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共检索到14条 ,权限内显示50条;
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Data from: Spatial autocorrelation in fitness affects the estimation of natural selection in the wild
- 负责人:
- DOI:
- doi:10.5061/dryad.pm86c
- 摘要:
- -based exponential covariance function, two simultaneous autoregressive models (SAR, the lagged-response model (SAR-lag) and the spatial error model (SAR
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Lean-season primary productivity and heat dissipation as key drivers of geographic body-size variation in a widespread marsupial
- 负责人:
- DOI:
- doi:10.5061/dryad.gq264
- 摘要:
- with increasing mean summer maximum temperature. Spatial autoregression coefficients estimated from the simultaneous autoregressive models were always high
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: A spatially explicit hierarchical model to characterize population viability
- 负责人:
- Campbell, Steven
- 关键词:
- capture-recapture CAR model demography multi-state model population viability analysis recruitment Sonoran desert tortoise spatial autoregressive model survival spatial variation
- DOI:
- doi:10.5061/dryad.v0q5035
- 摘要:
- , spatial autoregressive model for capture-recapture data from multiple locations to obtain spatially explicit estimates of adult survival (Φad), juvenile survival (Φjuv
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Spatio-temporally explicit model averaging for forecasting of Alaskan groundfish catch
- 负责人:
- Correia, Hannah
- DOI:
- doi:10.5061/dryad.s23g7bc
- 摘要:
- forecasting models and a modern spatial prediction model: the autoregressive integrated moving averages (ARIMA) model, the Bayesian hierarchical model
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Validating dispersal distances inferred from autoregressive occupancy models with genetic parentage assignments
- 负责人:
- Hall, Laurie
- DOI:
- doi:10.5061/dryad.3bb81dv
- 摘要:
- ween parent-offspring dyads identified with 16 microsatellites. 3.We used a novel autoregressive multi-season occupancy model that accounted for bot
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Amphibian functional diversity is related to high annual precipitation and low precipitation seasonality in the New World
- 负责人:
- DOI:
- doi:10.5061/dryad.nk0bj96
- 摘要:
- of spatial autoregressive models (SAR). Results. Based on 212 different functional attributes for 2776 species, we found that functional diversity has a latitudinal gr
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Differences in spatial synchrony and interspecific concordance inform guild-level population trends for aerial insectivorous birds
- 负责人:
- 关键词:
- aerial insectivorous birds population synchrony spatial concordance North American Breeding Bird Survey
- DOI:
- doi:10.5061/dryad.364mb
- 摘要:
- were derived from Bayesian hierarchical models with continuous autoregressive spatial structures. Stratum-level spatial concordance among species
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Primary productivity explains size variation across the Pallid bat’s (Antrozous pallidus) western geographic range
- 负责人:
- Kelly, Rochelle
- DOI:
- doi:10.5061/dryad.c5805
- 摘要:
- t variation in resource availability may be a key factor underlying spatial patterns in size, morphology and, possibly, feeding performance within wide
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Overcompensation and phase effects in a cyclic common vole population: between first and second-order cycles
- 负责人:
- DOI:
- doi:10.5061/dryad.2hk46
- 摘要:
- autoregressive model, we would conclude only that negative delayed density-dependence exists. The additive structure of this model cannot show when delayed DD occurs
![](http://agri.nais.net.cn/resources/front/images/source_91.jpg)
Data from: Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure
- 负责人:
- DOI:
- doi:10.5061/dryad.737gk
- 摘要:
- h as autoregressive models, generalized least squares, or mixed models are used. Block cross-validation, where data are split strategically rather than randomly, can address