scholarly journals Biodiversity trends are stronger in marine than terrestrial assemblages

2018 ◽  
Author(s):  
Shane Blowes ◽  
Sarah Supp ◽  
Laura Antão ◽  
Amanda Bates ◽  
Helge Bruelheide ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Change ◽  
Species Turnover ◽  
Temporal Trends ◽  
Compositional Change ◽  
Taxa Richness ◽  
Rates Of Change ◽  
Extinction Rates ◽  
Consistent Change ◽  
Biodiversity Change

SummaryHuman activities have fundamentally altered biodiversity. Extinction rates are elevated and model projections suggest drastic biodiversity declines. Yet, observed temporal trends in recent decades are highly variable, despite consistent change in species composition. Here, we uncover clear spatial patterns within this variation. We estimated trends in the richness and composition of assemblages in over 50,000 time-series, to provide the most comprehensive assessment of temporal change in biodiversity across the planet to date. The strongest, most consistent pattern shows compositional change dominated by species turnover, with marine taxa experiencing up to fourfold the variation in rates of change of terrestrial taxa. Richness change ranged from no change to richness gains or losses of ~10% per year, with tropical marine biomes experiencing the most extreme changes. Earth is undergoing a process of spatial reorganisation of species and, while few areas are unaffected, biodiversity change is consistently strongest in the oceans.

scholarly journals The many forms of beta diversity: a comment on McGill et al. and some notational suggestions

2017 ◽  
Author(s):  
Tobias Jeppsson
Keyword(s):  
Spatial Patterns ◽  
Beta Diversity ◽  
Temporal Trend ◽  
Species Turnover ◽  
Temporal Trends ◽  
Β Diversity ◽  
Different Types ◽  
Biodiversity Change ◽  
The Many

Fundamentally, beta diversity is a measure of species turnover across time or space. In practice, it is sometimes unclear exactly what aspect of beta diversity that is implied in studies. For instance, a trend in ’spatial beta diversity’ can be used to refer to both differences in spatial beta diversity between sites, as well as a temporal trend in spatial beta diversity (at the same site). In a recent review, McGill et al. [1] provide a useful and much needed overview of different aspects of biodiversity change, and show areas where we lack knowledge. Even so, McGill et al. ignore some aspects of beta diversity and sometimes pool different types of beta diversity under the same heading. However, their review mainly focused on temporal trends in diversity, while I here want to highlight spatial patterns in temporal β -diversity (species turnover) as an important but somewhat overlooked component of biodiversity change. Furthermore, I propose a slightly modified classification and nomenclature of metrics of biodiversity change, with the aim of complementing their review. The notation used here can hopefully be useful to other authors as well.

scholarly journals Quantifying temporal change in biodiversity: challenges and opportunities

2013 ◽  
Vol 280 (1750) ◽  
pp. 20121931 ◽  
Author(s):  
Maria Dornelas ◽  
Anne E. Magurran ◽  
Stephen T. Buckland ◽  
Anne Chao ◽  
Robin L. Chazdon ◽  
...  
Keyword(s):  
Time Series ◽  
Temporal Change ◽  
Biodiversity Loss ◽  
Phase Shifts ◽  
Underlying Structure ◽  
Temporal Data ◽  
Statistical Procedures ◽  
Analytic Methods ◽  
Challenges And Opportunities ◽  
Biodiversity Change

Growing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series—lack of physical boundaries, uni-dimensionality, autocorrelation and directionality—that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.

scholarly journals The geography of biodiversity change in marine and terrestrial assemblages

Science ◽  
2019 ◽  
Vol 366 (6463) ◽  
pp. 339-345 ◽  
Author(s):  
Shane A. Blowes ◽  
Sarah R. Supp ◽  
Laura H. Antão ◽  
Amanda Bates ◽  
Helge Bruelheide ◽  
...  
Keyword(s):  
Time Series ◽  
Species Richness ◽  
Spatial Variation ◽  
Geographic Variation ◽  
Human Activities ◽  
Global Scale ◽  
Composition Change ◽  
Compositional Change ◽  
Biodiversity Change ◽  
Terrestrial Biomes

Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans.

scholarly journals The many forms of beta diversity: a comment on McGill et al. and some notational suggestions

