scholarly journals Shifts in potential geographical distribution of Pterocarya stenoptera under climate change scenarios in China

2020 ◽  
Vol 10 (11) ◽  
pp. 4828-4837
Author(s):  
Keliang Zhang ◽  
Huina Liu ◽  
Haolei Pan ◽  
Wenhao Shi ◽  
Yi Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Climate Change Scenarios ◽  
Pterocarya Stenoptera

scholarly journals Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia

2020 ◽  
Vol 21 (10) ◽  
Author(s):  
AHMAD DWI SETYAWAN ◽  
JATNA SUPRIATNA ◽  
NISYAWATI NISYAWATI ◽  
ILYAS NURSAMSI ◽  
SUTARNO SUTARNO ◽  
...  
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Flowering Plant ◽  
Distribution Model ◽  
Climate Change Scenarios ◽  
Mountainous Areas ◽  
Bioclimatic Variables ◽  
Suitable Habitats ◽  
High Level ◽  
Impacts Of Climate Change

Abstract. Setyawan AD, Supriatna J, Nisyawati, Nursamsi I, Sutarno, Sugiyarto, Sunarto, Pradan P, Budiharta S, Pitoyo A, Suhardono S, Setyono P, Indrawan M. 2020. Predicting potential impacts of climate change on the geographical distribution of mountainous selaginellas in Java, Indonesia. Biodiversitas 21: 4866-4877. Selaginella is a genus of non-flowering plant that requires water as a medium for fertilization, as such, it prefers mountainous areas with high level of humidity. Such unique ecosystem of Selaginella is available in some parts of Java Island, Indonesia, especially in highland areas with altitude of more than 1,000 meters above sea level. However, most mountainous areas in Java are likely to be affected by climate change due to global warming, threatening the habitat and sustainability of Selaginella. This study aimed to investigate the impacts of climate change on the geographical distribution of Selaginella opaca Warb. and Selaginella remotifolia Spring. In doing so, we predicted the suitable habitats of both species using Species Distribution Model (SDM) tool of MaxEnt under present climate conditions and future conditions under four climate change scenarios. Species occurrence data were obtained from fieldworks conducted in 2007-2014 across Java Island (283 points: 144 and 139 points for S. opaca and S. remotifolia, respectively) and combined with secondary data from Global Biodiversity Information Facility (GBIF) (52 points: 35 and 17 points for S. opaca and S. remotifolia, respectively), and this dataset was used to model present geographical distribution using environmental and bioclimatic variables. Then, future distribution was predicted under four climate change scenarios: i.e. RCP (Representative Carbon Pathways) 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 in three different time periods (2030, 2050, and 2080). The results of the models showed that the extent of suitable habitats of S. opaca and S. remotifolia will be reduced between 1.8-11.4% due to changes in climatic condition, and in the areas with high level of habitat suitability, including Mount Sumbing, Mount Sindoro and Mount Dieng (Dieng Plateau), the reduction can reach up to 60%. This study adds another context of evidence to understand the potential impacts of climate change on biodiversity, especially on climate-sensitive species, such as Selaginella, in climate-risk regions like mountainous areas of Java Island.

scholarly journals Spatio-temporal effects of climate change on the geographical distribution and flowering phenology of hummingbird-pollinated plants

2019 ◽  
Vol 124 (3) ◽  
pp. 389-398 ◽  
Author(s):  
Ana Paula Araujo Correa-Lima ◽  
Isabela Galarda Varassin ◽  
Narayani Barve ◽  
Victor Pereira Zwiener
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Plant Species ◽  
Ecological Niche ◽  
Flowering Phenology ◽  
Climate Change Scenarios ◽  
Niche Modelling ◽  
Distribution Models ◽  
Tropical Plants ◽  
Tropical Plant

Abstract Backgrounds and Aims Tropical plant species are already suffering the effects of climate change and projections warn of even greater changes in the following decades. Of particular concern are alterations in flowering phenology, given that it is considered a fitness trait, part of plant species ecological niche, with potential cascade effects in plant–pollinator interactions. The aim of the study was to assess the potential impacts of climate change on the geographical distribution and flowering phenology of hummingbird-pollinated plants. Methods We implemented ecological niche modelling (ENM) to investigate the potential impacts of different climate change scenarios on the geographical distribution and flowering phenology of 62 hummingbird-pollinated plant species in the Brazilian Atlantic Forest. Key Results Distribution models indicate future changes in the climatic suitability of their current habitats, suggesting a tendency towards discontinuity, reduction and spatial displacement. Flowering models indicate that climate can influence species phenology in different ways: some species may experience increased flowering suitability whereas others may suffer decreased suitability. Conclusions Our results suggest that hummingbird-pollinated species are prone to changes in their geographical distribution and flowering under different climate scenarios. Such variation may impact the community structure of ecological networks and reproductive success of tropical plants in the near future.

scholarly journals Predictions of potential geographical distribution of Diaphorina citri (Kuwayama) in China under climate change scenarios

