sampbias , a method for quantifying geographic sampling biases in species distribution data

Linking democracy and biodiversity conservation: Empirical evidence and research gaps

(2019) Oskar Rydén et al.   AMBIO

Sampling bias correction in species distribution models by quasi-linear Poisson point process

(2019) Osamu Komori et al.   Ecological Informatics

Accessibility maps as a tool to predict sampling bias in historical biodiversity occurrence records

(2018) Sophie Monsarrat et al.   ECOGRAPHY

Widespread sampling biases in herbaria revealed from large-scale digitization

(2017) Barnabas H. Daru et al.   NEW PHYTOLOGIST

Multidimensional biases, gaps and uncertainties in global plant occurrence information

(2016) Carsten Meyer et al.   ECOLOGY LETTERS

Uncertainty analysis of crowd-sourced and professionally collected field data used in species distribution models of Taiwanese moths

(2015) Yu-Pin Lin et al.   BIOLOGICAL CONSERVATION

Bias and information in biological records

(2015) Nick J. B. Isaac et al.   BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY

spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models

(2015) Matthew E. Aiello-Lammens et al.   ECOGRAPHY

Estimation of spatial sampling effort based on presence-only data and accessibility

(2015) Daniel Fernández et al.   ECOLOGICAL MODELLING

Global priorities for an effective information basis of biodiversity distributions

(2015) Carsten Meyer et al.   Nature Communications

Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot

(2015) Kristine Engemann et al.   Ecology and Evolution

Attenuation of species abundance distributions by sampling

(2015) H. Shimadzu et al.   Royal Society Open Science

Accounting for spatially biased sampling effort in presence-only species distribution modelling

(2014) Jessica Stolar et al.   DIVERSITY AND DISTRIBUTIONS

Environmental filters reduce the effects of sampling bias and improve predictions of ecological niche models

(2014) Sara Varela et al.   ECOGRAPHY

Spatial filtering to reduce sampling bias can improve the performance of ecological niche models

(2014) Robert A. Boria et al.   ECOLOGICAL MODELLING

Environmental and socio-economic factors shaping the geography of floristic collections in China

(2014) Wenjing Yang et al.   GLOBAL ECOLOGY AND BIOGEOGRAPHY

Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias

(2014) Yoan Fourcade et al.   PLoS One

Bias correction in species distribution models: pooling survey and collection data for multiple species

(2014) William Fithian et al.   Methods in Ecology and Evolution

Species-people correlations and the need to account for survey effort in biodiversity analyses

(2013) A. Márcia Barbosa et al.   DIVERSITY AND DISTRIBUTIONS

The importance of correcting for sampling bias in MaxEnt species distribution models

(2013) Stephanie Kramer-Schadt et al.   DIVERSITY AND DISTRIBUTIONS

Spatial bias in the GBIF database and its effect on modeling species' geographic distributions

(2013) Jan Beck et al.   Ecological Informatics

Geographical sampling bias in a large distributional database and its effects on species richness-environment models

(2013) Wenjing Yang et al.   JOURNAL OF BIOGEOGRAPHY

Across-taxa incongruence in patterns of collecting bias

(2012) Mariana M. Vale et al.   JOURNAL OF BIOGEOGRAPHY

Sampling bias in geographic and environmental space and its effect on the predictive power of species distribution models

(2012) Nadia Bystriakova et al.   SYSTEMATICS AND BIODIVERSITY

Geographic sampling bias in the South African Frog Atlas Project: implications for conservation planning

(2010) Emily A. Botts et al.   BIODIVERSITY AND CONSERVATION

Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data

(2010) Jorge M. Lobo et al.   JOURNAL FOR NATURE CONSERVATION

Distorted Views of Biodiversity: Spatial and Temporal Bias in Species Occurrence Data

(2010) Elizabeth H. Boakes et al.   PLOS BIOLOGY

Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data

(2009) Steven J. Phillips et al.   ECOLOGICAL APPLICATIONS