2017 ◽  
Author(s):  
Tobias Jeppsson
Keyword(s):  
Spatial Patterns ◽  
Beta Diversity ◽  
Temporal Trend ◽  
Species Turnover ◽  
Temporal Trends ◽  
Β Diversity ◽  
Different Types ◽  
Biodiversity Change ◽  
The Many

Fundamentally, beta diversity is a measure of species turnover across time or space. In practice, it is sometimes unclear exactly what aspect of beta diversity that is implied in studies. For instance, a trend in ’spatial beta diversity’ can be used to refer to both differences in spatial beta diversity between sites, as well as a temporal trend in spatial beta diversity (at the same site). In a recent review, McGill et al. [1] provide a useful and much needed overview of different aspects of biodiversity change, and show areas where we lack knowledge. Even so, McGill et al. ignore some aspects of beta diversity and sometimes pool different types of beta diversity under the same heading. However, their review mainly focused on temporal trends in diversity, while I here want to highlight spatial patterns in temporal β -diversity (species turnover) as an important but somewhat overlooked component of biodiversity change. Furthermore, I propose a slightly modified classification and nomenclature of metrics of biodiversity change, with the aim of complementing their review. The notation used here can hopefully be useful to other authors as well.

Are local losses of biodiversity causing degraded ecosystem function?

2017 ◽  
Author(s):  
Mark Vellend
Keyword(s):  
Ecosystem Function ◽  
Species Interactions ◽  
Regional Scale ◽  
Temporal Trends ◽  
Biodiversity Loss ◽  
Large Degree ◽  
Global Scale ◽  
Degraded Ecosystem ◽  
Biodiversity Change ◽  
Local Extirpation

This chapter highlights the scale dependence of biodiversity change over time and its consequences for arguments about the instrumental value of biodiversity. While biodiversity is in decline on a global scale, the temporal trends on regional and local scales include cases of biodiversity increase, no change, and decline. Environmental change, anthropogenic or otherwise, causes both local extirpation and colonization of species, and thus turnover in species composition, but not necessarily declines in biodiversity. In some situations, such as plants at the regional scale, human-mediated colonizations have greatly outnumbered extinctions, thus causing a marked increase in species richness. Since the potential influence of biodiversity on ecosystem function and services is mediated to a large degree by local or neighborhood species interactions, these results challenge the generality of the argument that biodiversity loss is putting at risk the ecosystem service benefits people receive from nature.

scholarly journals 1120. Impact of Training Residents to Improve HIV Screening in a Teaching Hospital in Mexico City

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S590-S590
Author(s):  
Lorena Guerrero-Torres ◽  
Isaac Núñez-Saavedra ◽  
Yanink Caro-Vega ◽  
Brenda Crabtree-Ramírez
Keyword(s):  
Emergency Department ◽  
Time Series ◽  
Hiv Testing ◽  
Teaching Hospital ◽  
Educational Intervention ◽  
Temporal Trends ◽  
Hiv Screening ◽  
Hiv Diagnosis ◽  
Post Intervention ◽  
Hiv Test

Abstract Background Among 230,000 people living with HIV in Mexico, 24% are unaware of their diagnosis, and half of newly diagnosed individuals are diagnosed with advanced disease. Early diagnosis is the goal to mitigate HIV epidemic. Missed opportunities may reflect a lack of clinicians’ consideration of HIV screening as part of routine medical care. We assessed whether an educational intervention on residents was effective to 1) improve the knowledge on HIV screening; 2) increase the rate of HIV tests requested in the hospitalization floor (HF) and the emergency department (ED); and 3) increase HIV diagnosis in HF and ED. Methods Internal Medicine and Surgery residents at a teaching hospital were invited to participate. The intervention occurred in August 2018 and consisted in 2 sessions on HIV screening with an expert. A questionnaire was applied before (BQ) and after (AQ) the intervention, which included HIV screening indications and clinical cases. The Institutional Review Board approved this study. Written informed consent was obtained from all participants. BQ and AQ scores were compared with a paired t-test. To evaluate the effect on HIV test rate in the HF and ED, an interrupted time series analysis was performed. Daily rates of tests were obtained from September 2016 to August 2019 and plotted along time. Restricted cubic splines (RCS) were used to model temporal trends. HIV diagnosis in HF and ED pre- and post-intervention were compared with a Fisher’s exact test. A p< 0.05 was considered significant. Results Among 104 residents, 57 participated and completed both questionnaires. BQ score was 79/100 (SD±12) and AQ was 85/100 (SD±8), p< .004. Time series of HIV testing had apparent temporal trends (Fig 1). HIV test rate in the HF increased (7.3 vs 11.1 per 100 episodes) and decreased in the ED (2.6 vs 2.3 per 100 episodes). HIV diagnosis increased in the HF, from 0/1079 (0%) pre-intervention to 5/894 (0.6%) post-intervention (p< .018) (Table 1). Fig 1. HIV test rates. Gray area represents post-intervention period. Table 1. Description of episodes, HIV tests and rates pre- and post-intervention in the Emergency Department and Hospitalization Floor. Conclusion A feasible educational intervention improved residents’ knowledge on HIV screening, achieved maintenance of a constant rate of HIV testing in the HF and increased the number of HIV diagnosis in the HF. However, these results were not observed in the ED, where administrative barriers and work overload could hinder HIV screening. Disclosures All Authors: No reported disclosures

