scholarly journals Predictors of the long-term conservation value of sites in a mechanistic metacommunity model

2021 ◽  
Author(s):  
Jacob L Dinner O'Sullivan ◽  
Christopher Terry ◽  
Ramesh Wilson ◽  
Axel Rossberg
Keyword(s):  
Parameter Range ◽  
Conservation Priorities ◽  
Total Biomass ◽  
Relevant Parameter ◽  
Observation Data ◽  
Conservation Value ◽  
Species Loss ◽  
Biomass Loss ◽  
Small Sites

Conserving biodiversity often requires assessment of which sites should be prioritised for protection. Sites are often selected based on area or connectivity, with the assumption that a site's long-term conservation value, as defined by the number of regional species extinctions its removal causes, is smallest for small, disconnected sites. In a simulation study of a mechanistic metacommunity model we find across the parameter range studied that site area is a good predictor of biomass loss following site removal but an insufficient predictor of the long-term species losses incurred as a result. We show that, out of five conceptually distinct predictors tested, including biodiversity, area and connectivity measures, the strongest predictor of long-term species loss (conservation value) is compositional distinctness (average between-site Bray-Curtis dissimilarity) of the impacted community. In extreme cases, small sites located in highly distinct habitats can lead to more species loss when removed than large sites located in more common habitats. Fitting our model to observation data on Andean diatoms and Brazilian lichen-fungi, we show that compositional distinctness exceeds area (total biomass) as a predictor of long-term species losses in the empirically relevant parameter range. Since conservation is primarily concerned with maintaining biodiversity, as opposed to undifferentiated biomass, our results robustly demonstrate that site area alone is not sufficient to gauge conservation priorities; comparative assessment of the community composition of sites is essential.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Evaluations of Surface PM10 Concentration and Chemical Compositions in MERRA-2 Aerosol Reanalysis over Central and Eastern China

2021 ◽  
Vol 13 (7) ◽  
pp. 1317
Author(s):  
Xiaodan Ma ◽  
Peng Yan ◽  
Tianliang Zhao ◽  
Xiaofang Jia ◽  
Jian Jiao ◽  
...  
Keyword(s):  
Eastern China ◽  
Mainland China ◽  
Chemical Components ◽  
Chemical Compositions ◽  
Observation Data ◽  
Causative Factors ◽  
Routine Sampling ◽  
Aerosol Compositions ◽  
Modern Era

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

scholarly journals Long-Term Observations of Beach Variability at Hasaki, Japan

2020 ◽  
Vol 8 (11) ◽  
pp. 871
Author(s):  
Masayuki Banno ◽  
Satoshi Nakamura ◽  
Taichi Kosako ◽  
Yasuyuki Nakagawa ◽  
Shin-ichi Yanagishima ◽  
...  
Keyword(s):  
Morphological Change ◽  
High Frequency ◽  
Climate Changes ◽  
Wave Climate ◽  
Time Interval ◽  
Observation Data ◽  
Beach Profile ◽  
Water Level Variations ◽  
Monthly Variations

Long-term beach observation data for several decades are essential to validate beach morphodynamic models that are used to predict coastal responses to sea-level rise and wave climate changes. At the Hasaki coast, Japan, the beach profile has been measured for 34 years at a daily to weekly time interval. This beach morphological dataset is one of the longest and most high-frequency measurements of the beach morphological change worldwide. The profile data, with more than 6800 records, reflect short- to long-term beach morphological change, showing coastal dune development, foreshore morphological change and longshore bar movement. We investigated the temporal beach variability from the decadal and monthly variations in elevation. Extremely high waves and tidal anomalies from an extratropical cyclone caused a significant change in the long-term bar behavior and foreshore slope. The berm and bar variability were also affected by seasonal wave and water level variations. The variabilities identified here from the long-term observations contribute to our understanding of various coastal phenomena.

Long-term (47 yr) effects of tillage and frequency of summerfallow on soil organic carbon in a Dark Brown Chernozem soil in western Canada

2016 ◽  
Vol 96 (4) ◽  
pp. 347-350 ◽  
Author(s):  
Elwin G. Smith ◽  
H. Henry Janzen ◽  
Lauren Scherloski ◽  
Francis J. Larney ◽  
Benjamin H. Ellert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Concentration ◽  
Western Canada ◽  
Conservation Value ◽  
Chernozem Soil ◽  
No Till ◽  
Organic Carbon Concentration ◽  
Annual Changes

After 47 yr of no-till and reduced summerfallow at Lethbridge, Alberta, soil organic carbon concentration and stocks increased 2.14 g kg−1 and 2.22 Mg ha−1, respectively, in the surface 7.5 cm layer. These findings confirmed the conservation value of reducing tillage and summerfallow. The annual changes were relatively small.

scholarly journals Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

2021 ◽  
Vol 13 (4) ◽  
pp. 680
Author(s):  
Lei Wang ◽  
Wen Zhuo ◽  
Zhifang Pei ◽  
Xingyuan Tong ◽  
Wei Han ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arabian Peninsula ◽  
Vegetation Coverage ◽  
Observation Data ◽  
Desert Locust ◽  
Meteorological Observations ◽  
Earth Observation Data ◽  
Vegetation Loss

Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gregarization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust swarms would fly into the Indochina Peninsula and Southwest China.

