scholarly journals Examining floristic boundaries between garden types at the global scale

2014 ◽  
pp. 71 ◽  
Author(s):  
Josep Padullés Cubino ◽  
Josep Vila Subirós ◽  
Carles Barriocanal Lozano
Keyword(s):  
Species Distribution ◽  
Climatic Factors ◽  
Potential Evapotranspiration ◽  
Global Climate ◽  
Global Scale ◽  
Plant Composition ◽  
Goods And Services ◽  
Primary Driver ◽  
Future Income ◽  
Garden Plant

Gardens represent important sources of goods and services for their owners. This functionality translates directly into the types of plants cultivated in a given garden, and terminology has been developed to distinguish each category of garden according to its purpose. The factors explaining the differentiation and distribution of gardens have not previously been explored at the global scale. In this study, the plant lists for 44 sets of gardens from around the world were analyzed to explore their taxonomic similarities and the factors shaping each garden. Several biophysical and socioeconomic variables were examined at the appropriate scale for their roles in garden species distribution. Physical and climatic factors (temperature, rainfall, potential evapotranspiration and distance between settlements) were found to be significantly related with species makeup; all of these factors were less important than GDP per person, a proxy for household income, which was determined to be the primary driver of garden composition. All of the studied socioeconomic factors, such as language similarity among settlements and population density, were significant drivers of species distribution. However, the present analysis omits a number of variables due to data unavailability, such as garden size and owner gender, which have been previously recognized as influences on garden plant composition. The genera cultivated in different gardens were found to be very different from each other, and the definitions of each type are hard to establish from these data alone. Finally, the implications of likely future income variations, such those caused by severe economic crisis, and global climate change on bio-cultural diversity and food security are discussed.

scholarly journals Biotic interactions and climate in species distribution modelling

2019 ◽  
Author(s):  
Daniel P. Bebber ◽  
Sarah J. Gurr
Keyword(s):  
Climate Change ◽  
Species Distribution ◽  
Climatic Factors ◽  
Global Climate ◽  
Biotic Interactions ◽  
Global Scale ◽  
Species Distribution Modelling ◽  
Distribution Modelling ◽  
Host Preferences ◽  
Migration Rates

SummarySpecies have preferred environmental niches 1 and their geographical distributions respond to global climate change 2. Predicting range shifts under climate change has profound implications for conservation of biodiversity 3, provision of ecosystem services, and in the management of invasive species 4. Species distribution modelling (SDM) has largely focussed on climate variations, but biotic interactions, such as predation and competition, can alter potential distributions 5,6 and affect migration rates 7. However, a lack of data on biotic interactions has restricted consideration of these factors for many species 1. Here, we compare the power of biotic and climatic factors as predictors of global distributions of hundreds of crop pests and pathogens (CPPs), for which host preferences are known. We show that host availability is a more important predictor of endobiotic pathogen distributions (fungi, oomycetes, bacteria, viruses and nematodes) than of epibiotic pest distributions (insect herbivores). Conversely, climatic variables are better predictors of epibiotic pest distributions. These results are robust to statistical controls for varying observational capacity among countries. Our findings demonstrate that life history affects global scale species distributions and that SDM should incorporate biotic interactions as well as climate.

scholarly journals Drivers of Marine Heatwaves in the Northwest Atlantic: The Role of Air–Sea Interaction During Onset and Decline

2021 ◽  
Vol 8 ◽  
Author(s):  
Robert W. Schlegel ◽  
Eric C. J. Oliver ◽  
Ke Chen
Keyword(s):  
Heat Flux ◽  
Mixed Layer ◽  
Heat Budget ◽  
Mixed Layer Depth ◽  
Global Scale ◽  
Self Organizing Map ◽  
Physical Processes ◽  
Northwest Atlantic ◽  
Goods And Services ◽  
Primary Driver

