Influence of nonclimatic factors on the habitat prediction of tree species and an assessment of the impact of climate change

2011 ◽  
Vol 9 (1) ◽  
pp. 111-120 ◽  
Author(s):  
Motoki Higa ◽  
Ikutaro Tsuyama ◽  
Katsuhiro Nakao ◽  
Etsuko Nakazono ◽  
Tetsuya Matsui ◽  
...  
2015 ◽  
Vol 38 (4) ◽  
pp. 303-308
Author(s):  
Vikas Kumar ◽  
R.K. Dhaliwal ◽  
Charan Singh ◽  
Manmeet Kaur

The present study was carried in different geographical regions of Punjab with the aim to evaluate the impact of climate change on the faunal and floral diversity. A multistage random sampling design was followed to select the study area. Species richness, evenness, Simpson index, Shannon-Wiener index, Index of dominance, Similarity and dissimilarity index were calculated. Comparative performance of different species in different locations was studied in term of present and past status. The number of forest tree species in Hoshiarpur, Ludhiana and Bathinda did not show any change in forest tree species and remain same without any change in bio-diversity index. The number of fruit tree species has been increased comparatively in all three localities. The number of bird’s species has been decreased comparatively in all three localities due to change in climatic condition, whereas, incremental changes were recorded in number of individuals of animals, however number of species is remained unchanged. The number of wild species has been decreased comparatively in all three localities. Ecological indices revealed that diversity index, species richness and evenness index were increased in all three localities; however, Index of Dominance was reduced.


2020 ◽  
Author(s):  
Moonil Kim ◽  
Nick Strigul ◽  
Elena Rovenskaya ◽  
Florian Kraxner ◽  
Woo-Kyun Lee

<p>The velocity and impact of climate change on forest appear to be site, environment, and tree species-specific. The primary objective of this research is to assess the changes in productivity of major temperate tree species in South Korea using terrestrial inventory and satellite remote sensing data. The area covered by each tree species was further categorized into either lowland forest (LLF) or high mountain forest (HMF) and investigated. We used the repeated Korean national forest inventory (NFI) data to calculate a stand-level annual increment (SAI). We then compared the SAI, a ground-based productivity measure, to MODIS net primary productivity (NPP) as a measure of productivity based on satellite imagery. In addition, the growth index of each increment core, which eliminated the effect of tree age on radial growth, was derived as an indicator of the variation of productivity by tree species over the past four decades. Based on these steps, we understand the species- and elevation-dependent dynamics. The secondary objective is to predict the forest dynamics under climate change using the Perfect Plasticity Approximation with Simple Biogeochemistry (PPA-SiBGC) model. The PPA-SiBGC is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the major species by using NFI and increment core data. We predicted forest dynamics using the following time-series metrics: Net ecosystem exchange, aboveground biomass, belowground biomass, C, N, soil respiration, and relative abundance. We then focus on comparing the impact of climate change on LLF and HMF. The results of our study can be used to develop climate-smart forest management strategies to ensure that both LLF and HMF continue to be resilient and continue to provide a wide range of ecosystem services in the Eastern Asian region.</p>


Author(s):  
N. Maidanovych ◽  

The purpose of this work is to review and analyze the main results of modern research on the impact of climate change on the agro-sphere of Ukraine. Results. Analysis of research has shown that the effects of climate change on the agro-sphere are already being felt today and will continue in the future. The observed climate changes in recent decades have already significantly affected the shift in the northern direction of all agro-climatic zones of Europe, including Ukraine. From the point of view of productivity of the agro-sphere of Ukraine, climate change will have both positive and negative consequences. The positives include: improving the conditions of formation and reducing the harvesting time of crop yields; the possibility of effective introduction of late varieties (hybrids), which require more thermal resources; improving the conditions for overwintering crops; increase the efficiency of fertilizer application. Model estimates of the impact of climate change on wheat yields in Ukraine mainly indicate the positive effects of global warming on yields in the medium term, but with an increase in the average annual temperature by 2 ° C above normal, grain yields are expected to decrease. The negative consequences of the impact of climate change on the agrosphere include: increased drought during the growing season; acceleration of humus decomposition in soils; deterioration of soil moisture in the southern regions; deterioration of grain quality and failure to ensure full vernalization of grain; increase in the number of pests, the spread of pathogens of plants and weeds due to favorable conditions for their overwintering; increase in wind and water erosion of the soil caused by an increase in droughts and extreme rainfall; increasing risks of freezing of winter crops due to lack of stable snow cover. Conclusions. Resource-saving agricultural technologies are of particular importance in the context of climate change. They include technologies such as no-till, strip-till, ridge-till, which make it possible to partially store and accumulate mulch on the soil surface, reduce the speed of the surface layer of air and contribute to better preservation of moisture accumulated during the autumn-winter period. And in determining the most effective ways and mechanisms to reduce weather risks for Ukrainian farmers, it is necessary to take into account the world practice of climate-smart technologies.


2012 ◽  
Vol 20 (1) ◽  
pp. 108-115 ◽  
Author(s):  
Wu Weiwei ◽  
Xu Haigen ◽  
Wu Jun ◽  
Cao Mingchang

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