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Benthic Crustacea and Mollusca distribution in Arctic fjord – case study of patterns in Hornsund, Svalbard

Drewnik A., Węsławski J. M., Włodarska-Kowalczuk M.

Oceanologia

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2017

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No. 59 (4)

565--575

EN

We present the results of species distribution modeling conducted on macrobenthic occurrence data collected between 2002 and 2014 in Arctic fjord – Hornsund. We focus on species from Mollusca and Crustacea taxa. This study investigates the importance of individual environmental factors for benthic species distribution, with a special emphasis on bottom water temperature. It aims to verify the hypothesis that the distribution of species is controlled by low water temperatures in the fjord and that the inner basins of the fjord serve as potential refugia for Arctic species threatened by the climate change-related intensification of warmer water inflows. Our results confirm the importance of bottom water temperature in regulating the presence of benthic fauna in the Hornsund fjord. The distribution of studied species is clearly related to specific water mass – colder (<1°C) or warmer (>1°C); and the preferred temperature regimes seem to be species specific and unrelated to analyzed groups. This study supports the notion that inner basins of the Hornsund fjord are potential refugia for cold water Arctic fauna, while the outer and central basins provide suitable habitats for fauna that prefer warmer waters.

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The potential effects of climate change on suitable habitat for the Sichuan Hill Partridge (Arborophila rufipectus, Boulton) based on the maximum entropy modeling

Lei J., Xu H., Cui P., Guang Q., Ding H.

Polish Journal of Ecology

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2014

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Vol. 62, nr 4

771--787

EN

Climate change is considered one of the greatest threats to biodiversity in future decades. Learning about the habitat preferences and geographical distributions of endangered species is critical for conservation management and planning in the context of climate change. This study investigated the effects of climate change on suitable habitat for Arborophila rufipectus Boulton, an endangered species that is endemic to southwest China. We used the known presence records for this species and a series of environmental variable layers to develop a predictive distribution model using maximum entropy modelling; this model was then used to assess the effects of future climate change on suitable habitat for this species. Our study indicated that climate change might have significant effects on suitable habitat for this species. By 2050, under a no-dispersal hypothesis, more than four-fifths of the habitat currently assessed as suitable would be lost, and the mean latitude of suitable habitat would shift northward by more than 100 kilometres. Based on this model, climate change would also aggravate habitat fragmentation. Under a full-dispersal hypothesis, all four climate trajectories developed by the Canadian Centre for Climate Modelling and Analysis (Ccma) and the Commonwealth Scientific and Industrial Research Organization (CSIRO) present similar trends: the area of suitable habitat is predicted to increase substantially, and habitat fragmentation would be mitigated under the two climate trajectories developed by the Goddard Institute for Space Studies (GISS). Finally, we offer some practical proposals for the future conservation of this endangered species.

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Predicting current and future invasion of Solidago canadensis; a study from China

Xu Z., Peng H., Feng Z., Abdulsalih N.

Polish Journal of Ecology

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2014

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Vol. 62, nr 2

263--271

EN

Solidago canadensis, which is native to North America, is considered to be the most widespread invasive alien plant. The invasion of Solidago canadensis in China has resulted in serious environmental problems. Therefore, understanding the relationship between the geographical distribution of S. canadensis and bioclimatic variables, and then predicting the potential distribution of this species is essential for management actions and practices. Although several studies have delineated the potential distribution of S. canadensis in China, how this species would respond to variations in future climatic conditions remains unclear. In the present study, we predicted the potential distribution of S. canadensis under current and future climatic conditions using species distribution models. We also analyzed range shifting of this species under current and future climatic conditions. We arrived at several conclusions. First, the potential distribution of S. canadensis may expand 40% under future climatic condition compare with that of under current condition. Second, mean diurnal range, isothermality, mean temperature of the wettest quarter, mean temperature of the warmest quarter, precipitation of the driest month, and precipitation seasonality (coefficient of variation) are key bioclimatic variables in determine the potential distribution of S. canadensis. Third, expansion of S. canadensis can be partly attributed to the relatively warmer and wetter future bioclimatic condition than current one.

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Species distribution models to estimate the deforested area of Picea crassifolia in arid region recently protected : Qilian Mts. National Natural Reserve (China)

Xu Z., Zhao C., Feng Z.

Polish Journal of Ecology

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2012

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Vol. 60, nr 3

515-524

EN

The earth is now facing the land degradation due to human disturbance, natural habitats were converted to rural and agricultural areas in order to fulfill the increasing demand of human population. The deforestation of Picea crassifolia (Qinghai spruce) forest at Qilian Mts is an example of such disturbance. P. crassifolia is an ecologically and hydrologically important plant species in the northwestern arid area of China. However, the forests have been intensively and extensively deforested. In order to restore the human-disturbed ecosystems, the spatial distribution of P. crassifolia needs to be delineated. This study employed Genetic Algorithm for Rule-set Prediction model (GARP) and Maximum entropy model (Maxent) and four environmental variables (mean temperature of the warmest quarter, precipitation of the wettest quarter, annual solar radiation, topographic wetness index) to predict the potential distribution of P. crassifolia in Qilian Mts. Genetic Algorithm for Rule-set Prediction model (GARP) produces a model of species niches in geographic space based on heterogeneous rule-sets. Maximum entropy model (Maxent) focuses on fitting a probability distribution for occurrence based on the idea that the best explanation to unknown phenomena will maximize the entropy of the probability distribution, subject to the appropriate constraints. The environmental variables were spatially interpolated throughout the entire study area. We used sensitivity-specificity sum maximum approach to select the threshold value. The projected niche space for the mean temperature of the warmest quarter is between 8.5 and 18.1[degrees]C; the space for the precipitation of the wettest quarter is between 149 and 245 mm; the space for annual solar radiation is 118-1100 x 10[^3] wh m[^-2] and the space for topographic wetness index is between -0.4 and 5.1. The results show that both GARP and Maxent's models produce acceptable predictions, but the overall comparison shows that GARP prediction is better than Maxent's; the comparison between the observed distribution and the predicted distribution suggests that 61% (2869 km2) of P. crassifolia forests have been deforested.