Observation of Low x Phenomena in Hadronic Final States

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阐释现象考博英语作文模版

阐释现象考博英语作文模版英文回答：Empirical phenomena are manifestations of underlying mechanisms and principles that shape our physical andsocial world. Examining such phenomena can provide valuable insights into the workings of nature, the dynamics of human behavior, and the intricate interrelationships between different aspects of our existence.A systematic approach to explicating empirical phenomena involves several key steps:1. Observation and Measurement:To understand a phenomenon, it is crucial to observe and measure it accurately. This involves using appropriate instruments, techniques, and methodologies to collect data that can be used to quantify and characterize the phenomenon. By meticulously observing and measuring,researchers can obtain a reliable representation of the phenomenon under investigation.2. Data Analysis and Interpretation:Once data has been collected, it is analyzed and interpreted to identify patterns, trends, and correlations. Statistical methods, computational models, and qualitative analysis techniques are employed to extract meaningful insights from the data. By analyzing the data, researchers can uncover underlying causes, relationships, and mechanisms that explain the phenomenon.3. Hypothesis Formulation and Testing:Based on the initial observations and analysis, researchers formulate hypotheses that propose potential explanations for the observed phenomenon. These hypotheses are then tested through carefully designed experiments or observational studies. By testing hypotheses, researchers can confirm or reject their proposed explanations andrefine their understanding of the phenomenon.4. Theoretical Framework and Model Building:The results of empirical investigations are integrated into a theoretical framework that provides a coherent explanation for the phenomenon. This framework may incorporate existing theories, modify them, or propose new constructs to account for the observed data. Researchers also develop models to represent the underlying mechanisms and relationships in a simplified and testable manner.5. Replication and Validation:To ensure the validity and generalizability of the findings, researchers replicate studies and conduct cross-validation analyses. By replicating the study withdifferent samples, methodologies, and contexts, researchers can increase the confidence in their conclusions and rule out alternative explanations.In conclusion, explicating empirical phenomena is a complex and iterative process that requires carefulobservation, data analysis, hypothesis testing, theoretical framework development, and validation. By following these steps, researchers can uncover the mechanisms andprinciples that underpin the phenomena we observe in the world, deepening our understanding of nature and ourselves.中文回答：阐释现象。

关于现象的英文模板作文

关于现象的英文模板作文英文回答：Phenomena are events or experiences that are observed and can be scientifically studied. They can be natural,like the weather or the movement of the stars, or they can be artificial, like the creation of a new technology or the spread of a disease.Phenomena can be classified into different types based on their characteristics. Some of the most common types of phenomena include:Physical phenomena: These are phenomena that involve the physical properties of matter and energy. Examples of physical phenomena include the movement of objects, the transfer of heat, and the emission of light.Chemical phenomena: These are phenomena that involve the chemical reactions between different substances.Examples of chemical phenomena include the formation of new compounds, the decomposition of substances, and the release of gases.Biological phenomena: These are phenomena that involve the living world. Examples of biological phenomena include the growth and development of organisms, the interaction between species, and the evolution of life.Psychological phenomena: These are phenomena that involve the mind and behavior of humans and animals. Examples of psychological phenomena include perception, learning, memory, and emotion.Social phenomena: These are phenomena that involve the interactions between individuals and groups in society. Examples of social phenomena include the formation ofsocial groups, the spread of culture, and the development of social norms.Phenomena can be studied by scientists using a variety of methods. Some of the most common methods of scientificstudy include:Observation: This involves observing a phenomenon and recording data about it.Experimentation: This involves manipulating a phenomenon and observing the results.Modeling: This involves creating a mathematical or computer model of a phenomenon to simulate its behavior.Analysis: This involves breaking down a phenomenon into its component parts and studying them individually.The study of phenomena is essential for understanding the world around us. By studying phenomena, scientists can learn about the laws of nature, the history of the Earth, and the behavior of humans and animals.中文回答：现象是指可以观察和科学研究的事件或经历。

