Results 151 to 160 of about 460,152 (328)

Wetland occupancy by duck broods in cropland‐dominated landscapes of the United States Prairie Pothole Region

open access: yesThe Journal of Wildlife Management, Volume 87, Issue 2, February 2023., 2023
We evaluated how wetland occupancy by duck broods varied across crop‐dominated landscapes of the Prairie Pothole Region (PPR) in the United States to inform conservation strategies in the face of widespread land use alterations and climate change. We found about 4 in 10 small wetlands in crop‐dominated landscapes within the PPR were used by duck broods
Blake J. Mitchell   +5 more
wiley   +1 more source

Pathways for socio-economic system transitions expressed as a Markov chain. [PDF]

open access: yesPLoS One, 2023
Schweizer VJ   +4 more
europepmc   +1 more source

On Obtaining Sharp Bounds of the Rate of Convergence for a Class of Continuous-Time Markov Chains [PDF]

open access: yesarXiv, 2019
We study inhomogeneous continuous-time weakly ergodic Markov chains with a finite state space. We introduce the notion of a Markov chain with the regular structure of an infinitesimal matrix and study the sharp upper bounds on the rate of convergence for such class of Markov chains.
arxiv  

Effects of spatially heterogeneous lakeside development on nearshore biotic communities in a large, deep, oligotrophic lake

open access: yesLimnology and Oceanography, Volume 67, Issue 12, Page 2649-2664, December 2022., 2022
Abstract Sewage released from lakeside development can reshape ecological communities. Nearshore periphyton can rapidly assimilate sewage‐associated nutrients, leading to increases of filamentous algal abundance, thus altering both food abundance and quality for grazers.
Michael F. Meyer   +11 more
wiley   +1 more source

A quantum parallel Markov chain Monte Carlo. [PDF]

open access: yesJ Comput Graph Stat, 2023
Holbrook AJ.
europepmc   +1 more source

Bounds on Lifting Continuous Markov Chains to Speed Up Mixing [PDF]

open access: yesarXiv, 2016
It is often possible to speed up the mixing of a Markov chain $\{ X_{t} \}_{t \in \mathbb{N}}$ on a state space $\Omega$ by \textit{lifting}, that is, running a more efficient Markov chain $\{ \hat{X}_{t} \}_{t \in \mathbb{N}}$ on a larger state space $\hat{\Omega} \supset \Omega$ that projects to $\{ X_{t} \}_{t \in \mathbb{N}}$ in a certain sense. In
arxiv  

Boundary theory for recurrent Markov chains [PDF]

open access: bronze, 1963
John G. Kemeny, J. Laurie Snell
openalex   +2 more sources

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