scholarly journals Lean Pattern in an Altitude Range Shift of a Tree Species: Abies pinsapo Boiss.

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1451
Author(s):  
Antonio González-Hernández ◽  
Diego Nieto-Lugilde ◽  
Julio Peñas ◽  
Francisca Alba-Sánchez
Keyword(s):  
Lower Limit ◽  
Leading Edge ◽  
Climatic Conditions ◽  
Range Shift ◽  
Distribution Models ◽  
Altitudinal Distribution ◽  
Altitudinal Shift ◽  
Abies Pinsapo ◽  
And Migration

Organisms modify their geographical distributions in response to changes in environmental conditions, or modify their affinity to such conditions, to avoid extinction. This study explored the altitudinal shift of Abies pinsapo Boiss. in the Baetic System. We analysed the potential distribution of the realised and reproductive niches of A. pinsapo populations in the Ronda Mountains (Southern Spain) by using species distribution models (SDMs) for two life stages within the current populations. Then, we calculated the species’ potential altitudinal shifts and identified the areas in which the processes of persistence and migration predominated. The realised and reproductive niches of A. pinsapo are different to one another, which may indicate a displacement in its altitudinal distribution owing to changes in the climatic conditions of the Ronda Mountains. The most unfavourable conditions for the species indicate a trailing edge (~110 m) at the lower limit of its distribution and a leading edge (~55 m) at the upper limit. Even though the differences in the altitudinal shifts between the trailing and leading edges will not cause the populations to become extinct in the short term, they may threaten their viability if the conditions that are producing the contraction at the lower limit persist in the long term.

scholarly journals Humboldt’sTableau Physiquerevisited

2019 ◽  
Vol 116 (26) ◽  
pp. 12889-12894 ◽  
Author(s):  
Pierre Moret ◽  
Priscilla Muriel ◽  
Ricardo Jaramillo ◽  
Olivier Dangles
Keyword(s):  
Environmental Changes ◽  
Original Data ◽  
Range Shift ◽  
Tree Line ◽  
Tropical Andes ◽  
Altitudinal Distribution ◽  
Climate Change Effects ◽  
Altitudinal Shift ◽  
History Of ◽  
Vegetation Belt

Alexander von Humboldt’sTableau Physique(1807) has been one of the most influential diagrams in the history of environmental sciences. In particular, detailed observations of the altitudinal distribution of plant species in the equatorial Andes, depicted on a cross-section of Mt. Chimborazo, allowed Humboldt to establish the concept of vegetation belt, thereby laying the foundations of biogeography. Surprisingly, Humboldt’s original data have never been critically revisited, probably due to the difficulty of gathering and interpreting dispersed archives. By unearthing and analyzing overlooked historical documents, we show that the top section of theTableau Physique, above the tree line, is an intuitive construct based on unverified and therefore partly false field data that Humboldt constantly tried to revise in subsequent publications. This finding has implications for the documentation of climate change effects in the tropical Andes. We found that Humboldt’s primary plant data above tree line were mostly collected on Mt. Antisana, not Chimborazo, which allows a comparison with current records. Our resurvey at Mt. Antisana revealed a 215- to 266-m altitudinal shift over 215 y. This estimate is about twice lower than previous estimates for the region but is consistent with the 10- to 12-m/decade upslope range shift observed worldwide. Our results show the cautious approach needed to interpret historical data and to use them as a resource for documenting environmental changes. They also profoundly renew our understanding of Humboldt’s scientific thinking, methods, and modern relevance.