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rulin Wang ◽  
Hua Yang ◽  
Mingtian Wang ◽  
Zhe Zhang ◽  
Tingting Huang ◽  
...  
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Climate Change Scenarios ◽  
Diaphorina Citri

scholarly journals IMPACT OF CLIMATE CHANGE ON THE GEOGRAPHICAL DISTRIBUTION OF A CLOUD FOREST INDICATOR TREE SPECIES

2020 ◽  
Vol 44 ◽  
Author(s):  
Guilherme Neto dos Santos ◽  
Ana Carolina da Silva ◽  
Pedro Higuchi
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Tree Species ◽  
Cloud Forest ◽  
High Impact ◽  
Future Climate ◽  
Conservation Strategies ◽  
Future Climate Change ◽  
Change Scenario ◽  
Climate Change Scenarios

ABSTRACT The cloud forests are threatened due to the climate change process. Investigations seeking to predict how future climate change will affect species are of great importance as they are fundamental to generating conservation strategies. We aimed to detect how climate change affects the potential geographical distribution of Drimys angustifolia Miers, a tree species that is an indicator of the upper-montane cloud forest in the Brazilian subtropical Atlantic Forest. The areas where D. angustifolia occurs were obtained from geographic coordinates available in scientific publications and the Global Biodiversity Information database. For climate niche modeling, we used the maximum entropy algorithm with 19 climate variables. Two climate change scenarios were considered for 2061-2080: one of low and one of high impact. D. angustifolia predominantly occurs in the upper-montane forests and is absent from dry and warm sites. The variables that best explained the D. angustifolia climatic niche were mean temperature of the warmest quarter, precipitation of driest month, and precipitation of the warmest quarter. Both scenarios indicated changes towards a more tropical regional future climate. Under the low impact climate change scenario, D. angustifolia coverage declined by 68.24% (± 7.32%) across its area of potential occurrence; it declined by 79.15% (± 9.65%) under the high impact scenario. In conclusion, the results of the present study showed that D. angustifolia and its associated ecosystem are threatened by the potential impacts of future climate change. Consequently, we highlight climatically stable areas for the occurrence of D. angustifolia, such as those located in the highest parts of the mountain ranges of the southern and southeastern regions of Brazil, which should be considered as priority areas for protection and conservation.

scholarly journals MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier

2020 ◽  
Vol 12 (7) ◽  
pp. 2671 ◽  
Author(s):  
H. Oğuz Çoban ◽  
Ömer K. Örücü ◽  
E. Seda Arslan
Keyword(s):  
Climate Change ◽  
Geographical Distribution ◽  
Potential Distribution ◽  
Climate Change Scenarios ◽  
Change Analysis ◽  
Climate System Model ◽  
Study Results ◽  
Bioclimatic Variables ◽  
Rcp 8.5 ◽  
Future Potential

The purpose of the study was to model the current and potential future distribution of Quercus libani Olivier (Lebanon Oak), a tree species in Turkey, and to predict the changes in its geographical distribution under different climate change scenarios. In this study, 19 bioclimatic variables at a spatial resolution of 30 arc seconds (~1 km2) were used, collected from the WorldClim database. The bioclimatic data with high correlation according to 31 sets of presence data on the species were reduced with principal component analysis (PCA), and the current and potential distribution were identified using MaxEnt 3.4.1 software. In order to predict how the distribution of the species will be affected by climate change, its potential geographical distribution by 2050 and 2070 was modeled under the Representative Concentration Pathways (RCP) RCP 4.5 and RCP 8.5 scenarios of the species using the Community Climate System Model (CCSM, version 4), which is a climate change model based on the report of the fifth Intergovernmental Panel on Climate Change (IPCC). Change analysis was performed to determine the spatial differences between its current and future distribution areas. The study results showed that the suitable areas for the current distribution of Quercus libani Olivier cover 72,819 km2. Depending on the CCSM4 climate model, the suitable area will decline to 67,580 km2 by 2070, according to the RCP 4.5 scenario, or 63,390 km2 in the RCP 8.5 scenario. This may lead to a reduction in the future population of this species. The change analysis showed that suitable and highly suitable areas will decrease under global climate change scenarios (RCP 4.5 and RCP 8.5) for both current and future potential distribution areas. In this context, our study results indicate that for the management of this species, protective environmental measures should be taken, and climate change models need to be considered in land use and forest management planning.

Modelling impacts of different climate change scenarios on soil water regime of a Mollisol

2005 ◽  
Vol 33 (1) ◽  
pp. 185-188 ◽  
Author(s):  
Csilla Farkas ◽  
Roger Randriamampianina ◽  
Juraj Majerčak
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Water Regime ◽  
Climate Change Scenarios ◽  
Soil Water Regime

scholarly journals Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

2021 ◽  
Author(s):  
Mark Cooper ◽  
Kai P. Voss-Fels ◽  
Carlos D. Messina ◽  
Tom Tang ◽  
Graeme L. Hammer
Keyword(s):  
Climate Change ◽  
Crop Improvement ◽  
Target Population ◽  
Crop Productivity ◽  
Climate Change Scenarios ◽  
Global Food Security ◽  
Genotype By Environment ◽  
Improvement Strategies ◽  
Yield Gaps ◽  
On Farm

Abstract Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

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