so-called Multilayer Perceptron (MLP), in particular. The use of neural models is proven to be an adequate mathematical prediction tool in this problem due the non-linearity of the problem. These models enable us to predict, with one month foresight, the general rainfall dynamics, with average errors of 44 mm (RMSE) in a test series of 4 years with a rainfall standard deviation equal to 73 mm. Also, the sensitivity analysis in the neural network models reveals that observations in the status of the vegetation cover in previous months have a predictive power greater than other considered variables. Linear models yield average results of 55 mm (RMSE) although they need a large number of error terms (12) to obtain acceptable models. Nevertheless, they provide means for assessing the seasonal influence of the precipitation regime with the aid of linear dummy regression parameters, thereby offering an immediate interpretation (e.g. coherent maps) of the causality between vegetation cover and rainfall.

Ploidy Variation in Fraxinus L. (Oleaceae) of Eastern North America: Genome Size Diversity and Taxonomy in a Suddenly Endangered Genus

2018 ◽  
Vol 179 (5) ◽  
pp. 377-389 ◽  
Author(s):  
Alan T. Whittemore ◽  
Julian J. N. Campbell ◽  
Zheng-Lian Xia ◽  
Craig H. Carlson ◽  
Daniel Atha ◽  
...  
Keyword(s):  
North America ◽  
Genome Size ◽  
Eastern North America ◽  
Size Diversity

An exploration of genome size diversity in dragonflies and damselflies (Insecta: Odonata)

2009 ◽  
Vol 278 (3) ◽  
pp. 163-173 ◽  
Author(s):  
A. M. Ardila‐Garcia ◽  
T. R. Gregory
Keyword(s):  
Genome Size ◽  
Size Diversity

scholarly journals Genome size diversity in orchids: consequences and evolution

2009 ◽  
Vol 104 (3) ◽  
pp. 469-481 ◽  
Author(s):  
I. J. Leitch ◽  
I. Kahandawala ◽  
J. Suda ◽  
L. Hanson ◽  
M. J. Ingrouille ◽  
...  
Keyword(s):  
Genome Size ◽  
Size Diversity

scholarly journals A Holling Functional Response Model for Mapping QTLs Governing Interspecific Interactions

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-Yu Zhang ◽  
Huiying Gong ◽  
Qing Fang ◽  
Xuli Zhu ◽  
Libo Jiang ◽  
...  
Keyword(s):  
Functional Response ◽  
Species Interactions ◽  
Community Dynamics ◽  
Interspecific Interactions ◽  
Microbial Interactions ◽  
Ecological Communities ◽  
Response Model ◽  
Ecological Interactions ◽  
Dynamic Complexity ◽  
Genome Level

Genes play an important role in community ecology and evolution, but how to identify the genes that affect community dynamics at the whole genome level is very challenging. Here, we develop a Holling type II functional response model for mapping quantitative trait loci (QTLs) that govern interspecific interactions. The model, integrated with generalized Lotka-Volterra differential dynamic equations, shows a better capacity to reveal the dynamic complexity of inter-species interactions than classic competition models. By applying the new model to a published mapping data from a competition experiment of two microbial species, we identify a set of previously uncharacterized QTLs that are specifically responsible for microbial cooperation and competition. The model can not only characterize how these QTLs affect microbial interactions, but also address how change in ecological interactions activates the genetic effects of the QTLs. This model provides a quantitative means of predicting the genetic architecture that shapes the dynamic behavior of ecological communities.

scholarly journals The Dynamic Hypercube as a Niche Community Model

2021 ◽  
Vol 9 ◽  
Author(s):  
John M. Halley ◽  
Stuart L. Pimm
Keyword(s):  
Community Dynamics ◽  
Neutral Theory ◽  
Species Abundance ◽  
Ecological Communities ◽  
Evolutionary Time ◽  
Community Model ◽  
Theory Of Island Biogeography ◽  
Species Abundance Distributions ◽  
Hypercube Model ◽  
Zero Sum

Different models of community dynamics, such as the MacArthur–Wilson theory of island biogeography and Hubbell’s neutral theory, have given us useful insights into the workings of ecological communities. Here, we develop the niche-hypervolume concept of the community into a powerful model of community dynamics. We describe the community’s size through the volume of the hypercube and the dynamics of the populations in it through the fluctuations of the axes of the niche hypercube on different timescales. While the community’s size remains constant, the relative volumes of the niches within it change continuously, thus allowing the populations of different species to rise and fall in a zero-sum fashion. This dynamic hypercube model reproduces several key patterns in communities: lognormal species abundance distributions, 1/f-noise population abundance, multiscale patterns of extinction debt and logarithmic species-time curves. It also provides a powerful framework to explore significant ideas in ecology, such as the drift of ecological communities into evolutionary time.

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