scholarly journals Detecting regime shifts in communities using estimated rates of change

2020 ◽  
Vol 77 (4) ◽  
pp. 1546-1555 ◽  
Author(s):  
Eric J Pedersen ◽  
Mariano Koen-Alonso ◽  
Tyler D Tunney
Keyword(s):  
Time Series ◽  
Rapid Change ◽  
Single Species ◽  
Community Change ◽  
Regime Shifts ◽  
Rate Of Change ◽  
Spatiotemporal Pattern ◽  
Wide Range ◽  
Capita Rate ◽  
Per Capita

Abstract Regime shifts (periods of rapid change punctuating longer periods of lower variability) are observed in a wide range of ecosystems, and effective fisheries management requires the ability to detect these shifts. Detecting shifts is straightforward in single-species time series when transitions are detectable as periods of rapid change. However, shifts in complex and spatially structured communities may be harder to detect. We propose an approach to characterize community regime shifts, using nonparametric spatiotemporal regression models to estimate three indicators of community change (the among-species mean rate of change, mean per-capita rate of change, and standard deviation of per-capita rate of change). These indicators can detect shifts that result in either changes in abundance or composition. We applied our approach to a 37-year community biomass time series that spans the Newfoundland Shelf groundfish collapse. Our method detected a community shift earlier than alternative single-indicator breakpoint approaches and gave additional insight into the spatiotemporal pattern of the change, including detecting three separate periods of change and characterizing the first locations to show signs of recovery. The indicators applied in this study provide novel insights into Newfoundland groundfish dynamics and should be useful in the characterization of other abrupt ecological changes.

scholarly journals Determining carrying capacity from foraminiferal time-series

2012 ◽  
Vol 31 (2) ◽  
pp. 111-119 ◽  
Author(s):  
Brent Wilson ◽  
Benjamin P. Horton
Keyword(s):  
Time Series ◽  
Population Density ◽  
Carrying Capacity ◽  
Rate Of Change ◽  
Negative Slope ◽  
Population Densities ◽  
Intraspecific Interactions ◽  
Rate Of Increase ◽  
Capita Rate ◽  
Per Capita

Abstract. The carrying capacity K is the equilibrium population density of a species that an area can support while adequately meeting the needs of every individual. Although widely used in ecology, it has yet to be applied rigorously to living foraminifera. K is readily determined from time-series of population densities. Given that Nt+1 = Nt + RNt, in which Nt is the population densities at time t, Nt+1 is the density at a subsequent time t+1 and R is the per capita rate of change in population density, then linear regression gives Rt = Rm − sNt, in which Rt is the per capita rate of increase at time t, the constant Rm is the maximum possible individual rate of increase, and the negative slope s represents the strength of intraspecific interactions. Setting Rt = 0, so that Nt = K and Rm – sK = 0, gives K = Rm/s, which is applicable in aseasonal environments. There are two carrying capacities in seasonal environments, depending on whether the season is favourable (Kmax) or unfavourable (Kmin). Values of Kmax and Kmin are estimated for Nonion depressulus in the Exe estuary, UK (25 monthly samples), Quinqueloculina spp. in the Indian River Lagoon, USA (60 monthly samples) and Haynesina germanica in Cowpen Marsh, UK (25 fortnightly samples). The most precise estimate was for H. germanica, but it was unclear if this was due to the high rate of sampling or the large number of replicates used to erect this time-series.

scholarly journals Spatiotemporal analysis of some extreme rainfall indices over Iraq (1981–2017)

2021 ◽  
Vol 30 (2) ◽  
pp. 221-235
Author(s):  
Alaa Al-Lami ◽  
Hasanain Al-Shamarti ◽  
Yaseen Al-Timimi
Keyword(s):  
Time Series ◽  
Extreme Rainfall ◽  
Spatiotemporal Analysis ◽  
Rate Of Change ◽  
Mean Annual Precipitation ◽  
Spatiotemporal Pattern ◽  
Northwestern Part ◽  
Positive Trend ◽  
Human Environment ◽  
The Impact