DOES HARMFUL CLIMATE INCREASE OR DECREASE MIGRATION? EVIDENCE FROM RURAL HOUSEHOLDS IN NIGERIA

2019 ◽  
Vol 10 (04) ◽  
pp. 1950013
Author(s):  
CRISTINA CATTANEO ◽  
EMANUELE MASSETTI
Keyword(s):  
Climate Change ◽  
Adaptation Strategy ◽  
Climatic Conditions ◽  
Marginal Effect ◽  
Cross Sectional ◽  
Temperature Changes ◽  
And Migration ◽  
Migrant Households ◽  
The Impact

This paper analyzes whether migration is an adaptation strategy that households employ to cope with climate in Nigeria. We estimate our model using the cross-sectional variation in climate and long-term migration decisions because we are interested in the average response to long-term climatic conditions. For households that operate farms, we find that the relationship between climate and migration is nonlinear. In particular, climates closer to ideal farming conditions are associated with a higher propensity to migrate, whereas in the least favorable climatic conditions, the propensity to migrate declines. The marginal effect of rainfall and temperature changes on migration varies by season. We estimate the impact of climate change on the number of migrant households in 2031–2060 and 2071–2100, ceteris paribus. With current population levels, climate change generates between 3.6 and 6.3 million additional migrants, most of them being internal. However, these estimates are not statistically significant.

scholarly journals A 1-km global dataset of historical (1979–2017) and future (2020–2100) Köppen-Geiger climate classification and bioclimatic variables

2021 ◽  
Author(s):  
Diyang Cui ◽  
Shunlin Liang ◽  
Dongdong Wang ◽  
Zheng Liu
Keyword(s):  
Climate Change ◽  
Regional Scale ◽  
Climatic Conditions ◽  
Future Climate ◽  
Distribution Models ◽  
Climate Classification ◽  
Climate Change Research ◽  
Climate Zones ◽  
Bioclimatic Variables

Abstract. The Köppen-Geiger classification scheme provides an effective and ecologically meaningful way to characterize climatic conditions and has been widely applied in climate change studies. Significant changes in Köppen climates have been observed and projected in the recent two centuries. Current accuracy, temporal coverage, spatial and temporal resolution of historical and future climate classification maps cannot sufficiently fulfil the current needs of climate change research. Comprehensive assessment of climate change impacts requires a more accurate depiction of fine-grained climatic conditions and continuous long-term time coverage. Here, we present a series of improved 1-km Köppen-Geiger climate classification maps for ten historical periods in 1979–2017 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The historical maps are derived from multiple downscaled observational datasets and the future maps are derived from an ensemble of bias-corrected downscaled CMIP5 projections. In addition to climate classification maps, we calculate 12 bioclimatic variables at 1-km resolution, providing detailed descriptions of annual averages, seasonality, and stressful conditions of climates. The new maps offer higher classification accuracy and demonstrate the ability to capture recent and future projected changes in spatial distributions of climate zones. On regional and continental scales, the new maps show accurate depictions of topographic features and correspond closely with vegetation distributions. We also provide a heuristic application example to detect long-term global-scale area changes of climate zones. This high-resolution dataset of Köppen-Geiger climate classification and bioclimatic variables can be used in conjunction with species distribution models to promote biodiversity conservation and to analyze and identify recent and future interannual or interdecadal changes in climate zones on a global or regional scale. The dataset referred to as KGClim, is publicly available at http://doi.org/10.5281/zenodo.4546140 for historical climate and http://doi.org/10.5281/zenodo.4542076 for future climate.

scholarly journals A 1-km global dataset of historical (1979–2017) and future (2020–2100) Köppen-Geiger climate classification and bioclimatic variables

2021 ◽  
Author(s):  
Diyang Cui ◽  
Shunlin Liang ◽  
Dongdong Wang ◽  
Zheng Liu
Keyword(s):  
Climate Change ◽  
Regional Scale ◽  
Climate Change Impacts ◽  
Global Scale ◽  
Climatic Conditions ◽  
Distribution Models ◽  
Climate Classification ◽  
Climate Zones ◽  
Bioclimatic Variables