Earth observation data for assessing biodiversity conservation priorities in South Asia

2018 ◽  
Vol 28 (8-9) ◽  
pp. 2197-2219 ◽  
Author(s):  
C. Sudhakar Reddy ◽  
V. S. Faseela ◽  
Anjaly Unnikrishnan ◽  
C. S. Jha
Keyword(s):  
South Asia ◽  
Biodiversity Conservation ◽  
Earth Observation ◽  
Conservation Priorities ◽  
Observation Data ◽  
Earth Observation Data

Exploring the relationships between urban form metrics and the vegetation biomass loss under urban expansion in China

2018 ◽  
Vol 47 (3) ◽  
pp. 363-380
Author(s):  
Tong Zhang ◽  
Sophia Shuang Chen ◽  
Guangyu Li
Keyword(s):  
Urban Form ◽  
Urban Areas ◽  
Yangtze River ◽  
Green Space ◽  
Yangtze River Delta ◽  
Urban Morphology ◽  
Total Biomass ◽  
Urban Metrics ◽  
Biomass Loss ◽  
Loss Index

Compact urban form has been applied as a strategy to reduce the loss of green space that occurs from development, but the impact of this policy on the provision of green space still presents many uncertainties. This research investigated the statistical relationship between urban form indicators and the loss of vegetation biomass to understand the response of quality green space provision to changes in urban morphology. A methodology combining multi-source data assimilation, statistical analysis, and spatial analysis was adopted for the Yangtze River Delta cities of China. First, six urban metrics were selected to describe the shape and layout of urban patches in each city, and the total biomass loss index was then introduced as a parameter. The values of urban metrics and total biomass loss index were calculated for the 50 Yangtze River Delta cities. Second, ordinary least squares regression and geographically weighted regression analyses were then used to establish a quantitative relationship between total biomass loss index and urban form indicators. The results revealed an extremely negative correlation between total biomass loss index and the three urban variables of Richard compactness, density gradient, and the Gini coefficient; moreover, the parameter estimates for the three variables in the geographically weighted regression model were local and varied over space. Third, the mechanisms by which the urban form influences biomass loss were discussed and different urban form planning strategies for particular urban areas were suggested. In conclusion, compact urban form in a clustered layout of urban areas with a dense central agglomeration was verified to be ecologically superior and conducive to green space protection. For the physical interpretation of the statistical relationship between urban morphology and vegetation loss, the interface effect of urban agglomeration on vegetation merits further study.

scholarly journals A SLR Pre-Processing Algorithm Based on Satellite Signature Effect

2021 ◽  
Vol 11 (19) ◽  
pp. 8880
Author(s):  
Bowen Guan ◽  
Cunbo Fan ◽  
Ning An ◽  
Ricardo Cesar Podesta ◽  
Dra Ana Pacheco ◽  
...  
Keyword(s):  
Mean Value ◽  
Observation Data ◽  
Short Term ◽  
Error Sources ◽  
Effect Model ◽  
The Mean ◽  
The Stability ◽  
First Time ◽  
Satellite Signature Effect

As one of the major error sources, satellite signature effect should be reduced or even erased from the distribution of the post-fit residuals to improve the ranging precision. A simulation of satellite signature effect removal process for normal point algorithm is conducted based on a revised model of satellite response, which fully considers the structural and distribution characteristics of retroreflectors. In order to eliminate both long-term and short-term satellite signature effect, a clipping method for SLR data processing is proposed by defining the clipping location as 5.6 mm away from the mean value of the long-term fit residuals to select effective returns for normal points. The results indicate that, compared to normal points algorithm, the RMS per NP of LAGEOS-1 observation data processed by the clipping method is reduced from 62.90 ± 9.9 mm to 56.07 ± 4.69 mm, and the stability of RMS is improved 53%. This study improves the satellite signature effect model and simulates the fluctuation of normal points caused by satellite signature effect for the first time. The new method based on the simulation of satellite signature effect has stronger robustness and applicability, which can further minimize the influence of satellite signature effect on the SLR production and significantly improve the data property.

scholarly journals Bird trends from long-term observation data at sites in the Hudson Bay Lowlands

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Rodney W. Brook ◽  
Lisa A. Pollock ◽  
Kenneth F. Abraham ◽  
Glen S. Brown
Keyword(s):  
Hudson Bay ◽  
Observation Data ◽  
Hudson Bay Lowlands ◽  
Long Term Observation

Effect of reintroduced manual mowing on biodiversity in abandoned fen meadows

Biologia ◽  
2015 ◽  
Vol 70 (1) ◽  
Author(s):  
Jakub Horak ◽  
Lenka Safarova
Keyword(s):  
Restoration Ecology ◽  
Conservation Value ◽  
High Conservation ◽  
New Type ◽  
Surrounding Landscape ◽  
Flower Visiting ◽  
Short Time ◽  
Positive Effect ◽  
Insect Group

AbstractWetlands have recently become of high environmental interest. The restoration effects on habitats like fens are one of the main topics of recent restoration ecology, especially due to their interconnection with other ecosystems. We studied the manual mowing effect on abandoned fen using the response of three study taxa: diurnal butterflies, flower-visiting beetles and vascular plants. Our results showed that butterflies seems to be quickly-responding indicator taxon for evaluation and that restored management had a positive effect on both species richness and composition of this insect group. The results indicated that the manual mowing effect could be rapid. In comparison with the surrounding landscape, we found that: (i) the manually mowed site was most similar to strictly protected area, (ii) some species of high conservation value could reach higher abundance in restored than protected site, and (iii) manual mowing could bring a new type of habitat (i.e., spatial heterogeneity) compared to the other management types (abandonment, conservation and agri-environmental mowing). The main implication seems to be optimistic for practice: The manual mowing of long-term abandoned fen is leading to the creation of habitat with high conservation value in a relatively short time.

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