水体富营养化导致蓝藻水华暴发

N:P ratios,light limitation,and cyanobacterial dominance in a subtropical lake impacted by non-point source nutrient pollutionKarl E.Havens a,*,R.Thomas James a ,Therese L.East a ,Val H.Smith baSouth Florida Water Management District,West Palm Beach,Florida 33406,USAbU niversity ofKansas,Lawrence,Kansas 66045,U SAReceived 2May 2002;accepted 19July 2002‘‘Capsule’’:Low ratios ofN:P and low underwater irradiance control dominance ofcyanobacteria in a subtropical lake.AbstractA long-term (28-year)data set was used to investigate historical changes in concentrations of phosphorus (P),nitrogen (N),N:P ratios,and Secchi disk transparency in a shallow subtropical lake (Lake Okeechobee,Florida,USA).The aim was to evaluate changes in the risk of N 2-ﬁxing cyanobacterial blooms,which have infrequently occurred in the lake’s pelagic zone.Predictions regarding bloom risk were based on previously published N:P ratio models.Temporal trends in the biomass of cyanobacteria were evaluated using phytoplankton data collected in 1974,1989–1992,and 1997–2000.Concentrations of pelagic total P increased from near 50m g l À1in the mid-1970s to over 100m g l À1in the late 1990s.Coincidentally,the total N:P (mass)ratio decreased from 30:1to below 15:1,and soluble N:P ratio decreased from 15:1to near 6:1,in the lake water.Published empirical models predict that current conditions favor cyanobacteria.The observations conﬁrm this prediction:cyanobacteria presently account for 50–80%of total phytoplankton biovolume.The historical decrease in TN:TP ratio in the lake can be attributed to a decreased TN:TP ratio in the inﬂow water and to a decline in the lake’s assimilation of P,relative to N.Coincident with these declines in total and soluble N:P ratios,Secchi disk transparency declined from 0.6m to near 0.3m,possibly due to increased mineral turbidity in the lake water.Empirical models predict that under the turbid,low irradiance conditions that prevail in this lake,non-heterocystous cyanobacteria should dominate the phytoplankton.Our observations conﬁrmed this prediction:non-N 2-ﬁxing taxa (primarily Oscillatoria and Lyngbya spp.)typically dominated the cyanobacteria community during the last decade.The only exception was a year with very low water levels,when heterocystous N 2-ﬁxing Anabaena became dominant.In the near-shore regions of this shallow lake,low N:P ratios potentially favor blooms of N 2-ﬁxing cyanobacteria,but their occurrence in the pelagic zone is restricted by low irradiance and lack of stable stratiﬁcation.#2002Elsevier Science Ltd.All rights reserved.Keywords:Cyanobacteria;Nitrogen:phosphorus ratios;Transparency;Shallow lakes1.IntroductionCyanobacteria dominance,and sometimes bloom formation,are among the most visible symptoms of accelerated eutrophication of lakes and reservoirs (Moss et al.,1997).At high densities,cyanobacteria produce taste and odor problems in drinking water,impair aes-thetics,and kill aquatic biota due to conditions asso-ciated with their senescence (e.g.low dissolved oxygen and high ammonia concentrations)and/or the productionof toxins (Paerl et al.,2001).Understanding the cause of cyanobacteria dominance has been a focal point of classical and contemporary limnological research.Early experimental whole-lake research (Schindler,1977)established that high concentrations of P,and a low N:P supply ratio,are favorable for the production of cya-nobacteria blooms.Smith (1983)evaluated data from a wide range of temperate lakes and concluded that a total N:P ratio (TN:TP)of 29:1diﬀerentiates between lakes with cyanobacteria dominance (TN:TP <29:1by mass)and lakes without such dominance (TN:TP >29:1).Smith et al.