scholarly journals Functional spatial scale of community composition change in response to windthrow disturbance in a deciduous temperate forest

2007 ◽  
Vol 23 (2) ◽  
pp. 249-258 ◽  
Author(s):  
Toshihide Hirao ◽  
Masashi Murakami ◽  
Hiroyuki Oguma
2014 ◽  
Vol 83 ◽  
pp. 109-115 ◽  
Author(s):  
Saori Fujii ◽  
Seikoh Saitoh ◽  
Hiroshi Takeda

2020 ◽  
Vol 48 ◽  
pp. 100985
Author(s):  
Iñaki Odriozola ◽  
Tijana Martinovic ◽  
Barbara Doreen Bahnmann ◽  
David Ryšánek ◽  
Tereza Mašínová ◽  
...  

2016 ◽  
Vol 93 (2) ◽  
pp. fiw223 ◽  
Author(s):  
Tereza Mašínová ◽  
Barbara Doreen Bahnmann ◽  
Tomáš Větrovský ◽  
Michal Tomšovský ◽  
Kristina Merunková ◽  
...  

2012 ◽  
Vol 13 (8) ◽  
pp. 663-672 ◽  
Author(s):  
Kadri Koorem ◽  
Ülle Saks ◽  
Virve Sõber ◽  
Annika Uibopuu ◽  
Maarja Öpik ◽  
...  

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e111667 ◽  
Author(s):  
Nicolas Chemidlin Prévost-Bouré ◽  
Samuel Dequiedt ◽  
Jean Thioulouse ◽  
Mélanie Lelièvre ◽  
Nicolas P. A. Saby ◽  
...  

2021 ◽  
Vol 18 (6) ◽  
pp. 2213-2220
Author(s):  
Shawn D. Taylor ◽  
Dawn M. Browning

Abstract. Grasslands provide many important ecosystem services globally, and projecting grassland productivity in the coming decades will provide valuable information to land managers. Productivity models can be well calibrated at local scales but generally have some maximum spatial scale in which they perform well. Here we evaluate a grassland productivity model to find the optimal spatial scale for parameterization and thus for subsequently applying it in future productivity projections for North America. We also evaluated the model on new vegetation types to ascertain its potential generality. We find the model most suitable when incorporating only grasslands, as opposed to also including agriculture and shrublands, and only in the Great Plains and eastern temperate forest ecoregions of North America. The model was not well suited to grasslands in North American deserts or northwest forest ecoregions. It also performed poorly in agriculture vegetation, likely due to management activities, and shrubland vegetation, likely because the model lacks representation of deep water pools. This work allows us to perform long-term projections in areas where model performance has been verified, with gaps filled in by future modeling efforts.


Author(s):  
Lucie A Malard ◽  
Muhammad Zohaib Anwar ◽  
Carsten S Jacobsen ◽  
David A Pearce

Bacterial community composition is largely influenced by environmental factors, and this applies to the Arctic region. However, little is known about the role of spatial factors in structuring such communities. In this study, we evaluated the influence of spatial scale on bacterial community structure across an Arctic landscape. Our results showed that spatial factors accounted for approximately 10% of the variation at the landscape scale, equivalent to observations across the whole Arctic region, suggesting that while the role and magnitude of other processes involved in community structure may vary, the role of dispersal may be stable globally in the region. We assessed dispersal limitation by identifying the spatial autocorrelation distance, standing at approximately 60 m, which would be required in order to obtain fully independent samples and may inform future sampling strategies in the region. Finally, indicator taxa with strong statistical correlations with environment variables were identified. However, we showed that these strong taxa-environment associations may not always be reflected in the geographical distribution of these taxa. IMPORTANCE The significance of this study is threefold. It investigated the influence of spatial scale on the soil bacterial community composition across a typical Arctic landscape and demonstrated that conclusions reached when examining the influence of specific environmental variables on bacterial community composition are dependent upon the spatial scales over which they are investigated. This study identified a dispersal limitation (spatial autocorrelation) distance of approximately 60 m, required to obtain samples with fully independent bacterial communities, and therefore, should serve to inform future sampling strategies in the region and potentially elsewhere. The work also showed that strong taxa-environment statistical associations may not be reflected in the observed landscape distribution of the indicator taxa.


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