Extreme rainfall is one of the environmental hazards with disastrous effects on the human environment. Water resources management is very vulnerable to any changes in rainfall intensities. A spatiotemporal analysis is essential for study the impact of climate change and variability on extreme rainfall. In this study, daily rainfall data for 36 meteorological stations in Iraq during 1981–2017 were used to investigate the spatiotemporal pattern of 10 extreme rainfall indices using RClimDex package. These indices were classified into two categories: rainfall total (PRCPTOT, SDII, R95p, R99p, RX1day, and RX5day) and rainfall days (CDD, CWD, R10, and R20). Depending on the mean annual precipitation data, the study area was divided into three climatic zones to examine the time series features of those 10 indices. Results showed a tendency to increase in precipitation toward the northwestern part of Iraq, and more than 70% of stations achieved a positive trend for most indices. The most frequent negative trend appeared in eight stations distributed in the western and southern parts of Iraq, namely (Heet, Haditha, Anah, Rutba, Qaim, Nukheb, Najaf, and Fao). A significant positive trend appeared obviously in PRCPTOT and R95p with a rate of 0.1–4.6 and 0.5–2.7 mm per year, respectively. Additionally, the least trend increasing appeared in all precipitation days indices specifically in R10 and R20. Time series analyses revealed a positive trend in all regions under study, except SDII in the southern region. The most significant rate of change was noticed in regions one and two (northern and middle parts of Iraq), particularly for PRCPTOT and R95p 3.26 and 2.45 mm per day, respectively. Only the northern and eastern regions of Iraq experienced a high probability of significant extreme rainfall.

Decreasing water pressure cues ‘bailout’ in seaweed-associated crustaceans

2020 ◽  
Vol 653 ◽  
pp. 121-129
Author(s):  
RB Taylor ◽  
S Patke
Keyword(s):  
Water Pressure ◽  
Rapid Change ◽  
Brown Seaweed ◽  
Model System ◽  
Rate Of Change ◽  
Suitable Habitat ◽  
Changing Light ◽  
Surface Increase ◽  
Reduced Water ◽  
Transparent Chamber

Small mobile crustaceans are abundant on seaweeds. Many of these crustaceans rapidly abandon their host if it is detached from the seafloor and floats towards the surface, but the trigger for this ‘bailout’ behaviour is unknown. We tested 2 potential cues, i.e. rapid change in light and rapid change in water pressure, using >1 mm epifauna on the brown seaweed Carpophyllum plumosum as a model system. Bailout occurred in response to reduced water pressure, but not to changing light, as (1) bailout occurred at similar rates in light and dark, (2) bailout occurred on the seafloor when water pressure was reduced within a transparent chamber by the equivalent of ~0.5 m depth or more, and (3) little bailout occurred when water pressure was held constant within the chamber while seaweeds were raised to the surface. Increase in pressure (simulating sinking) did not induce bailout. The rate of bailout increased with increasing magnitude of pressure reduction but was not influenced greatly by the rate of change of pressure within the range tested (up to an equivalent of 0.4 m depth s-1). The use of pressure rather than light as a cue for bailout is consistent with the need for seaweed-associated crustaceans to rapidly abandon a detached host and relocate to suitable habitat during both day and night.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals Examining GDP Growth and Its Volatility: An Episodic Approach

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 890
Author(s):  
Jakub Bartak ◽  
Łukasz Jabłoński ◽  
Agnieszka Jastrzębska
Keyword(s):  
Economic Growth ◽  
Genetic Algorithm ◽  
Time Series ◽  
Human Capital ◽  
Growth Rates ◽  
Structural Breaks ◽  
Negative Relationship ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Per Capita

In this paper, we study economic growth and its volatility from an episodic perspective. We first demonstrate the ability of the genetic algorithm to detect shifts in the volatility and levels of a given time series. Having shown that it works well, we then use it to detect structural breaks that segment the GDP per capita time series into episodes characterized by different means and volatility of growth rates. We further investigate whether a volatile economy is likely to grow more slowly and analyze the determinants of high/low growth with high/low volatility patterns. The main results indicate a negative relationship between volatility and growth. Moreover, the results suggest that international trade simultaneously promotes growth and increases volatility, human capital promotes growth and stability, and financial development reduces volatility and negatively correlates with growth.

scholarly journals Sequence data from isolated lichen-associated melanized fungi enhance delimitation of two new lineages within Chaetothyriomycetidae

2021 ◽  
Vol 20 (7) ◽  
pp. 911-927
Author(s):  
Lucia Muggia ◽  
Yu Quan ◽  
Cécile Gueidan ◽  
Abdullah M. S. Al-Hatmi ◽  
Martin Grube ◽  
...  
Keyword(s):  
Sequence Data ◽  
Single Species ◽  
Sister Group ◽  
Asexual Propagation ◽  
Dna Sequence Data ◽  
Wide Range ◽  
The Family ◽  
Rock Inhabiting Fungi ◽  
Stable Habitat