(1995)concluded that a mass ratio of 22:1provided a more distinct boundary0269-7491/03/$-see front matter #2002Elsevier Science Ltd.All rights reserved.P I I :S 0269-7491(02)00304-4Environmental Pollution 122(2003)379–390/locate/envpol*Corresponding author.Tel.:+1-561-682-6534;fax:+1-561-682-6442.E-mail address:khavens@ (K.E.Havens).between lakes dominated by N-ﬁxing cyanobacteria and lakes with low occurrence of these algae.The mechanism proposed(Smith,1983)to link cya-nobacteria dominance to a low TN:TP ratio is that all species of cyanobacteria are better able to compete for nitrogen than other phytoplankton when N is scarce. Therefore,when excessive P loading creates a surplus supply of phosphorus,N becomes relatively scarce and cyanobacteria are predicted to become dominant.Sub-sequent multi-lake surveys and controlled experiments (Smith and Bennett,1999)have generally supported this hypothesis(for a contrasting view,however,see Down-ing et al.,2001).Cyanobacterial blooms in moderately deep,stratiﬁed eutrophic lakes typically are comprised of N2-ﬁxing taxa,including Anabaena and Aphanizomenon(Paerl et al.,2001).These bloom-forming members of the Nos-tocaceae are strong resource competitors under condi-tions of nitrogen limitation because they canﬁx new nitrogen from N2,a gaseous source of inorganic nitro-gen that is not available to other phytoplankton (Horne,1979;Howarth et al.,1988;Tilman,1982).In contrast,shallow eutrophic lakes typically are domi-nated by cyanobacterial taxa that do notﬁx N2,in par-ticular the family Oscillatoriaceae,including Oscillatoria,Planktothrix,and Limnothrix(Berger, 1989;van Duin et al.,1995).The dominance of non-N2-ﬁxing cyanobacteria is attributed to their ability to maintain net growth at low underwater irradiance(van Duin et al.,1995).Oscillatoriaceae can attain high bio-mass in shallow eutrophic lakes,but do not form sur-face blooms.They continue to grow even when biomass and light attenuation become extremely high,possibly setting up a stable feedback loop that maintains their dominance over other phytoplankton species(Scheﬀer et al.,1997).A long-term(28-year)data set from a large sub-tropical lake(Lake Okeechobee,Florida,USA)pro-vides an opportunity to further evaluate the factors that control cyanobacterial biomass and taxonomic compo-sition in phytoplankton communities.This lake has displayed a wide range of TN:TP ratios,underwater irradiances,and phytoplankton composition,and has infrequent blooms of N2-ﬁxers such as Anabaena circi-nalis(Jones,1987).Most often it is dominated by Oscillatoria and Lyngbya(Havens et al.,1998).The lake also experiences frequent wind resuspension of its mud bottom sediments(Jin et al.,2000),and has a corre-spondingly high contribution of abiotic seston to underwater light attenuation(Havens,1995a).During winter the phytoplankton can include a high relative biovolume of small centric diatoms and pico-plankton (Phlips et al.,1997).Our objective is to use a long-term water chemistry data set(1973–2000),and historic phy-toplankton data sets(1974,1989–1992,1997–2000)to address the following questions:1.Have pelagic nutrient concentrations and N:Pratios changed in a direction that favors bloom-forming,N2-ﬁxing cyanobacteria?2.Have there been historical changes in the abso-lute and the relative biomass of cyanobacteria,and are those changes consistent with predictionsbased on nutrient-ratio theory?3.Is there evidence that low underwater irradiancesuppresses dominance by N2-ﬁxing cyano-bacteria,relative to what would be predictedfrom N:P ratios?4.What are the lake management implications ofthese results,from the perspective of LakeOkeechobee and other shallow eutrophic lakes?2.Study siteLake Okeechobee(Fig.1)is a natural lake located at 27 000N,80 500W in south Florida,USA.A dike that was constructed in the early part of the20th century for regionalﬂood control encircles the lake,and its hydrol-ogy is constrained by water control structures on all outﬂows and all but one inﬂow.Depth in the pelagic zone averages3m,with a maximal depth of4.5m.In addition to providingﬂood protection and water sup-ply,the lake’s littoral zone is an important wildlife habitat,and the ecosystem supports a valuable recrea-tionalﬁshery(Furse and Fox,1993).3.Data sourcesWater chemistry data were obtained from the long-term monitoring program of the South Florida Water Management District(SFWMD),and included monthly (October–April)or twice monthly(May–September) data from eight pelagic stations(Fig.1).The period of record was January1973to December2000.We exam-ined data for near-surface samples of TP,TN,soluble reactive P(SRP),dissolved inorganic N(DIN= NO x-N+NH4-N),chlorophyll a,and Secchi transpar-ency.The methods of sample collection,processing, analysis,and quality control follow established standard protocols of the Florida