Abstract. The Köppen-Geiger climate classification scheme provides an effective and ecologically meaningful way to characterize climatic conditions and has been widely applied in climate change studies. The Köppen-Geiger climate maps currently available are limited by relatively low spatial resolution, poor accuracy, and noncomparable time periods. Comprehensive assessment of climate change impacts requires a more accurate depiction of fine-grained climatic conditions and continuous long-term time coverage. Here, we present a series of improved 1-km Köppen-Geiger climate classification maps for ten historical periods in 1979–2017 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The historical maps are derived from multiple downscaled observational datasets and the future maps are derived from an ensemble of bias-corrected downscaled CMIP5 projections. In addition to climate classification maps, we calculate 12 bioclimatic variables at 1-km resolution, providing detailed descriptions of annual averages, seasonality, and stressful conditions of climates. The new maps offer higher classification accuracy and demonstrate the ability to capture recent and future projected changes in spatial distributions of climate zones. On regional and continental scales, the new maps show accurate depictions of topographic features and correspond closely with vegetation distributions. We also provide a heuristic application example to detect long-term global-scale area changes of climate zones. This high-resolution dataset of Köppen-Geiger climate classification and bioclimatic variables can be used in conjunction with species distribution models to promote biodiversity conservation and to analyze and identify recent and future interannual or interdecadal changes in climate zones on a global or regional scale. The dataset referred to as KGClim, is publicly available at http://doi.org/10.5281/zenodo.4546140 for historical climate and http://doi.org/10.5281/zenodo.4542076 for future climate.

scholarly journals A 1 km global dataset of historical (1979–2013) and future (2020–2100) Köppen–Geiger climate classification and bioclimatic variables

2021 ◽  
Vol 13 (11) ◽  
pp. 5087-5114
Author(s):  
Diyang Cui ◽  
Shunlin Liang ◽  
Dongdong Wang ◽  
Zheng Liu
Keyword(s):  
Climate Change ◽  
Regional Scale ◽  
Climatic Conditions ◽  
Future Climate ◽  
Distribution Models ◽  
Climate Classification ◽  
Climate Change Research ◽  
Climate Zones ◽  
Bioclimatic Variables

Abstract. The Köppen–Geiger classification scheme provides an effective and ecologically meaningful way to characterize climatic conditions and has been widely applied in climate change studies. Significant changes in the Köppen climates have been observed and projected in the last 2 centuries. Current accuracy, temporal coverage and spatial and temporal resolution of historical and future climate classification maps cannot sufficiently fulfill the current needs of climate change research. Comprehensive assessment of climate change impacts requires a more accurate depiction of fine-grained climatic conditions and continuous long-term time coverage. Here, we present a series of improved 1 km Köppen–Geiger climate classification maps for six historical periods in 1979–2013 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The historical maps are derived from multiple downscaled observational datasets, and the future maps are derived from an ensemble of bias-corrected downscaled CMIP5 projections. In addition to climate classification maps, we calculate 12 bioclimatic variables at 1 km resolution, providing detailed descriptions of annual averages, seasonality, and stressful conditions of climates. The new maps offer higher classification accuracy than existing climate map products and demonstrate the ability to capture recent and future projected changes in spatial distributions of climate zones. On regional and continental scales, the new maps show accurate depictions of topographic features and correspond closely with vegetation distributions. We also provide a heuristic application example to detect long-term global-scale area changes of climate zones. This high-resolution dataset of the Köppen–Geiger climate classification and bioclimatic variables can be used in conjunction with species distribution models to promote biodiversity conservation and to analyze and identify recent and future interannual or interdecadal changes in climate zones on a global or regional scale. The dataset referred to as KGClim is publicly available via http://glass.umd.edu/KGClim (Cui et al., 2021d)​​​​​​​ and can also be downloaded at https://doi.org/10.5281/zenodo.5347837 (Cui et al., 2021c) for historical climate and https://doi.org/10.5281/zenodo.4542076 (Cui et al., 2021b) for future climate.

Modelling of Moisture Movement in Wood during Outdoor Storage

2001 ◽  
Vol 6 (2) ◽  
pp. 3-14 ◽  
Author(s):  
R. Baronas ◽  
F. Ivanauskas ◽  
I. Juodeikienė ◽  
A. Kajalavičius
Keyword(s):  
Experimental Data ◽  
Finite Difference ◽  
Climatic Conditions ◽  
Two Dimensional ◽  
Moisture Movement ◽  
Finite Difference Technique ◽  
Long Term Storage ◽  
Space Formulation ◽  
Term Storage

