45629
2016
2016
eng
1313
1323
11
209
article
Wiley-Blackwell
Hoboken
1
--
--
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Niche dynamics of alien species do not differ among sexual and apomictic flowering plants
We compiled global occurrence data sets of 13 congeneric sexual and apomictic species pairs, and used principal components analysis (PCA) and kernel smoothers to compare changes in climatic niche optima, breadths and unfilling/expansion between native and alien ranges. Niche change metrics were compared between sexual and apomictic species. All 26 species showed changes in niche optima and/or breadth and 14 species significantly expanded their climatic niches. However, we found no effect of the reproductive system on niche dynamics. Instead, species with narrower native niches showed higher rates of niche expansion in the alien ranges. Our results suggest that niche shifts are frequent in plant invasions but evolutionary potential may not be of major importance for such shifts. Niche dynamics rather appear to be driven by changes of the realized niche without adaptive change of the fundamental climatic niche.
New phytologist : international journal of plant science
10.1111/nph.13694
26508329
0028-646X
1469-8137
wos2016:2019
WOS:000373378000041
Dellinger, AS (reprint author), Univ Vienna, Dept Bot & Biodivers Res, Rennweg 14, A-1030 Vienna, Austria., agnes.dellinger@univie.ac.at
DFG [Ho-4395/1-1, SFB 990-B12, KL-1866/3-1, KL-1866/9-1]; Austrian Science Fund (FWF) [I1189-B16]; Centre of Excellence PLADIAS [14-36079G]; Czech Academy of Sciences [RVO 67985939]; Praemium Academiae award from The Czech Academy of Sciences; Czech Science Foundation [14-36079G]
importub
2020-03-22T20:08:01+00:00
filename=package.tar
f781c108c774fe44880fdf776d9dd9bd
Agnes S. Dellinger
Franz Essl
Diego Hojsgaard
Bernhard Kirchheimer
Simone Klatt
Wayne Dawson
Jan Pergl
Petr Pysek
Mark van Kleunen
Ewald Weber
Marten Winter
Elvira Hoerandl
Stefan Dullinger
eng
uncontrolled
adaptation
eng
uncontrolled
asexual reproduction
eng
uncontrolled
niche shifts
eng
uncontrolled
plant invasion
eng
uncontrolled
reproductive system
eng
uncontrolled
species distribution modelling
Institut für Biochemie und Biologie
Referiert
Import
36183
2012
2012
eng
293
304
12
2
21
article
Wiley-Blackwell
Malden
1
--
--
--
Forecasting species ranges by statistical estimation of ecological niches and spatial population dynamics
Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties.
Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation.
Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.
Global ecology and biogeography : a journal of macroecology
10.1111/j.1466-8238.2011.00663.x
1466-822X
wos:2011-2013
WOS:000298912900018
Pagel, J (reprint author), Univ Potsdam, Inst Biochem & Biol, Maulbeerallee 2, D-14469 Potsdam, Germany., jpagel@uni-potsdam.de
University of Potsdam Graduate Initiative on Ecological Modelling
(UPGradE); German Federal Agency for Nature Conservation; European
Commission [GOCE-CT-2003-506675, 226701]; European Union
[MTKD-CT-2006-042261]
Jörn Pagel
Frank Martin Schurr
eng
uncontrolled
Biogeography
eng
uncontrolled
ecological forecasts
eng
uncontrolled
global change
eng
uncontrolled
hierarchical Bayesian statistics
eng
uncontrolled
long-distance dispersal
eng
uncontrolled
niche theory
eng
uncontrolled
process-based model
eng
uncontrolled
range shifts
eng
uncontrolled
spatial demography
eng
uncontrolled
species distribution modelling
Institut für Biochemie und Biologie
Referiert
34646
2013
2013
eng
1366
1379
14
11
19
article
Wiley-Blackwell
Hoboken
1
--
--
--
The importance of correcting for sampling bias in MaxEnt species distribution models
AimAdvancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better-surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet Viverra tangalunga in Borneo.
LocationBorneo, Southeast Asia.
MethodsWe collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range-restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north-eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas.
ResultsSpatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased.
Main ConclusionsWe conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
Diversity & distributions : a journal of biological invasions and biodiversity
10.1111/ddi.12096
1366-9516
1472-4642
wos:2011-2013
WOS:000325542600003
Kramer-Schadt, S (reprint author), Leibniz Inst Zoo & Wildlife Res, Alfred Kowalke Str 17, D-10315 Berlin, Germany., kramer@izw-berlin.de; wilting@izw-berlin.de
Benta Wawasan Sdn Bhd; British Ecological Society; Chester Zoo The North
England Zoological Society; Cleveland Metro-parks; Clouded Leopard
Project; Columbus Zoo; Department of Wildlife, Fisheries and
Aquaculture, Flora Blossom Sdn Bhd; Forest and Wildlife Research Center,
Mississippi State University; Houston Zoo; KTS Plantation Sdn Bhd;
Leibniz Institute for Zoo and Wildlife Research; Malaysia Airlines;
Nashville Zoo; Point Defiance Zoo and Aquarium; Shared Earth Foundation;
Usitawi Network; Wild Cat Club; WWF-Germany; WWF-Malaysia;
Recanati-Kaplan Foundation; Woodspring Trust
Stephanie Kramer-Schadt
Jürgen Niedballa
John D. Pilgrim
Boris Schröder-Esselbach
Jana Lindenborn
Vanessa Reinfelder
Milena Stillfried
Ilja Heckmann
Anne K. Scharf
Dave M. Augeri
Susan M. Cheyne
Andrew J. Hearn
Joanna Ross
David W. Macdonald
John Mathai
James Eaton
Andrew J. Marshall
Gono Semiadi
Rustam Rustam
Henry Bernard
Raymond Alfred
Hiromitsu Samejima
J. W. Duckworth
Christine Breitenmoser-Wuersten
Jerrold L. Belant
Heribert Hofer
Andreas Wilting
eng
uncontrolled
Borneo
eng
uncontrolled
carnivora
eng
uncontrolled
conservation planning
eng
uncontrolled
ecological niche modelling
eng
uncontrolled
maximum entropy (MaxEnt)
eng
uncontrolled
sampling bias
eng
uncontrolled
Southeast Asia
eng
uncontrolled
species distribution modelling
eng
uncontrolled
viverridae
Institut für Geowissenschaften
Referiert
Institut für Erd- und Umweltwissenschaften