Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

2020 ◽  
Vol 39 (6) ◽  
pp. 36-47
Author(s):  
Yunlei Zhang ◽  
Huaming Yu ◽  
Haiqing Yu ◽  
Binduo Xu ◽  
Chongliang Zhang ◽  
...  
Author(s):  
Joseph A. Veech

Habitat analysis is strictly defined as a statistical examination to identify the environmental variables that a species associates with, wherein association is taken as some form of correspondence between a species response variable (e.g., presence–absence or abundance) and the environmental variables. There are other statistical techniques and empirical goals that extend this basic framework. These techniques often rely on a habitat analysis having been conducted as an initial step. Resource selection functions quantify an individual’s and a species’ use of a resource based upon the properties of the resource. Resource is broadly defined and can include particular types of habitat. Selectivity and preference indices are used to assess an individual’s preference and active choice of different resource types. Compositional data analysis is a statistical method for examining the composition of an individual’s territory or home range with regard to different habitat types that may be represented. Habitat suitability modeling and species distribution modeling are closely related techniques designed to map the spatial distribution of a species’ habitat and sometimes the species itself based upon its habitat requirements and other factors.


2020 ◽  
Author(s):  
Da-Ju Wang ◽  
Hai-Yan Wei ◽  
Xu-Hui Zhang ◽  
Ya-Qin Fang ◽  
Wei Gu

Abstract Aims Remote sensing (RS) is a technical method for effectively capturing real-world data on a large scale. We aimed to (i) realize the time synchronization of species and environmental variables, and extract variables related to the actual growth of species based on RS in habitat suitability modeling, and (ii) provide a reference for species management. Methods Taking invasive species Ambrosia artemisiifolia in China as an example for habitat suitability modeling. Temperature and precipitation variables were calculated from the land surface temperature (LST) provided by the moderate-resolution imaging spectroradiometer (MODIS), and climate station data, respectively. Besides, other variables that directly affect the growth or reproduction of A. artemisiifolia were also included, such as the relative humidity of the previous year's flowering period (RHPFP), and the effective UV irradiance reaching the Earth's surface (UVI). The Random Forest (RF) method was selected to model the habitat suitability. The environmental variables and samples were divided into four-time periods (i.e. 1990-2000, 2001-2005, 2006-2010, and 2011-2016) based on sampling time. Variables from the long-time series of RS (1990-2016) and WorldClim (1960-1990) were also modeled. Important Findings It was feasible to extract environmental variables from RS for habitat suitability modeling, and was more accurate than that based on the variables from WorldClim. The potential distribution of A. artemisiifolia in 1990-2000 and 2006-2010 was smaller than that in 2001-2005 and 2011-2016. The precipitation of driest months (bio14), precipitation coefficient of variation (bio15), RHPFP, and UVI were the important environmental variables that affect the growth and reproduction of A. artemisiifolia. The results indicated that the time synchronization of species and environmental variables improved the prediction accuracy of A. artemisiifolia, which should be considered in habitat suitability modeling (especially for annual species). This study can provide an important reference for the management and prevention of the spread of A. artemisiifolia.


2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.


2021 ◽  
Vol 42 (3(SI)) ◽  
pp. 806-811
Author(s):  
N.F. Khodri ◽  
◽  
T. Lihan ◽  
M.A. Mustapha ◽  
T.M. Taher ◽  
...  

Aim: This research assessed the distribution of leopard to predict the habitat suitability in Taman Negara National Park and adjacent forest area. Methodology: Environmental factors for habitat suitability were derived from geographical information system (GIS) data such as elevation, slope, land-use, distance from urban and distance from river. Leopard presence data from 1993 to 2008 were integrated with the environmental parameters using maximum entropy (MaxEnt) modeling to assess habitat suitability across the study area. Results: The results showed that distance from river contributed the most (39.3%) in the habitat suitability modeling followed by distance from urban (31.4%), elevation (12.3%), land use types (10.1%), and slope (6.9%). Distance from river and urban showed highest contribution that influenced leopard distribution in which most suitable habitat occurred in proximity with river and further from urban. Habitat suitability of leopard were distributed among 48% over 2,218,389 ha of the study area. Interpretation: The findings of this study provides knowledge on how the species move and exploit different habitat niches for more effective conservation management. It provide models for future wildlife conservation and urban planning.


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