Sampling bias

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa

Background: Spatial conservation prioritisation (SCP) is a set of computational tools designed to support the efficient spatial allocation of priority areas for conservation actions, but it is subject to many sources of uncertainty which should be …

Improved species-occurrence predictions in data-poor regions: using large-scale data and bias correction with down-weighted Poisson regression and Maxent

Species distribution modelling (SDM) has become an essential method in ecology and conservation. In the absence of survey data, the majority of SDMs are calibrated with opportunistic presence-only data, incurring substantial sampling bias. We address …

Reliability of species distribution modelling for wildlife conservation in developing countries

Species distribution models have become essential tools in ecology and wildlife conservation. However, their reliability when used for conservation management is often compromised by many challenges and limitations, as for example the lack of …

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling

Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country’s borders, typically along a limited environmental gradient with biased and incomplete data, making the quality …