Marine heatwaves (MHWs) are increasing in duration and intensity at a global scale and are projected to continue to increase due to the anthropogenic warming of the climate. Because MHWs may have drastic impacts on fisheries and other marine goods and services, there is a growing interest in understanding the predictability and developing practical predictions of these events. A necessary step toward prediction is to develop a better understanding of the drivers and processes responsible for the development of MHWs. Prior research has shown that air–sea heat flux and ocean advection across sharp thermal gradients are common physical processes governing these anomalous events. In this study we apply various statistical analyses and employ the self-organizing map (SOM) technique to determine specifically which of the many candidate physical processes, informed by a theoretical mixed-layer heat budget, have the most pronounced effect on the onset and/or decline of MHWs on the Northwest Atlantic continental shelf. It was found that latent heat flux is the most common driver of the onset of MHWs. Mixed layer depth (MLD) also strongly modulates the onset of MHWs. During the decay of MHWs, atmospheric forcing does not explain the evolution of the MHWs well, suggesting that oceanic processes are important in the decay of MHWs. The SOM analysis revealed three primary synoptic scale patterns during MHWs: low-pressure cyclonic Autumn-Winter systems, high-pressure anti-cyclonic Spring-Summer blocking, and mild but long-lasting Summer blocking. Our results show that nearly half of past MHWs on the Northwest Atlantic shelf are initiated by positive heat flux anomaly into the ocean, but less than one fifth of MHWs decay due to this process, suggesting that oceanic processes, e.g., advection and mixing are the primary driver for the decay of most MHWs.

scholarly journals Contrasting Evolution Patterns of Endorheic and Exorheic Lakes on the Central Tibetan Plateau and Climate Cause Analysis during 1988–2017

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1962
Author(s):  
Zhilong Zhao ◽  
Yue Zhang ◽  
Zengzeng Hu ◽  
Xuanhua Nie
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climatic Factors ◽  
Global Climate ◽  
Rapid Expansion ◽  
Annual Precipitation ◽  
The Tibetan Plateau ◽  
Lake Area ◽  
Climate Change Research ◽  
Mean Temperature

The alpine lakes on the Tibetan Plateau (TP) are indicators of climate change. The assessment of lake dynamics on the TP is an important component of global climate change research. With a focus on lakes in the 33° N zone of the central TP, this study investigates the temporal evolution patterns of the lake areas of different types of lakes, i.e., non-glacier-fed endorheic lakes and non-glacier-fed exorheic lakes, during 1988–2017, and examines their relationship with changes in climatic factors. From 1988 to 2017, two endorheic lakes (Lake Yagenco and Lake Zhamcomaqiong) in the study area expanded significantly, i.e., by more than 50%. Over the same period, two exorheic lakes within the study area also exhibited spatio-temporal variability: Lake Gaeencuonama increased by 5.48%, and the change in Lake Zhamuco was not significant. The 2000s was a period of rapid expansion of both the closed lakes (endorheic lakes) and open lakes (exorheic lakes) in the study area. However, the endorheic lakes maintained the increase in lake area after the period of rapid expansion, while the exorheic lakes decreased after significant expansion. During 1988–2017, the annual mean temperature significantly increased at a rate of 0.04 °C/a, while the annual precipitation slightly increased at a rate of 2.23 mm/a. Furthermore, the annual precipitation significantly increased at a rate of 14.28 mm/a during 1995–2008. The results of this study demonstrate that the change in precipitation was responsible for the observed changes in the lake areas of the two exorheic lakes within the study area, while the changes in the lake areas of the two endorheic lakes were more sensitive to the annual mean temperature between 1988 and 2017. Given the importance of lakes to the TP, these are not trivial issues, and we now need accelerated research based on long-term and continuous remote sensing data.

scholarly journals Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets

2021 ◽  
Vol 13 (9) ◽  
pp. 1716
Author(s):  
Ankur Srivastava ◽  
Jose F. Rodriguez ◽  
Patricia M. Saco ◽  
Nikul Kumari ◽  
Omer Yetemen
Keyword(s):  
Cloud Cover ◽  
Climatic Factors ◽  
Global Analysis ◽  
Empirical Relationship ◽  
Aridity Index ◽  
Global Scale ◽  
Empirical Models ◽  
Coefficient Of Determination ◽  
Crop Modeling ◽  
Atmospheric Transmissivity

Atmospheric transmissivity (τ) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of τ is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate τ. Most of the previous studies provided region specific datasets of τ, which usually provide local assessments. Hence, there is a necessity to give the empirical models for τ estimation on a global scale that can be easily assessed. This study presents the analysis of the τ relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate τ by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r2) was 0.88 relatively higher than the warm temperate (r2 = 0.74) and arid regions (r2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the τ in different ecosystems across the globe.

