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Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change.

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We conducted a snow depth 0 cm (non-snowpack), 10 cm, 20 cm, 30 cm and natural depth) gradient experiment under four quantities of nitrogen addition (control, no added N; low-N, 5 g N m−2 yr−1; medium-N, 10 g N m−2 yr−1; and high-N, 15 g N m−2 yr−1) and took an-entire-year measurements of soil respiration (Rs) in Korean pine forests in northeastern China during 2013–2014. No evidence for effects of N on Rs could be found during the growing season. On the other hand, reduction of snowpack decreased winter soil respiration due to accompanied relatively lower soil temperature. We found that winter temperature sensitivities (Q10) of Rs were significantly higher than the growing season Q10 under all the N addition treatments. Moderate quantities of N addition (low-N and medium-N) significantly increased temperature sensitivities (Q10) of Rs, but excessive (high-N) addition decreased it during winter. The Gamma empirical model predicted that winter Rs under the four N addition treatments contributed 4.8. ± 0.3% (control), 3.6 ± 0.6% (low-N), 4.3 ± 0.4% (medium-N) and 6.4 ± 0.5% (high-N) to the whole year Rs. Our results demonstrate that N deposition will alter Q10 of winter Rs. Moreover, winter Rs may contribute very few to annual Rs budget.

As crucial terrestrial ecosystems, temperate forests play an important role in global soil carbon dioxide flux, and this process can be sensitive to atmospheric nitrogen deposition. It is often reported that the nitrogen addition induces a change in soil carbon dioxide emission in growing season. However, the important effects of interactions between nitrogen deposition and the freeze-thaw-cycle have never been investigated. Here we show nitrogen deposition delays spikes of soil respiration and weaken soil respiration. We found the nitrogen addition, time and nitrogen addition×time exerted the negative impact on the soil respiration of spring freeze-thaw periods due to delay of spikes and inhibition of soil respiration (p < 0.001). The values of soil respiration were decreased by 6% (low-nitrogen), 39% (medium-nitrogen) and 36% (high-nitrogen) compared with the control. And the decrease values of soil respiration under medium- and high-nitrogen treatments during spring freeze-thaw-cycle period in temperate forest would be approximately equivalent to 1% of global annual C emissions. Therefore, we show interactions between nitrogen deposition and freeze-thaw-cycle in temperate forest ecosystems are important to predict global carbon emissions and sequestrations. We anticipate our finding to be a starting point for more sophisticated prediction of soil respirations in temperate forests ecosystems.