How citizen science could improve species distribution models and their independent assessment

Using ecological niche modelling to prioritise areas for conservation of the critically endangered Buffy-Headed marmoset (Callithrix flaviceps)

Endemic to the Atlantic Forest in Southeastern Brazil, the critically endangered Buffy-Headed marmoset (Callithrix flaviceps) is lacking the required attention for effective conservation. We modelled its ecological niche with the main objectives of (1) defining suitable habitat and (2) prioritising areas for conservation and/or restoration. The current geographical range of Callithrix flaviceps in the Atlantic Forest of Southeast Brazil. We used Ensemble Species Distribution Modelling to define current habitat suitability considering four climate and two landscape variables. To identify areas to prioritise for conservation and/or restoration, we predicted future habitat suitability considering the intermediate (RCP4.5) and extreme (RCP8.5) climate change scenarios for the years 2050 and 2070. Among the variables included to predict current species distribution, tree canopy cover, precipitation seasonality and temperature seasonality were the most important whereas digital elevation model and precipitation during the wettest month were the least important. Callithrix flaviceps was most likely to occur in areas with tree canopy cover >80%, high precipitation seasonality and temperature seasonality between 21 and 23°C. From the future suitability prediction maps, the Caparaó National Park stands out as a likely key area for the preservation of the species. Furthermore, high climatic suitability but low landscape suitability suggests that habitat restoration in 'Serra das Torres' (South of the current distribution area) might be a useful strategy. However, creating ecological corridors on the west side of Caparaó would be necessary to improve connectivity. More surveys within and beyond the current geographical range are required to define more precisely the distribution of the species. Our results support the notion that seasonality is important for Callithrix flaviceps and that as a montane species, it prefers colder environments and higher altitudes. Within both climate change scenarios, Caparaó National Park was predicted to be highly suitable, with a high probability of presence.

Predicting the distribution of Ixodes ricinus and Dermacentor reticulatus in Europe: a comparison of climate niche modelling approaches

BACKGROUND

The ticks Ixodes ricinus and Dermacentor reticulatus are two of the most important vectors in Europe. Climate niche modelling has been used in many studies to attempt to explain their distribution and to predict changes under a range of climate change scenarios. The aim of this study was to assess the ability of different climate niche modelling approaches to explain the known distribution of I. ricinus and D. reticulatus in Europe.

METHODS

A series of climate niche models, using different combinations of input data, were constructed and assessed. Species occurrence records obtained from systematic literature searches and Global Biodiversity Information Facility data were thinned to different degrees to remove sampling spatial bias. Four sources of climate data were used: bioclimatic variables, WorldClim, TerraClimate and MODIS satellite-derived data. Eight different model training extents were examined and three modelling frameworks were used: maximum entropy, generalised additive models and random forest models. The results were validated through internal cross-validation, comparison with an external independent dataset and expert opinion.

RESULTS

The performance metrics and predictive ability of the different modelling approaches varied significantly within and between each species. Different combinations were better able to define the distribution of each of the two species. However, no single approach was considered fully able to capture the known distribution of the species. When considering the mean of the performance metrics of internal and external validation, 24 models for I. ricinus and 11 models for D. reticulatus of the 96 constructed were considered adequate according to the following criteria: area under the receiver-operating characteristic curve > 0.7; true skill statistic > 0.4; Miller's calibration slope 0.25 above or below 1; Boyce index > 0.9; omission rate < 0.15.

CONCLUSIONS

This comprehensive analysis suggests that there is no single 'best practice' climate modelling approach to account for the distribution of these tick species. This has important implications for attempts to predict climate-mediated impacts on future tick distribution. It is suggested here that climate variables alone are not sufficient; habitat type, host availability and anthropogenic impacts, not included in current modelling approaches, could contribute to determining tick presence or absence at the local or regional scale.

Not all who wander are lost: Trail bias in community science

The exponential growth and interest in community science programs is producing staggering amounts of biodiversity data across broad temporal and spatial scales. Large community science datasets such as iNaturalist and eBird are allowing ecologists and conservation biologists to answer novel questions that were not possible before. However, the opportunistic nature of many of these enormous datasets leads to biases. Spatial bias is a common problem, where observations are biased towards points of access like roads and trails. iNaturalist-a popular biodiversity community science platform-exhibits strong spatial biases, but it is unclear how these biases affect the quality of biodiversity data collected. Thus, we tested whether fine-scale spatial bias due to sampling from trails affects taxonomic richness estimates. We compared timed transects with experienced iNaturalist observers on and off trails in British Columbia, Canada. Using generalized linear mixed models, we found higher overall taxonomic richness on trails than off trails. In addition, we found more exotic as well as native taxa on trails than off trails. There was no difference between on and off trail observations for species that are rarely observed. Thus, fine-scale spatial bias from trails does not reduce the quality of biodiversity measurements, a promising result for those interested in using iNaturalist data for research and conservation management.