Department of Environmental Protection that are described in detail in James et al. (1995a).Unless otherwise indicated,data reported in this paper for any given year are arithmetic means from the eight pelagic stations.Full yearly data,rather than data from some speci-ﬁed‘‘growing season’’were used here for several rea-sons.First,conditions in this Florida lake are favorable for phytoplankton growth year-round in some lake regions.Water temperatures in the pelagic region vary only from approximately18to30 C between winter and mid-summer,respectively(Havens380K.E.Havens et al./Environmental Pollution122(2003)379–390et al.,1994).In the central pelagic region,a higher degree of sediment resuspension during the windy win-ter season does restrict phytoplankton growth (Phlips et al.,1993),but at that same time of year,phyto-plankton maxima have been observed in western pela-gic regions (Phlips et al.,1993).Second,use of yearly-averaged data allows for consistency when comparing in-lake TN:TP ratios with ratios in total yearly loads from the watershed.Third,when we compared historic trends in TP,TN,TN:TP and other attributes pre-sented in this paper,on both a yearly average vs.sum-mer average (May-September)basis,no substantive diﬀerences were found.Nutrient loading data were examined with a focus on the loading ratio of TN:TP and the relative residence times of N vs.P (t N or t P =lake mass+annual change in lake mass/output mass+mass loss to sediments).The net sedimentation coeﬃcient for P (calculated here as (input Àoutput)/change in lake mass)also was calcu-lated from the lake nutrient budget.These attributes were examined in order to explain observed historic changes in lake water TN:TP ratios.Water andnutrientFig.1.Map of Lake Okeechobee,showing locations of long-term (1973–2000)water quality monitoring stations (open circles),and the stations where data were collected for evaluation of phytoplankton biovolume and taxonomic composition by Marshall (1977,black circles),Cichra et al.(1995,grey circles),and the ongoing SFWMD sampling program (grey squares).The small inset map shows the location of this lake in Florida,USA.K.E.Havens et al./Environmental Pollution 122(2003)379–390381budgets for Lake Okeechobee are determined based on data collected at32inﬂow/outﬂow monitoring sites plus the eight in-lake pelagic monitoring stations.Flows at tributary structures are continuously monitored and nutrient sampling is done with a combination of monthly or twice monthly grab samples and time-com-posite autosamplers.Water depths in the lake were determined from a network of12stage recorders main-tained by the SFWMD and United States Army Corps of Engineers.Details of this sampling program and nutrient budget calculations are provided in James et al. (1995b).Phytoplankton data were compiled from a number of successive programs carried out on the lake since the early1970s.Sampling carried out by Marshall(1977) during1974included the eight long-term water quality monitoring stations.Cichra et al.(1995)sampled21 stations from1988to1990,and the SFWMD collected phytoplankton samples from four pelagic stations from 1997to2000.Marshall(1977)and Cichra et al.(1995) sampled monthly.The SFWMD sampling was every other month from1994to1999and monthly thereafter. To maintain spatial continuity in the data set,we inclu-ded only data from the four stations located closest to the current SFWMD phytoplankton sampling stations in our analyses.In all sampling programs,the phyto-plankton was preserved in Lugols solution and counted with an inverted microscope at1000Âmagniﬁcation or higher following the methods of Lund et al.(1958). Species’cell volumes were determined by measuring cells and approximating their shapes to regular geo-metric solids,and data are expressed as population bio-volumes(m m3mlÀ1).Here we focus on both the absolute and the relative biovolumes of all cyano-bacteria;of N2-ﬁxing cyanobacteria;and of selected cyanobacterial taxa including Anabaena,Aphanizome-non,Microcystis,Oscillatoria,and Lyngbya.All of these taxa have been dominant at one time or another in the recent history of the lake(Havens et al.,1998)and they all are implicated with water quality problems in other eutrophic lakes and reservoirs(Paerl et al.,2001).For comparative purposes,we also evaluated data from Lake Okeechobee in the context of other published studies,drawing upon datasets published in Smith (1985,1986).4.Results and discussionke nutrient statusTotal P concentrations in Lake Okeechobee display year-to-year variation(Fig.2A)that