1. Invasive alien species and climate change are two of the most serious global environmental threats. In particular, it is of great interest to understand how changing climates could impact the distribution of invaders that pose serious threats to ecosystems and human activities.2. In this study, we developed ensemble species distribution models for predicting the current and future global distribution of the signal crayfish Pacifastacus leniusculus and the red swamp crayfish Procambarus clarkii, two of the most highly problematic invaders of freshwater ecosystems worldwide. We collected occurrence records of the species, from native and alien established ranges worldwide.These records in combination with averaged observations of current climatic conditions were used to calibrate a set of 10 distinct correlative models for estimating the climatic niche of each species. We next projected the estimated niches into the geographical space for the current climate conditions and for the 2050s and 2070s under representative concentration pathway 2.6 and 8.5 scenarios.3. Our species distribution models had high predictive abilities and suggest that annual mean temperature is the main driver of the distribution of both species.Model predictions indicated that the two crayfish species have not fully occupied their suitable climates and will respond differently to future climate scenarios in different geographic regions. Suitable climate for P. leniusculus was predicted to shift poleward and to increase in extent in North America and Europe but decrease in Asia. Regions with suitable climate for P. clarkii are predicted to widen in Europe but contract in North America and Asia.4. This study highlights that invasive species with different thermal preference are likely to respond differently to future climate changes. Our results provide important information for policy makers to design and implement anticipated measures for the prevention and control of these two problematic species. K E Y W O R D Sclimate change, habitat suitability, Pacifastacus leniusculus, Procambarus clarkii, species distribution modelling
This paper uses data for the period 1950-2050 compiled by the United Nations Population Division together with methods including spatial autocorrelation analysis, hierarchical cluster analysis and the standard deviational ellipse, to analyze the spatio-temporal evolution of population and urbanization in the 75 countries located along the routes of the Silk Road Economic Belt and the 21st-century Maritime Silk Road, to identify future population growth and urbanization hotspots. The results reveal the following: First, in 2015, the majority of Belt and Road countries in Europe, South Asia and Southeast Asia had high population densities, whereas most countries in Central Asia, North Africa and West Asia, as well as Russia and Mongolia, had low population densities; the majority of countries in South Asia, Southeast Asia, Central Asia, West Asia and North Africa had rapid population growth, whereas many countries in Europe had negative population growth; and five Belt and Road countries are in the initial stage of urbanization, 44 countries are in the acceleration stage of urbanization, and 26 are in the terminal stage of urbanization. Second, in the century from 1950 to 2050, the mean center of the study area's population is consistently located in the border region between India and China. Prior to 2000, the trajectory of the mean center was from northwest to southeast, but from 2000 it is on a southward trajectory, as the population of the study area becomes more concentrated. Future population growth hotspots are predicted to be in South Asia, West Asia and Southeast Asia, and hotspot countries for the period 2015-2030 include India, China, Pakistan and Indonesia, though China will move into negative population growth after 2030. Third, the overall urban population of Belt and Road countries increased from 22% in 1950 to 49% in 2015, and it is expected to gradually catch up with the world average, reaching 64% in 2050. The different levels of urbanization in different countries display significant spatial dependency, and in the hundred-year period under con-920 Journal of Geographical Sciences sideration, this dependency increases before eventually weakening. Fourth, between 2015 and 2030, urban population hotspots will include Thailand, China, Laos and Albania, while Kuwait, Cyprus, Qatar and Estonia will be urban "coldspots." Fifth, there were 293 cities with populations over 1 million located along the Belt and Road in 2015, but that number is expected to increase to 377 by 2030. Of those, 43 will be in China, with many of the others located in India, Indonesia and the eastern Mediterranean.
Artificial insemination (AI) is an important component of captive breeding programs for endangered species, such as the giant panda. The panda has been the subject of increasingly successful captive breeding programs involving a compilation of assisted breeding techniques, including AI using cryopreserved spermatozoa. AI implementation is currently hampered by a lack of understanding of the factors that may cause failure. We investigated factors influencing the probability of success of AI for 14 giant panda females housed at the China Center for Research and Conservation of the Giant Panda (CCRCGP) inseminated in a total of 20 instances using cryopreserved spermatozoa from 11 males currently residing in 6 different captive breeding institutions. One of the pandas was the oldest giant panda female to ever successfully conceive from AI (20.5 years old). The success of AI was significantly affected by the timing of AI in relationship to both timing of peak urinary estrogen of the female and percent decline in urinary estrogen between the peak level and the first AI attempt. Our results suggest that the window for successful AI in giant pandas may be narrower than previously suspected, although individual differences in rates of decline in urinary estrogen may reflect some degree of variation in this crucial window across females. Our results are consistent with recent research on pandas and other species that demonstrates the efficacy of cryopreserved spermatozoa for AI and highlights the need for more in-depth analysis of factors related to female physiology that may influence its success.
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