AbstractLichen thalli provide a long-lived and stable habitat for colonization by a wide range of microorganisms. Increased interest in these lichen-associated microbial communities has revealed an impressive diversity of fungi, including several novel lineages which still await formal taxonomic recognition. Among these, members of the Eurotiomycetes and Dothideomycetes usually occur asymptomatically in the lichen thalli, even if they share ancestry with fungi that may be parasitic on their host. Mycelia of the isolates are characterized by melanized cell walls and the fungi display exclusively asexual propagation. Their taxonomic placement requires, therefore, the use of DNA sequence data. Here, we consider recently published sequence data from lichen-associated fungi and characterize and formally describe two new, individually monophyletic lineages at family, genus, and species levels. The Pleostigmataceae fam. nov. and Melanina gen. nov. both comprise rock-inhabiting fungi that associate with epilithic, crust-forming lichens in subalpine habitats. The phylogenetic placement and the monophyly of Pleostigmataceae lack statistical support, but the family was resolved as sister to the order Verrucariales. This family comprises the species Pleostigma alpinum sp. nov., P. frigidum sp. nov., P. jungermannicola, and P. lichenophilum sp. nov. The placement of the genus Melanina is supported as a lineage within the Chaetothyriales. To date, this genus comprises the single species M. gunde-cimermaniae sp. nov. and forms a sister group to a large lineage including Herpotrichiellaceae, Chaetothyriaceae, Cyphellophoraceae, and Trichomeriaceae. The new phylogenetic analysis of the subclass Chaetothyiomycetidae provides new insight into genus and family level delimitation and classification of this ecologically diverse group of fungi.

Haemorheological Effects on Thrombocyte Adhesion and Aggregation Found Under Controlled Flow Conditions

1979 ◽  
Author(s):  
P.D. Richardson
Keyword(s):  
Rate Of Change ◽  
Continuous Observation ◽  
Flow Conditions ◽  
Wide Range ◽  
Stream Migration ◽  
Local Shear ◽  
Videotape Recording ◽  
Controlled Flow ◽  
A Site

Thrombocyte adhesion and aggregation in a vessel or on a chamber wall can be measured most readily if the flow is controlled and steady, and continuous observation is used. Videotape recording is very helpful for subsequent quantification of the dynamics. The adhesion of each thrombocyte can occur for a finite time interval:this interval has been observed to have a wide range. Platelets which escape often leave open a site which attracts other platelets preferentially. The rate of change of adhesion density (platelets/mm2) is affected by the local shear rate and the shear history upstream. Aggregation is affected similarly, and also proceeds with some platelet turnover. The role of erythrocytes in facilitating cross-stream migration of thrombocytes (which can enhance the growth rate of large thrombi) appears due in part to convective flow fields induced by the motion of erythrocytes in a shear flow, which can be demonstrated theoretically and experimentally. Observations of the phenomenlogy of adhesion and aggregation under controlled flow conditions and comparison with fLu id-dynamically based theory allows representation in terras of a small number of parameters with prospects of prediction of behaviour over a wide range of haemodynamic conditions; biochemical changes lead to changes in values of the parameters, so that activating agents and inhibiting agents modify values in different directions.

scholarly journals GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

2019 ◽  
Vol 12 (11) ◽  
pp. 4661-4679 ◽  
Author(s):  
Bin Cao ◽  
Xiaojing Quan ◽  
Nicholas Brown ◽  
Emilie Stewart-Jones ◽  
Stephan Gruber
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Ground Surface ◽  
Reanalysis Data ◽  
Meteorological Variables ◽  
Ensemble Simulations ◽  
Driving Time ◽  
Wide Range ◽  
Global Coverage ◽  
Uncertain Input

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

Comparative Study on BRIC Carbon Dioxide Emissions - Econometric Empirical Test Based on Cross-Century Time Series Data

2012 ◽  
Vol 616-618 ◽  
pp. 1512-1515
Author(s):  
Wei Hua Du
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Carbon Dioxide Emissions ◽  
Time Series Data ◽  
Comparative Statics ◽  
Total Carbon ◽  
Series Data ◽  
Per Capita Gdp ◽  
Bric Countries ◽  
Per Capita

Take for example the BRIC economies: Brazil, Russia, India and China. We investigated the time series data on the relationship between carbon dioxide emission and economic growth in these fast-growing developing countries by both comparative statics and comparative dynamics. The results show that there is the monotonic relationship between total carbon dioxide emissions, carbon dioxide emissions per capita and per capita GDP in any one of the BRIC countries. And there is decreasing relationship between the carbon dioxide emissions per unit GDP and per capita GDP.

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