This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. AbstractAim: We explore the phylogeography of Himalayan wolves using multiple genetic markers applied on a landscape-scale dataset and relate our findings to the biogeographic history of the region. Location: Himalayas of Nepal, the Tibetan Plateau of China and mountain ranges of Central Asia. Taxon: Himalayan wolf (also called the Tibetan wolf), Canis lupus chanco. Methods: We present a large-scale, non-invasive study of Himalayan wolves from across their estimated range. We analysed 280 wolf scat samples from western China, Kyrgyzstan and Tajikistan at two mtDNA loci, 17 microsatellite loci, four nonsynonymous SNPs in three nuclear genes related to the hypoxia pathway, and ZF genes on both sex chromosomes. | 1273 WERHAHN Et Al.

To understand the contemporary and anticipated future (future 30–50 years) distribution of Chinese wild yellowhorn (Xanthoceras sorbifolium Bunge) and to improve the species’ in situ conservation strategy within the network of China’s National Nature Reserves (NNR), we used BiodiversityR to predict the species’ distribution utilizing the “always-suitable” map concept. We then delineated the always-suitable distributions with the existing NNRs to identify potential conservation areas using an approach that concurrently considered spatial distribution, gap analysis, the role of climate change, and economic analyses. Seven bioclimatic variable predictors and 12 environmental niche modelling submodels successfully contributed to the final model assembly (AUC = 0.916, κ = 0.398). The species range delineation indicated that 71 of the 427 NNRs were included in the always-suitable area, accounting for 26 007 km2 (1.58%) of the species total distribution. This mapping endeavour highlighted the negative impact of climate change with a projected 15%–20% habitat decline and expected species’ distribution centers shifting from the country’s northwest to the southeast. Our results predict the continuous deterioration of X. sorbifolium because of its existing utilization as an oil source and its increased bioenergy potential. The adoption of a flexible management strategy embracing acceptable trade-offs between conservation and utilization within China’s NNRs could effectively alleviate the expected species decline.

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We embraced the ''learning from nature and back to nature'' paradigm to develop viable agroforestry scenarios through studying species association in 12 wild yellowhorn (Xanthoceras sorbifolium: a Chinese endemic oil woody plants) communities. We identified 18 species combinations for their suitability as agroforestry mixes where positive associations were detected and thus economic benefits are anticipated. In each wild yellowhorn community, we use nonmetric multidimensional scaling ordination to assess community structure and composition, and the climatic variables that most likely influenced existing species distributions. Next, pairwise and multiple species associations were evaluated using several multiple species association indices (e.g., v 2 , Jaccard, Ochiai, Dice). Generally, all species association indices were in agreement and were helpful in identifying several high valued medicinal species that showed positive and significant associations with yellowhorn. Finally, we proposed several agroforestry species mixes suitable for yellowhorn. Keywords Xanthoceras sorbifolium Á Species association and selection Á Agroforestry mixes Á Nonmetric multidimensional scaling ordination (NMDS) Qing Wang and Renbin Zhu have contributed equally to this work.

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