How much is enough? Influence of number of presence observations on the performance of species distribution models

@article{Sta2019HowMI,
  title={How much is enough? Influence of number of presence observations on the performance of species distribution models},
  author={Bente St{\o}a and Rune Halvorsen and Jogeir N. Stokland and Vladimir I. Gusarov},
  journal={Sommerfeltia},
  year={2019},
  volume={39},
  pages={1 - 28}
}
Abstract Species distribution modeling (SDM) can be useful for many applied purposes, e.g., mapping and monitoring of rare and endangered species. Sparse presence data are a recurrent, major obstacle to precise modeling of species distributions. Thus, knowing the minimum number of presences required to obtain reliable distribution models is of fundamental importance for applied use of SDM. This study uses a novel approach to assess the critical sample size (CSS) sufficient for an accurate… 

Figures and Tables from this paper

Sample size for the evaluation of presence-absence models
Abstract The effect of the training dataset sample size has been shown to have profound outcomes on the performance of species distribution models. However, the effects that the testing dataset
Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin, USA
TLDR
The results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.
Biogeographical factors determining Triatoma recurva distribution in Chihuahua, México, 2014
TLDR
This methodology can be used in other geographical contexts to locate potential sampling sites where these triatomines occur and determined T. recurva distribution area at a higher percentage evidencing its strong relationship with domestic and surrounding structures.
Predicting the Areas of Suitable Distribution for Zelkova serrata in China under Climate Change
Predicting the geographic distribution of a species together with its response to climate change is of great significance for biodiversity conservation and ecosystem sustainable development. Zelkova
Modeling the distribution of the Near Eastern fire salamander (Salamandra infraimmaculata) and Kurdistan newt (Neurergus derjugini) under current and future climate conditions in Iraq
TLDR
This study provides baseline information for further investigation of the mountain forest ecosystems, and biodiversity conservation actions in Iraq, and determines the main environmental variables shaping their distributions.

References

SHOWING 1-10 OF 68 REFERENCES
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
TLDR
This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
The effect of sample size and species characteristics on performance of different species distribution modeling methods
TLDR
Maxent was the most capable of the four modeling methods in producing useful results with sample sizes as small as 5, 10 and 25 occurrences, a result that should encourage conservationists to add distribution modeling to their toolbox.
Effects of sample size on the performance of species distribution models
A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is
The uncertain nature of absences and their importance in species distribution modelling
TLDR
The joint examination of ommission and comission errors provides a better understanding of the reliability of SDM results and confirms the importance of the kind of absences in determining the aspect of species distribution identified through SDM.
Species distribution modelling—Effect of design and sample size of pseudo-absence observations
We explored the effect of varying pseudo-absence data in species distribution modelling using empirical data for four real species and simulated data for two imaginary species. In all analyses we
Effects of sample size on accuracy of species distribution models
Abstract Given increasing access to large amounts of biodiversity information, a powerful capability is that of modeling ecological niches and predicting geographic distributions. Because, sampling
WHAT MATTERS FOR PREDICTING THE OCCURRENCES OF TREES: TECHNIQUES, DATA, OR SPECIES' CHARACTERISTICS?
Data characteristics and species traits are expected to influence the accuracy with which species' distributions can be modeled and predicted. We compare 10 modeling techniques in terms of predictive
Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity
Question: What are the effects of the number of presences on models generated with multivariate adaptive regression splines (MARS)? Do these effects vary with data quality and quantity and species
Using niche-based models to improve the sampling of rare species.
TLDR
The model-based approach to sampling for rare species helps in the discovery of new populations of the target species in remote areas where the predicted habitat suitability is high and may save up to 70% of the time spent in the field.
Novel methods improve prediction of species' distributions from occurrence data
TLDR
This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
...
1
2
3
4
5
...