Multiscale ecological niche modeling exhibits varying climate change impacts on habitat suitability of Madrean Pine-Oak trees

Anthropogenic climate change and increasing greenhouse gas emissions are expected to globally impact the biological function, community structure, and spatial distribution of biodiversity. Many existing studies explore the effect of climate change on biodiversity, generally at a single spatial scale. This study explores the potential effects of climate change on the habitat suitability of seven tree species at two distinct spatial scales: the Coronado National Forest (CNF), a local management area, and the Sierra Madre Occidental (SMO), an ecoregional extent. Habitat suitability was determined by extrapolating Ecological Niche Models (ENMs) based on citizen-science tree occurrence records into future climatic conditions using projected 30-year normals for two anthropogenic emissions scenarios through the end of the century. These ENMs, examined at a spatial resolution of 1 km2, are constructed using a mean average ensemble of three commonly used machine learning algorithms. The results show that habitat suitability is expected to decrease for all seven tree species at varying degrees. Results also show that climate-forcing scenario choice appears to be far less important for understanding changes in species habitat suitability than the spatial scale of modeling extent. Additionally, we observed non-linear changes in tree species habitat suitability within the SMO and CNF dependent on forest community type, latitude, and elevational gradient. The paper concludes with a discussion of the necessary steps to verify the estimated alters of these tree species under climate change. Most importantly, provides a framework for characterizing habitat suitability across spatial scales.

The Big Five: Species Distribution Models from Citizen Science Data as Tool for Preserving the Largest Protected Saproxylic Beetles in Italy

Background. Volunteers’ participation in scientific research has increased in recent decades. Citizen science (CS) data have been used in quantitative ecology to analyse species ranges by means of species distribution models. We investigated the Italian distribution of five large saproxylic beetles (big five), to describe their niche space, paramount areas for their conservation, and conservation gaps. Methods. CS data from two projects, climate and environmental variables were used to produce Habitat suitability (HS) maps for each species and averaged HS maps. The big five’s conservation status was assessed interpolating HS maps with the distribution of protected areas, concomitantly identifying conservation gaps. Results. The pre-alpine and Apennines arcs, north-eastern Sicily and eastern Sardinia, were identified as conservation’s hotspots. Ranking HS levels from minimum to optimal, the extent of conservation gaps decreases as environmental suitability for the big five increases. Conclusions. For the first time in Italy, CS data have been used to investigate niche space of the largest protected saproxylic beetles and analyse the distribution of their suitable habitat. The resulting HS raster maps and vector layers, reporting HS value in all Italian protected areas (n° 3771), were provided and discussed, reporting an application example for conservation purposes.

Enhancing Our Understanding of Ladybirds in Ireland – A Case Study of the Use of Citizen Science

Citizen science is increasingly recognised as a useful approach to contribute to biodiversity awareness while generating data and creating meaningful interactions among citizens and professional scientists. In a number of countries, academic institutions have led the way in developing ladybird projects, incorporating citizen science, to increase distributional data on the species, as well as a greater understanding of ladybird ecology. The current research evaluates the role of citizen science campaigns in collecting biological distributional data in Ireland, using ladybirds as a case example, examining if citizen science records and the use of photographs can provide a valuable insight into our understanding of ladybird ecology. From April 2020 to June 2021, a citizen science programme engaged with the wider public, via social media networks to increase the number of ladybird records and assist in establishing national data baselines, since ladybird rcording is a relatively new phenomenon in Ireland. This case study finds that citizen science projects using social media can increase the number of records of ladybirds and provide useful information on species distribution patterns. There were a disproportionate number of records from areas of high human population, resulting in a bias towards urban centres. Photographs submitted by members of the public provided a limited amount of information on food plants but indicated that ladybirds are valued as a species of interest to the public. These images can also help to increase records of the less common species, especially as members of the public may not be able to easily distinguish between different species of ladybirds.