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Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty
负责人:
关键词:
Electrona antarctica;climate model;IPCC;projection;uncertainty;Species distribution modelling;climate change;sea surface temperature
DOI:
doi:10.5061/dryad.4f98t
摘要:
future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its thr
Data from: Assimilating MODIS data-derived minimum input data set and water stress factors into CERES-Maize model improves regional corn yield predictions
负责人:
关键词:
DOI:
doi:10.5061/dryad.7ms8db6
摘要:
ng crop growth and yield at a regional scale. To improve the accuracy and precision of regional corn yield predictions, a simple approach for assimilati
Data from: How does spatial resolution affect model performance? A case for ensemble approaches for marine benthic mesophotic communities
负责人:
关键词:
spatial grain;Coral;Grid Size;Macroalgae;Species distribution modelling;sponges;spatial scale
DOI:
doi:10.5061/dryad.nh07v50
摘要:
oducing distribution models. Identifying the most relevant grid size and being aware of the influence it may have will provide more accurate predictions of the distributions
Data from: Input matters matter: bioclimatic consistency to map more reliable species distribution models
负责人:
关键词:
bioclimatic consistency;bioclimatic congruence;current
DOI:
doi:10.5061/dryad.6kv7k29
摘要:
) discrepancies among SDMs predictions depending on the chosen bioclimatic database. Finally, iv) we propose a strategy to assess bioclimatic cons
Data from: The seasonal climate niche predicts phenology and distribution of an ephemeral annual plant, Mollugo verticillata
负责人:
关键词:
climate change;germination phenology;herbarium;seasonal climate niche;MaxEnt;ecological niche model;flowering phenology;Mollugo verticillata;historical records;niche breadth;1896-2069
DOI:
doi:10.5061/dryad.0s9j3
摘要:
a novel species distribution model using herbarium records and monthly weather data, which predicts not only where a short-lived species should
Data from: The emergent geography of biophysical dispersal barriers across the Indo-West Pacific
负责人:
关键词:
connectivity;barriers;biophysical modelling;Dispersal;Network analysis;Coral reef
DOI:
doi:10.5061/dryad.24tt2
摘要:
ng the location of barriers and their capacity to filter taxa. Additionally, to compare model predictions with previously described barriers and build a more thoro
Data from: The evolution of bet hedging in response to local ecological conditions
负责人:
关键词:
competition;Ecology: evolutionary;Life history;Life history: evolution;bet hedging;Stochastic environments;Ecology: population;Life history: theory;Curculio elephas;Adaptation;Fitness
DOI:
doi:10.5061/dryad.g7jq6
摘要:
environmental perturbations of the underlying physiological mechanism. Using a model that includes these constraints, we predict the whole distribution of dormancy frequencies
Data from: Generalist predator's niche shifts reveal ecosystem changes in an experimentally fragmented landscape
负责人:
关键词:
stable isotopes;Lampropholis guichenoti;trophic structure;metacommunity
DOI:
doi:10.5061/dryad.56b81
摘要:
d stable isotopes of a generalist predator skink to test predictions from spatial theory on trophic structure and to quantify abiotic changes associated with
Data from: Does metabolism constrain bird and mammal ranges and predict shifts in response to climate change?
负责人:
关键词:
Mammalia;metabolic expansibility;range limit;metabolic scope;Metabolism;Aves;Holocene
DOI:
doi:10.5061/dryad.68fr52p
摘要:
on) highlight the need for more detailed, taxa?specific mechanistic models. Even coarse considerations of metabolism will likely lead to improved predictions ove
Data from: Climate-driven range shifts explain the distribution of extant gene pools and predict future loss of unique lineages in a marine
负责人:
关键词:
rear edge;Fucus vesiculosus;niche modeling;climate change;range shifts;genetic diversity;Holocene
DOI:
doi:10.5061/dryad.62797
摘要:
of the global genetic pool, by comparing present geographic distribution of genetic diversity and differentiation with predictive Species Distribution Model

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