• Title/Summary/Keyword: habitat niche modelling

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Using High Resolution Ecological Niche Models to Assess the Conservation Status of Dipterocarpus lamellatus and Dipterocarpus ochraceus in Sabah, Malaysia

  • Maycock, Colin R.;Khoo, Eyen;Kettle, Chris J.;Pereira, Joan T.;Sugau, John B.;Nilus, Reuben;Jumian, Jeisin;Burslem, David F.R.P.
    • Journal of Forest and Environmental Science
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    • v.28 no.3
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    • pp.158-169
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    • 2012
  • Sabah has experienced a rapid decline in the extent of forest cover. The precise impact of habitat loss on the conservation status of the plants of Sabah is uncertain. In this study we use the niche modelling algorithm MAXENT to construct preliminary, revised and final ecological niche models for Dipterocarpus lamellatus and Dipterocarpus ochraceus and combined these models with data on current land-use to derive conservation assessments for each species. Preliminary models were based on herbarium data alone. Ground surveys were conducted to evaluate the performance of these preliminary models, and a revised niche model was generated from the combined herbarium and ground survey data. The final model was obtained by constraining the predictions of the revised models by filters. The range overlap between the preliminary and revised models was 0.47 for D. lamellatus and 0.39 for D. ochraceus, suggesting poor agreement between them. There was substantial variation in estimates of habitat loss for D. ochraceus, among the preliminary, revised and constrained models, and this has the potential to lead to incorrect threat assessments. From these estimates of habitat loss, the historic distribution and estimates of population size we determine that both species should be classified as Critically Endangered under IUCN Red List guidelines. Our results suggest that ground-truthing of ecological niche models is essential, especially if the models are being used for conservation decision making.

Predicting the Invasion Pathway of Balanus perforatus in Korean Seawaters

  • Choi, Keun-Hyung;Choi, Hyun-Woo;Kim, Il-Hoi;Hong, Jae-Sang
    • Ocean and Polar Research
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    • v.35 no.1
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    • pp.63-68
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    • 2013
  • The European Common Barnacle Balanus perforatus Brugiere (Crustacea, Cirripedia) has been introduced into the east coast of Korea, presumably via the ballast water of ships. The species has since been spreading along both the northern and southern coast to the east, most likely due to alongshore currents. We predicted the potential range expansion of Balanus perforatus in Korean waters using Genetic Algorithm for Rule-set Prediction (GARP), an environmental niche modeling technique. The results show that much of the southern coastal waters of Korea could be colonized by the spread of the nonindigenous species, but that the west coast is unlikely to be invaded. More sampling on the west coast would enhance the predictability of the model. To our knowledge, this is the first report of its kind for predicting marine nonindigenous species in Korean waters using GARP modeling.

Tree species migration to north and expansion in their habitat under future climate: an analysis of eight tree species Khyber Pakhtunkhwa, Pakistan

  • Muhammad Abdullah Durrani;Rohma Raza;Muhammad Shakil;Shakeel Sabir;Muhammad Danish
    • Journal of Ecology and Environment
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    • v.48 no.1
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    • pp.96-109
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    • 2024
  • Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

Predictive Distribution Modelling of Calamus andamanicus Kurz, an Endemic Rattan from Andaman and Nicobar Islands, India

  • Sreekumar, V.B.;Suganthasakthivel, R.;Sreejith, K.A.;Sanil, M.S.
    • Journal of Forest and Environmental Science
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    • v.32 no.1
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    • pp.94-98
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    • 2016
  • Calamus andamanicus Kurz is one of the commercially important solitary rattans endemic to Andaman and Nicobar islands. The habitat suitability modeling program, MaxEnt, was used to predict the potential ecological niches of this species, based on bioclimatic variables. The study revealed high potential distribution of C. andamanicus across both Andaman and Nicobar islands. Of the 33 spatially unique points, 21 points were recorded from South and North Andamans and 12 from Great Nicobar Islands. The islands like Little Andaman, North Sentinel, Little Nicobar, Tllangchong, Teressa were also predicted positive even though this rattan is not recorded from these islands. Mean diurnal range, higher precipitation in the wettest month of the year, annual precipitation and precipitation in the driest month are the main predictors of this species distribution.

A Comparison of Machine Learning Species Distribution Methods for Habitat Analysis of the Korea Water Deer (Hydropotes inermis argyropus) (고라니 서식지 분석을 위한 기계학습식 종분포모형 비교)

  • Song, Won-Kyong;Kim, Eun-Young
    • Korean Journal of Remote Sensing
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    • v.28 no.1
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    • pp.171-180
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    • 2012
  • The field of wildlife habitat conservation research has attracted attention as integrated biodiversity management strategies. Considering the status of the species surveying data and the environmental variables in Korea, the GARP and Maxent models optimized for presence-only data could be one of the most suitable models in habitat modeling. For make sure applicability in the domestic environment we applied the machine learning species distribution model for analyzing habitats of the Korea water deer($Hydropotes$ $inermis$ $argyropus$) in the $Sapgyocheon$ watershed, $Chungcheong$ province. We used the $3^{rd}$ National Natural Environment Survey data and 10 environment variables by literature review for the modelling. Analysis results showed that habitats for the Korea water deer were predicted 16.3%(Maxent) and 27.1%(GARP), respectively. In terms of accuracy(training/test) the Maxent(0.85/0.69) was higher than the GARP(0.65/0.61), and the Spearman's rank correlation coefficient result of the Maxent(${\rho}$=0.71, p<0.01) was higher than the result of GARP(${\rho}$=0.55, p<0.05). However results could be depended on sites and target species, therefore selection of the appropriate model considering on the situation will be important to analyzing habitats.