Integrating expert knowledge and ecological niche models to estimate Mexican primates’ distribution

Abstract

Ecological niche modeling is used to estimate species distributions based on occurrence records and environmental variables, but it seldom includes explicit biotic or historical factors that are important in determining the distribution of species. Expert knowledge can provide additional valuable information regarding ecological or historical attributes of species, but the influence of integrating this information in the modeling process has been poorly explored. Here, we integrated expert knowledge in different stages of the niche modeling process to improve the representation of the actual geographic distributions of Mexican primates (Ateles geoffroyi, Alouatta pigra, and A. palliata mexicana). We designed an elicitation process to acquire information from experts and such information was integrated by an iterative process that consisted of reviews of input data by experts, production of ecological niche models (ENMs), and evaluation of model outputs to provide feedback. We built ENMs using the maximum entropy algorithm along with a dataset of occurrence records gathered from a public source and records provided by the experts. Models without expert knowledge were also built for comparison, and both models, with and without expert knowledge, were evaluated using four validation metrics that provide a measure of accuracy for presence-absence predictions (specificity, sensitivity, kappa, true skill statistic). Integrating expert knowledge to build ENMs produced better results for potential distributions than models without expert knowledge, but a much greater improvement in the transition from potential to realized geographic distributions by reducing overprediction, resulting in better representations of the actual geographic distributions of species. Furthermore, with the combination of niche models and expert knowledge we were able to identify an area of sympatry between A. palliata mexicana and A. pigra. We argue that the inclusion of expert knowledge at different stages in the construction of niche models in an explicit and systematic fashion is a recommended practice as it produces overall positive results for representing realized species distributions.

Global distribution patterns and niche modelling of the invasive Kalanchoe × houghtonii (Crassulaceae)

“…In general, results shown in Table 2 suggest that a direct use of GBIF records could be appropriate without an extensive exploration of other sources and a taxonomic expertise validation process in covering the realized environmental species niche requirements. Nevertheless, it could be highly dependent on the target taxonomic group, as for primates, the comparison of datasets without or with expert knowledge resulted in the recovering of a higher number of outliers in non-expert group 97 .…”

Strategies to optimize modeling habitat suitability of Bertholletia excelsa in the Pan‐Amazonia

“…Detailed biological knowledge is still scarce or incomplete for many if not most Amazonian plant species. Therefore, expert‐based information has been proposed as an alternative approach to identifying meaningful predictors in habitat modeling (Calixto‐Pérez et al, ). Our findings showed that PCA was effective in reducing omission error rates, data collinearity, and dimensionality, as well as preserving maximum variance, when applied to a set of variables preselected by experts.…”

“…The value and importance of a well‐constructed SDM have motivated an explosion of methods aimed at building more accurate models (Elith et al, ; Kuhnert, Martin, & Griffiths, ). However, few efforts have been made to develop a collaborative model‐building process among modelers, ecologists, and decision‐makers to improve model quality (Calixto‐Pérez et al, ) and to facilitate clear communication of model results (Addison et al, ).…”

Combining species distribution modelling and environmental perceptions to support sustainable strategies for Amazon-nut (<i>Bertholletia excelsa</i> Bonpl.) planting and conservation

“…It has been noted that this species is most vulnerable to drought during the dry season, and that dry and warm conditions negatively affect seed production (Thomas et al, 2017 Detailed biological knowledge is still scarce or incomplete for many if not most Amazonian plant species. Therefore expert-based information has been proposed as an alternative approach to identifying meaningful predictors in habitat suitability modelling (Calixto-Pérez et al, 2018). Our findings showed that PCA was effective in reducing omission error rates, data collinearity and dimensionality, as well as preserving maximum variance, when applied to a set of variables pre-selected by experts, following Dormann et al (2013). recommendations.…”

“…The value and importance of a well-constructed SDM has motivated an explosion of methods aimed at building more accurate models (Elith et al, 2011;Kuhnert, Martin, & Griffiths, 2010). However, few efforts have been made to develop a collaborative model-building process among modellers, ecologists, and decision-makers to improve model quality (Calixto-Pérez et al, 2018) and to facilitate clear communication of model results (Addison et al, 2013).…”