scholarly journals Structural equation modeling to shed light on the controversial role of climate on the spread of SARS-CoV-2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alessia Spada ◽  
Francesco Antonio Tucci ◽  
Aldo Ummarino ◽  
Paolo Pio Ciavarella ◽  
Nicholas Calà ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Population Density ◽  
Structural Equation ◽  
Climatic Factors ◽  
Demographic Data ◽  
Factor Loading ◽  
Statistical Technique ◽  
Global Scale ◽  
Equation Modeling ◽  
Relevant Role

AbstractClimate seems to influence the spread of SARS-CoV-2, but the findings of the studies performed so far are conflicting. To overcome these issues, we performed a global scale study considering 134,871 virologic-climatic-demographic data (209 countries, first 16 weeks of the pandemic). To analyze the relation among COVID-19, population density, and climate, a theoretical path diagram was hypothesized and tested using structural equation modeling (SEM), a powerful statistical technique for the evaluation of causal assumptions. The results of the analysis showed that both climate and population density significantly influence the spread of COVID-19 (p < 0.001 and p < 0.01, respectively). Overall, climate outweighs population density (path coefficients: climate vs. incidence = 0.18, climate vs. prevalence = 0.11, population density vs. incidence = 0.04, population density vs. prevalence = 0.05). Among the climatic factors, irradiation plays the most relevant role, with a factor-loading of − 0.77, followed by temperature (− 0.56), humidity (0.52), precipitation (0.44), and pressure (0.073); for all p < 0.001. In conclusion, this study demonstrates that climatic factors significantly influence the spread of SARS-CoV-2. However, demographic factors, together with other determinants, can affect the transmission, and their influence may overcome the protective effect of climate, where favourable.

scholarly journals Reduced resilience of terrestrial ecosystems locally is not reflected on a global scale

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Yuhao Feng ◽  
Haojie Su ◽  
Zhiyao Tang ◽  
Shaopeng Wang ◽  
Xia Zhao ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Vegetation Index ◽  
Global Climate ◽  
Terrestrial Ecosystem ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Ecological Resilience ◽  
Terrestrial Vegetation ◽  
Ecosystem Resilience

AbstractGlobal climate change likely alters the structure and function of vegetation and the stability of terrestrial ecosystems. It is therefore important to assess the factors controlling ecosystem resilience from local to global scales. Here we assess terrestrial vegetation resilience over the past 35 years using early warning indicators calculated from normalized difference vegetation index data. On a local scale we find that climate change reduced the resilience of ecosystems in 64.5% of the global terrestrial vegetated area. Temperature had a greater influence on vegetation resilience than precipitation, while climate mean state had a greater influence than climate variability. However, there is no evidence for decreased ecological resilience on larger scales. Instead, climate warming increased spatial asynchrony of vegetation which buffered the global-scale impacts on resilience. We suggest that the response of terrestrial ecosystem resilience to global climate change is scale-dependent and influenced by spatial asynchrony on the global scale.

scholarly journals Spurious North Tropical Atlantic precursors to El Niño

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wenjun Zhang ◽  
Feng Jiang ◽  
Malte F. Stuecker ◽  
Fei-Fei Jin ◽  
Axel Timmermann
Keyword(s):  
El Niño ◽  
Cross Correlation ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Tropical Atlantic ◽  
The North ◽  
Sst Variability ◽  
Primary Driver ◽  
North Tropical Atlantic

AbstractThe El Niño-Southern Oscillation (ENSO), the primary driver of year-to-year global climate variability, is known to influence the North Tropical Atlantic (NTA) sea surface temperature (SST), especially during boreal spring season. Focusing on statistical lead-lag relationships, previous studies have proposed that interannual NTA SST variability can also feed back on ENSO in a predictable manner. However, these studies did not properly account for ENSO’s autocorrelation and the fact that the SST in the Atlantic and Pacific, as well as their interaction are seasonally modulated. This can lead to misinterpretations of causality and the spurious identification of Atlantic precursors for ENSO. Revisiting this issue under consideration of seasonality, time-varying ENSO frequency, and greenhouse warming, we demonstrate that the cross-correlation characteristics between NTA SST and ENSO, are consistent with a one-way Pacific to Atlantic forcing, even though the interpretation of lead-lag relationships may suggest otherwise.

scholarly journals The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments

2010 ◽  
Vol 14 (11) ◽  
pp. 2193-2205 ◽  
Author(s):  
J. L. Peña-Arancibia ◽  
A. I. J. M. van Dijk ◽  
M. Mulligan ◽  
L. A. Bruijnzeel
Keyword(s):  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Global Scale ◽  
Tree Cover ◽  
Annual Rainfall ◽  
Ungauged Catchments ◽  
Ongoing Research ◽  
Daily Streamflow ◽  
Terrain Attributes ◽  
Streamflow Data

