High-resolution niche models via a correlative approach: Comparing and combining correlative and process-based information

Bogosian, Victor; Hellgren, Eric C.; Sears, Michael W.; Moody, Raymond W.

doi:10.1016/j.ecolmodel.2012.04.017

Cited by 9 publications

(9 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For example, Bogosian III et al . (2012) combined mechanistic and correlative models for a lizard species using data with a spatial resolution of 1 m. Although locations were collected by telemetry, individuals were not modelled separately. Sillero & Gonçalves‐Seco (2014) were the first in using LiDAR‐derived data with a spatial resolution of 1 m to model with Maxent four species of lizards and analyse the spatial structure of their community.…”

Section: Discussionmentioning

confidence: 99%

Ecological niche models improve home range estimations

Sillero¹,

Santos²,

Teodoro

et al. 2020

Journal of Zoology

View full text Add to dashboard Cite

Home ranges in animals can be estimated by different methods like minimum convex polygons, characteristic hulls or kernels while correlative ecological niche models (ENMs) are commonly employed for forecasting species' ranges. However, ENMs can also model the distribution of individuals if environmental very high spatial resolution data are available. Indeed, remote sensing (RS) can provide images with pixel sizes of few centimetres. Here, we modelled the distribution of individual lizards (Podarcis bocagei) combining aerial‐like photographs recorded with a compact camera and a matrix of temperature/humidity data‐loggers to obtain several environmental layers with very high spatial resolution. We recorded lizards’ positions in a 20 × 20 m mesocosm with a high precision GPS device (~10 cm of error), multiple times per day throughout the whole period of daily activity. We built an orthophoto map (pixels of 20 cm2) from camera pictures, a digital surface model, and a land‐cover supervised classification map. We recreated climate‐like variables by combining data‐logger data. For each individual, we calculated the distance to males and females, excluding the focal lizard. We computed individual realized niche models with Bioclim, GAM, GLM, Maxent and random forest. Models attained a very high evaluation score in most cases. The most contributing variables were related to microclimate (isothermality, minimum temperature and humidity) and distance to conspecifics. Our very high spatial resolution models provided robust information on how space is used by each lizard. Correlative models can identify the most suitable areas inside the home range, similar to core areas estimated from kernel algorithms, but allowed better statistical inference. Overall, RS tools generated high‐quality environmental data, and when combined with ENMs, improved the robustness of the predictions on spatial patterns of small terrestrial animals.

show abstract

Section: Discussionmentioning

confidence: 99%

Ecological niche models improve home range estimations

Sillero¹,

Santos²,

Teodoro

et al. 2020

Journal of Zoology

View full text Add to dashboard Cite

show abstract

“…ENMs are powerful statistical tools for analysing species niches and their changes over time and space [22]. However, very few studies have applied ENMs at very high spatial resolution [23][24][25][26][27][28] and even less have compared several species composing a community [10].…”

Section: Introductionmentioning

confidence: 99%

Local Segregation of Realised Niches in Lizards

Sillero

Argaña

Matos

et al. 2020

IJGI

View full text Add to dashboard Cite

Species can occupy different realised niches when sharing the space with other congeneric species or when living in allopatry. Ecological niche models are powerful tools to analyse species niches and their changes over time and space. Analysing how species’ realised niches shift is paramount in ecology. Here, we examine the ecological realised niche of three species of wall lizards in six study areas: three areas where each species occurs alone; and three areas where they occur together in pairs. We compared the species’ realised niches and how they vary depending on species’ coexistence, by quantifying niche overlap between pairs of species or populations with the R package ecospat. For this, we considered three environmental variables (temperature, humidity, and wind speed) recorded at each lizard re-sighting location. Realised niches were very similar when comparing syntopic species occurring in the same study area. However, realised niches differed when comparing conspecific populations across areas. In each of the three areas of syntopy, the less abundant species shift its realised niche. Our study demonstrates that sympatry may shift species’ realised niche.

show abstract

“…One type of ENMs are correlative models which are built by integrating species occurrences with spatial environmental variables of the study area [ 27 , 30 ]. Correlative ENMs characterize the relationship between occurrence locations of a species with environmental characteristics of those locations, and use this to estimate the environmental suitability for a species in a specific location.…”

Section: Introductionmentioning

confidence: 99%

“…Recent studies have demonstrated the predictive performance of these models [ 26 , 27 , 31 – 37 ]. Correlative models are widely used tools for assessing the risk of establishment of a variety of species including insects [ 25 – 27 , 32 , 33 ], aquatic organisms [ 23 , 34 ], plants [ 37 , 38 ], human diseases [ 39 ], vertebrates [ 30 , 36 , 40 ], and pathogens [ 41 , 42 ]. The information on a species’ potential risk of establishment is helpful in developing a Pest Risk Assessment (PRA) (not developed for MSD yet), since the countries normally impose quarantine measures simply based on host species’ presence [ 43 ].…”

Section: Introductionmentioning

confidence: 99%

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata

et al. 2016

View full text Add to dashboard Cite

The Mango Sudden Decline (MSD), also referred to as Mango Wilt, is an important disease of mango in Brazil, Oman and Pakistan. This fungus is mainly disseminated by the mango bark beetle, Hypocryphalus mangiferae (Stebbing), by infected plant material, and the infested soils where it is able to survive for long periods. The best way to avoid losses due to MSD is to prevent its establishment in mango production areas. Our objectives in this study were to: (1) predict the global potential distribution of MSD, (2) identify the mango growing areas that are under potential risk of MSD establishment, and (3) identify climatic factors associated with MSD distribution. Occurrence records were collected from Brazil, Oman and Pakistan where the disease is currently known to occur in mango. We used the correlative maximum entropy based model (MaxEnt) algorithm to assess the global potential distribution of MSD. The MaxEnt model predicted suitable areas in countries where the disease does not already occur in mango, but where mango is grown. Among these areas are the largest mango producers in the world including India, China, Thailand, Indonesia, and Mexico. The mean annual temperature, precipitation of coldest quarter, precipitation seasonality, and precipitation of driest month variables contributed most to the potential distribution of MSD disease. The mango bark beetle vector is known to occur beyond the locations where MSD currently exists and where the model predicted suitable areas, thus showing a high likelihood for disease establishment in areas predicted by our model. Our study is the first to map the potential risk of MSD establishment on a global scale. This information can be used in designing strategies to prevent introduction and establishment of MSD disease, and in preparation of efficient pest risk assessments and monitoring programs.

show abstract

High-resolution niche models via a correlative approach: Comparing and combining correlative and process-based information

Cited by 9 publications

References 70 publications

Ecological niche models improve home range estimations

Ecological niche models improve home range estimations

Local Segregation of Realised Niches in Lizards

Mapping Global Potential Risk of Mango Sudden Decline Disease Caused by Ceratocystis fimbriata

Contact Info

Product

Resources

About