1-23 of about 23 matches for site:peerj.com site:peerj.com site:peerj.com site:peerj.com site:peerj.com key factors
Coupling effect of key factors on ecosystem services in border areas: a study of the Pu’er region, S
https://peerj.com/articles/17015/
Coupling effect of key factors on ecosystem services in border areas: a study of
https://peerj.com/articles/5347/
both the magnitude of thermal stress and the duration are key factors in bleaching
Predicting the current fishable habitat distribution of Antarctic toothfish (Dissostichus mawsoni) a
https://peerj.com/articles/17131/
conditions in the Southern Ocean. This study aims to: (1) identify key factors influencing D. mawsoni
Unveiling the aesthetic secrets: exploring connections between genetic makeup, chemical, and environ
https://peerj.com/articles/17238/
Unveiling the aesthetic secrets: exploring connections between genetic makeup, chemical, and environmental factors for enhancing
The timing mega-study: comparing a range of experiment generators, both lab-based and online [PeerJ]
https://peerj.com/articles/9414/
tests in order to minimize the timing errors caused by external factors (the keyboard
https://peerj.com/sections/global-health/
surveillance of HBV, the study provides valuable insights into the various factors that need to
https://peerj.com/subjects/anthropology/
Tomáš Kalina 16,378 views · 1,819 downloads Manual restrictions on Palaeolithic technological behaviours Alastair J.M. Key , Christopher J. Dunmore 15
https://peerj.com/articles/16811/
Shuai Yuan 1 , 2 , 3 , Xiaodong Wu 1 , 2 , 3 , Heping Fu 1 , 2 , 3 1 Key Laboratory of Grassland
https://peerj.com/sections/paleontology-evolutionary-science/
a major extant clade." Mark Young, Handling Editor 29 February 2024 Downsizing a heavyweight: factors and methods
Feature tuning improves MAXENT predictions of the potential distribution of Pedicularis longiflora R
https://peerj.com/articles/13337/
Jianghua Zheng 1 , 2 1 College of Geographical Sciences, Xinjiang University , Urumqi , China 2 Key Laboratory of Oasis
https://peerj.com/articles/16783/reviews/
a map, but it's actually not a map. Notice that it lacks key information, such as coordinates
https://peerj.com/articles/6926/
Cao 1 , 2 , Zipeng Zhang 1 , 2 , Jie Liu 1 , 2 , Xiaohang Li 1 , 2 1 Key Laboratory of Smart
https://peerj.com/articles/12122/
Fig. 1 ). Figure 1: Diagram of Zhangjiakou Research Area. Zhangjiakou is a key area to maintain
Assessing insect responses to climate change: What are we testing for? Where should we be heading? [
https://peerj.com/articles/11/
about general responses. We examined how research on climate change affecting insects is being assessed, what factors are being tested and
https://peerj.com/articles/175/
had been reused at least once by third parties. Conclusion. After accounting for other factors affecting citation rate, we
Integrating structure-from-motion photogrammetry with geospatial software as a novel technique for q
https://peerj.com/articles/1077/
1997 ; Fisher et al., 2007 ; Alvarez-Filip et al., 2009 ; Zawada, Piniak & Hearn, 2010 ). These factors have a reciprocal
https://peerj.com/articles/12404/
Sæther & Bakke, 2000 ). This makes the knowledge of adult survival rates key to predicting
https://peerj.com/articles/4428/
could be used to simultaneously produce food while conserving our natural resource base: two factors that are pitted against
https://peerj.com/articles/5096/
statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR
https://peerj.com/articles/9414.html
type of “keypress”, controlling the type of response collected (i.e., key down vs key up
Exact integer linear programming solvers outperform simulated annealing for solving conservation pla
https://peerj.com/articles/9258/
the EILP formulation in Beyer et al. (2016) and Appendix S2 . Three key parameters that are important
https://peerj.com/articles/17209/
increased human disturbances, noise and light pollution, and removal of key habitat elements, which can
High-resolution density assessment assisted by deep learning of Dendrophyllia cornigera (Lamarck, 18
https://peerj.com/articles/17080/
a novel approach to high-resolution density distribution mapping of two key species of the