Abstract. The understanding of low flows in rivers is paramount more than ever as demand for water increases on a global scale. At the same time, limited streamflow data to investigate this phenomenon, particularly in the tropics, makes the provision of accurate estimations in ungauged areas an ongoing research need. This paper analysed the potential of climatic and terrain attributes of 167 tropical and sub-tropical unregulated catchments to predict baseflow recession rates. Daily streamflow data (m3 s–1) from the Global River Discharge Center (GRDC) and a linear reservoir model were used to obtain baseflow recession coefficients (kbf) for these catchments. Climatic attributes included annual and seasonal indicators of rainfall and potential evapotranspiration. Terrain attributes included indicators of catchment shape, morphology, land cover, soils and geology. Stepwise regression was used to identify the best predictors for baseflow recession coefficients. Mean annual rainfall (MAR) and aridity index (AI) were found to explain 49% of the spatial variation of kbf. The rest of climatic indices and the terrain indices average catchment slope (SLO) and tree cover were also good predictors, but co-correlated with MAR. Catchment elongation (CE), a measure of catchment shape, was also found to be statistically significant, although weakly correlated. An analysis of clusters of catchments of smaller size, showed that in these areas, presumably with some similarity of soils and geology due to proximity, residuals of the regression could be explained by SLO and CE. The approach used provides a potential alternative for kbf parameterisation in ungauged catchments.

scholarly journals Global phosphorus dynamics in terms of phosphine

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Wanyi Fu ◽  
Xihui Zhang
Keyword(s):  
Wastewater Treatment ◽  
Human Activities ◽  
Wastewater Treatment Plants ◽  
Global Climate ◽  
Global Scale ◽  
Phosphorus Cycle ◽  
Natural Ecosystems ◽  
Driving Cycles ◽  
Global Cycles ◽  
Urban Wastewater Treatment

AbstractSince the detection of phosphine in the wastewater treatment plants in 1988, more and more investigations revealed that phosphine is closely related to ecological activities on a global scale. Here, we present perspectives on the whole dynamic cycles of phosphorus, particularly in terms of phosphine and its interactions with natural ecosystems, as well as the impacts from human activities. It may conclude that the phosphine-driving cycles of phosphorus depend on the coordination of human activities with natural ecosystems. Most importantly, the extensive recovery of phosphorus in numerous urban wastewater treatment plants may seriously obstruct its global cycles to catch up with the ecological needs in natural ecosystems. Phosphine gas plays an important role in the biogeochemical phosphorus cycle. Phosphorus might be one of the important elements participating in the global climate change together with carbon and nitrogen.

Ramification of Global and Local Climatic Variability on Resurgent Cases of Dengue in Delhi, India

2021 ◽  
Vol 14 (7) ◽  
pp. 32-41
Author(s):  
Netrananda Sahu ◽  
Martand Mani Mishra
Keyword(s):  
Climatic Factors ◽  
Global Climate ◽  
Climatic Variability ◽  
Climatic Variation ◽  
Statistical Tool ◽  
High Positive Correlation ◽  
Local Climate ◽  
Vector Borne Diseases ◽  
Monsoon Index ◽  
Vector Borne

It has become evident that the global climate is changing rapidly over the past few decades. The variation and change in the global climatic factors have a notable impact on the local climate of a region. The changing climate is widely regarded as one of the most serious global health threats of the 21st century. Among various kinds of diseases, the most vulnerable to these changes are vector-borne diseases. In the Indian context, particularly Delhi city is the most vulnerable to dengue, a kind of vector-borne disease having its highest impact. We sought to identify and explore the correlation and influence of the global climatic phenomena and local climatic factors with the reported number of dengue cases in Delhi. The temporal expansions of reported dengue cases in Delhi have a variation from its first major outbreak in the city during the year 1996 to 2015. A statistical tool like Pearson Product Moment Correlation (PPMC) is used in this study to establish the interrelationship and the level of impact and local climatic variation on dengue. An exceptional negative correlation value of r = -0.82 between the monsoon index and the dengue incidences was reported during the positive years and also maintains a very high positive correlation with other global climatic indices. The study here finds that there is a strong correlation of climatic variation which further influences the epidemiology of dengue in Delhi.

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