A model of moisture movement in wood is presented in this paper in a two-dimensional-in-space formulation. The finite-difference technique has been used in order to obtain the solution of the problem. The model was applied to predict the moisture content in sawn boards from pine during long term storage under outdoor climatic conditions. The satisfactory agreement between the numerical solution and experimental data was obtained.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

SELECTION WORK TO IMPROVE PRODUCTIVE AND BREWING QUALITIES OF SPRING BARLEY

1970 ◽  
pp. 38-40
Author(s):  
О. V. Levakova ◽  
L. М. Eroshenko ◽  
А. N. Eroshenko
Keyword(s):  
Protein Content ◽  
Spring Barley ◽  
Humus Content ◽  
Stability Index ◽  
Field Studies ◽  
Climatic Conditions ◽  
Extract Content ◽  
Labile Phosphorus ◽  
Loam Soil

The article presents and analyzes data of competitive varietal testing of promising varieties and lines of spring barley for yield and brewing qualities. Field studies were conducted in 2014–2017 on dark gray forest heavy loam soil. Agrochemical parameters are total nitrogen – 0.24%, humus content in a layer of 0-40 cm (according to Tyurin) – 5.19%, hydrolysis nitrogen – 123.5 mg / kg, salt extract pH – 4.92 mg-eq / 100g; labile phosphorus - 34.6 mg / 100g, labile potassium – 20.0 mg / 100g. The forerunner is winter wheat. Meteorological conditions in the years of research differed from each other and from the average long-term value. Barley samples were assessed by the protein content in the grain (GOST 10846-91), extract content (GOST 12130-77), weight 1000 grains (GOST 10842-89). Ecological plasticity was determined by the method proposed by E.D. Nettevich, A.I. Morgunov and M.I. Maksimenko, stability index (Ľ) by A. A. Gryaznov, indicator of stability level (Puss) by E. D. Nettevich and A. I. Morgunov. The main measure for assessing quality indicators is protein content. Many other biochemical and technological features of grain depend on its level. The experimental data convincingly testify to the significant influence of the soil and climatic conditions on the yield and, especially, on the brewing qualities of barley in the conditions of the Central Region of the Nonchernozem Zone. According to the studied traits, new valuable varieties Nadezhny, Sir, Noble and selection lines 141 / 1-09 h 746, 23 / 1-10 h 784, distinguished by high adaptability and resistance to adverse environmental factors, have been identified.

scholarly journals Climate Mobility and Development Cooperation

2021 ◽  
Author(s):  
Robert Stojanov ◽  
Sarah Rosengaertner ◽  
Alex de Sherbinin ◽  
Raphael Nawrotzki
Keyword(s):  
Climate Adaptation ◽  
Human Mobility ◽  
Climate Impacts ◽  
Development Cooperation ◽  
Climate Variability And Change ◽  
Policy Frameworks ◽  
And Migration ◽  
And Function ◽  
Role And Function

AbstractDevelopment cooperation actors have been addressing climate change as a cross-cutting issue and investing in climate adaptation projects since the early 2000s. More recently, as concern has risen about the potential impacts of climate variability and change on human mobility, development cooperation actors have begun to design projects that intentionally address the drivers of migration, including climate impacts on livelihoods. However, to date, we know little about the development cooperation’s role and function in responding to climate related mobility and migration. As such, the main aim of this paper is to outline the policy frameworks and approaches shaping development cooperation actors’ engagement and to identify areas for further exploration and investment. First, we frame the concept of climate mobility and migration and discuss some applicable policy frameworks that govern the issue from various perspectives; secondly, we review the toolbox of approaches that development cooperation actors bring to climate mobility; and third, we discuss the implications of the current Covid-19 pandemic and identify avenues for the way forward. We conclude that ensuring safe and orderly mobility and the decent reception and long-term inclusion of migrants and displaced persons under conditions of more severe climate hazards, and in the context of rising nationalism and xenophobia, poses significant challenges. Integrated approaches across multiple policy sectors and levels of governance are needed. In addition to resources, development cooperation actors can bring data to help empower the most affected communities and regions and leverage their convening power to foster more coordinated approaches within and across countries.

Sign in / Sign up

Export Citation Format

Share Document