scholarly journals Trend Analysis of Annual and Seasonal River Runoff by Using Innovative Trend Analysis with Significant Test

Water ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Yongxiao Ge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
River Runoff ◽  
Temporal Trends ◽  
Temporal Distribution ◽  
Trend Test ◽  
Data Series ◽  
Mk Test ◽  
Comparison Results ◽  
Innovative Trend Analysis

This study investigated the temporal patterns of annual and seasonal river runoff data at 13 hydrological stations in the Lake Issyk-Kul basin, Central Asia. The temporal trends were analyzed using the innovative trend analysis (ITA) method with significance testing. The ITA method results were compared with the Mann-Kendall (MK) trend test at a 95% confidence level. The comparison results revealed that the ITA method could effectively identify the trends detected by the MK trend test. Specifically, the MK test found that the time series percentage decreased from 46.15% in the north to 25.64% in the south, while the ITA method revealed a similar rate of decrease, from 39.2% to 29.4%. According to the temporal distribution of the MK test, significantly increasing (decreasing) trends were observed in 5 (0), 6 (2), 4 (3), 8 (0), and 8 (1) time series in annual, spring, summer, autumn, and winter river runoff data. At the same time, the ITA method detected significant trends in 7 (1), 9 (3), 6(3), 9 (3), and 8 (2) time series in the study area. As for the ITA method, the “peak” values of 24 time series (26.97%) exhibited increasing patterns, 25 time series (28.09%) displayed increasing patterns for “low” values, and 40 time series (44.94%) showed increasing patterns for “medium” values. According to the “low”, “medium”, and “peak” values, five time series (33.33%), seven time series (46.67%), and three time series (20%) manifested decreasing trends, respectively. These results detailed the patterns of annual and seasonal river runoff data series by evaluating “low”, “medium”, and “peak” values.

scholarly journals Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 8295
Author(s):  
Patricia Melin ◽  
Oscar Castillo
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Temporal Trends ◽  
Main Idea ◽  
Temporal Analysis ◽  
Virus Propagation ◽  
Self Organizing Maps ◽  
Fractal Approach ◽  
The Times ◽  
Self Organizing

In this article, the evolution in both space and time of the COVID-19 pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries considered in this study. Self-organizing neural networks possess the capability to cluster countries in the space domain based on their similar characteristics, with respect to their COVID-19 cases. This form enables the finding of countries that have a similar behavior, and thus can benefit from utilizing the same methods in fighting the virus propagation. In order to validate the approach, publicly available datasets of COVID-19 cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of the time series of the countries considered in this study. Then, a hybrid combination, using fuzzy rules, of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient coronavirus disease 2019 (COVID-19) forecasting of the countries. Relevant conclusions have emerged from this study that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. Many of the existing works concerned with COVID-19 look at the problem mostly from a temporal viewpoint, which is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant for improving the forecasting ability. The main idea of this article is combining neural networks with a self-organizing nature for clustering countries with a high similarity and the fuzzy fractal approach for being able to forecast the times series. Simulation results of COVID-19 data from countries around the world show the ability of the proposed approach to first spatially cluster the countries and then to accurately predict in time the COVID-19 data for different countries with a fuzzy fractal approach.

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