Species distribution modeling and assessment of environmental drivers responsible for distribution and preferred niche of critically endangered and endemic ornamental freshwater fish species of the genus Sahyadria

Pathak, Ajey Kumar; Verma, Pushpendra Kumar; Dayal, Rajesh; Sarkar, Uttam Kumar

doi:10.1007/s11356-022-19459-6

Cited by 5 publications

(5 citation statements)

References 39 publications

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“…These are based on the analysis of occurrence records. They are efficient and innovative tools for predicting occurrence and understanding ecological processes that determine habitat preferences [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Current and Future Spatial Distribution of the Genus Cinchona in Peru: Opportunities for Conservation in the Face of Climate Change

Vergara,

Cieza-Tarrillo,

Ocaña

et al. 2023

Sustainability

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The genus Cinchona belongs to the Rubiaceae family and comprises native Peruvian tree species distributed in tropical areas. It is currently endangered due to human disturbance and overexploitation for medicinal, forestry and food uses. To date, the current and future distribution of Cinchona spp. under the climate change scenario is unknown. Here, we modeled the present and future spatial distribution of the genus Cinchona using bioclimatic, edaphic and topographic variables using the maximum entropy algorithm (MaxEnt). The results indicate that 8.08% (103,547.89 km2) and 6.02% (77,163.81 km2) of the surface of Peru possesses areas with high and moderate distribution probabilities, respectively, to host the genus Cinchona, distributed mainly in the departments of Cusco, Amazonas, San Martín and Cajamarca. Furthermore, according to future climate scenarios, the areas of high suitability will increase their extension for the years 2050 and 2070 by 3.65% and 3.9%, respectively. Since Peru seeks to promote the forest sector to be the other force for its development, this study can be considered as a basis for the establishment of priority zones for the conservation, restoration, reforestation and sustainable management of Cinchona spp. species in Peru.

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Section: Introductionmentioning

confidence: 99%

Current and Future Spatial Distribution of the Genus Cinchona in Peru: Opportunities for Conservation in the Face of Climate Change

Vergara,

Cieza-Tarrillo,

Ocaña

et al. 2023

Sustainability

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“…As mentioned before, the normally‐distributed errors and no trends in residuals relative to the fitted values (Hardin & Hardin, 2007) allow the GLM to be interpretably efficient for predicting out‐of‐bag data. In MaxEnt, as a density estimator algorithm, the species distribution is represented by a probability distribution that is closest to uniform (Pathak et al, 2022; Phillips et al, 2006). This probability distribution is bounded by a set of constraints that are simple functions of the explanatory variables, called “features,” and derived from the species occurrence locations.…”

Section: Discussionmentioning

confidence: 99%

“…As mentioned before, the normally-distributed errors and no trends in residuals relative to the fitted values (Hardin & Hardin, 2007) allow the GLM to be interpretably efficient for predicting out-of-bag data. In MaxEnt, as a density estimator algorithm, the species distribution is represented by a probability distribution that is closest to uniform (Pathak et al, 2022;Phillips et al, 2006).…”

Section: Models Comparison: Simple Regression Vs Complex Machine Lear...mentioning

confidence: 99%

MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models

Ahmadi

Hemami

Kaboli

et al. 2023

Ecology and Evolution

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Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well‐performing models has rarely been implemented. We integrated input data manipulation and model tuning for four commonly‐used SDMs: generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced‐biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model‐specific parameters considering two background selection methods: random and background weighting schemes. The performance of the fine‐tuned models was assessed based on recently identified localities of the species. The results indicated that although the fine‐tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out‐of‐bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over‐predict nonsampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced‐biased data in species distribution modeling approaches.

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“…Prioritization of habitats, which support endemic and endangered state fish species, may be declared as a protected reserve to ensure natural fishery recruitment. The use of spatial distribution models could be considered for determining the ecological niches and potential distribution areas (Pathak et al, 2022) for the rare and endemic state fishes, namely, S. , 2015). The protection of these aforementioned sites ensures the sustainable natural propagation of state fishes and also acts as refugia for other native and threatened fish species.…”

Section: In Situ Conservationmentioning

confidence: 99%

“…Prioritization of habitats, which support endemic and endangered state fish species, may be declared as a protected reserve to ensure natural fishery recruitment. The use of spatial distribution models could be considered for determining the ecological niches and potential distribution areas (Pathak et al, 2022) for the rare and endemic state fishes, namely, S. modestus , N. hexagonolepis , and B. carnaticus , for conservation planning. Conversely, efforts need to be taken to admit the existing locally recognized community‐based habitats under the prevailing legal framework.…”

Section: Conservation Approaches For the Prioritized State Fishesmentioning

confidence: 99%

The concept of “state fishes of India”: Current status, knowledge gaps, and strategic plans for conservation and sustainable utilization

Sarkar,

Kathirvelpandian,

Kantharajan

et al. 2024

Journal of Fish Biology

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The concept of “state fishes of India” highlights the importance and significance of the prioritized fish species distributed across various states within the country. This review article systematically documents the current status of state fishes from various perspectives, identifies the prevailing knowledge gaps, and also highlights the issues and strategic plans essential for the conservation and sustainable utilization of these valuable genetic resources. A total of 8357 publications were checked for the consolidated information on state fish species, and the appropriate items were selected under eight categories: biology, physiology and nutrition, aquaculture, habitat and environmental parameters, genetics and biotechnology, harvest and postharvest, fish health management, and others. The synthesized information was used to present the current status of research and development on state fish species. The knowledge gaps that are to be addressed are also depicted under the perspectives of fisheries management and conservation aquaculture. Based on the findings, strategic plans for the targeted conservation programmes are proposed and discussed under various in situ and ex situ conservation measures. Further, the departmental processes involved in the declaration, the importance of stakeholder involvement, namely, local communities and policymakers, in fostering effective conservation measures, and planning for utilization of these valuable fish genetic resources are also indicated.

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Species distribution modeling and assessment of environmental drivers responsible for distribution and preferred niche of critically endangered and endemic ornamental freshwater fish species of the genus Sahyadria

Cited by 5 publications

References 39 publications

Current and Future Spatial Distribution of the Genus Cinchona in Peru: Opportunities for Conservation in the Face of Climate Change

Current and Future Spatial Distribution of the Genus Cinchona in Peru: Opportunities for Conservation in the Face of Climate Change

MaxEnt brings comparable results when the input data are being completed; Model parameterization of four species distribution models

The concept of “state fishes of India”: Current status, knowledge gaps, and strategic plans for conservation and sustainable utilization

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