is positively corre-lated with water levels in the lake(Canﬁeld and Hoyer, 1988);this variation has been explained based on a number of physical and biological mechanisms(Havens,1997).Over the28-year period of record,there has been a general increase in TP,with concentrations in the early1970s averaging near50m g lÀ1,compared to>100 m g lÀ1since the late1990s.Total N concentrations (Fig.2B)also increased from the early1970s to1981, but then declined to near the original values in the1980s and1990s.As a result of these historic changes,the lake water TN:TP ratio decreased from approximately30:1 (with considerable variability)prior to1982to below 15:1in the1980s and1990s.According to Smith et al. (1995),lake water TN:TP ratios below22:1favor dom-inance by N2-ﬁxing cyanobacteria.Soluble reactive P concentrations(Fig.3A)display year-to-year variation that tracks changes in TP.There generally are high concentrations of SRP in the pelagic water of Lake Okeechobee,reﬂecting a surplus of P and explaining why the phytoplankton almost never are found to be limited by P in nutrient-addition bioassays (Aldridge et al.,1995;Phlips et al.,1997).Although DIN also displays high seasonal and year-to-year var-iation(Fig.3B),there is no signiﬁcant long-termtrend Fig.2.Yearly average concentrations of total phosphorus,TP(A), total nitrogen,TN(B),and the TN:TP ratio(C)in Lake Okeechobee from1973to2000.The data are means calculated from monthly or semi-monthly sampling at the eight pelagic stations shown in Fig.1. The critical ratio of22:1by mass(Smith et al.,1995),below which cyanobacteria dominance is predicted to occur,is shown in panel C.382K.E.Havens et al./Environmental Pollution122(2003)379–390in this attribute.During mid-summer,DIN concentra-tions typically decline to levels that are limiting for phytoplankton growth (Phlips et al.,1997).The ratio of DIN:SRP declined from near 20:1by mass (with con-siderable variation)in the early 1970s to ratios below 10:1after this time (Fig.3C).DIN:SRP ratios <10:1by mass are considered to indicate strongly nitrogen-limit-ing conditions that favor the growth and proliferation of N 2-ﬁxing cyanobacteria (Horne and Commins,1987;Smith et al.,1995).4.2.Nutrient loading ratiosThe historical trend in TN:TP loading ratio (by mass)is similar to that displayed by lake water TN:TP ratios (Fig.4A).Loading ratios averaged near 18:1in the 1970s,and then declined after 1982to near 12:1.Both lake and loading ratios declined from the ﬁrst to the second decade of sampling (Fig.4B).However,from the second to third decade,TN:TP ratios in the lake waterdeclined further,without a corresponding change in loading ratios.There also has been a parallel decrease in the N:P residence time ratio (Fig.5A).Vollenweider (1974)sug-gested that a shift in the N:P residence time ratio to values below 1may mark a change from phosphorus to nitrogen limitation of algal productivity,and indeed this shift in nutrient limitation status has been documented for Lake Okeechobee (Havens,1995b).Janus et al.(1990)concluded,‘‘if the [N:P residence time ratio]trend continues to a value below about 1,the implica-tion is that blooms of blue-green N 2-ﬁxers will become a more prominent feature of the lake,which may result in chronic water quality problems.’’In regard to the mechanism underlying the lake’s decreasing N:P resi-dence time ratio,we suspect that after decades of excessive P loads,the system has experienced a decrease in its ability to process incoming P.A downward trend in the net P sedimentation coeﬃcient (Fig.5B)conﬁrms that the lake’s capacity to assimilate P is decreasing,favoring a greater development of P surplus and N lim-itation (Havens and Schelske,2001).The recent ﬁnding (Fisher et al.,2001)of increased sedimentporewaterFig.4.Yearly average loading ratio of TN:TP (by mass)for inﬂows to Lake Okeechobee from 1973to 2000(A),and relationship between lake water TN:TP and inﬂow loading TN:TP (B).Three decades of data are diﬀerentiated in panel B to more clearly illustrate the changes that have occurred over time.Critical ratios for cyanobacteria dom-inance are taken from Smith et al.(1995)for the lake water and Flett et al.(1980)for theloads.Fig.3.Yearly average concentrations of soluble reactive phosphorus,SRP (A),dissolved inorganic nitrogen,DIN (B),and the DIN:SRP ratio (C)in Lake Okeechobee from 1973to 2000.The data are means calculated from monthly or semi-monthly sampling at the eight pelagic stations shown in Fig.1.The critical ratio of 10:1by mass (Horne and Commins,1987),below which cyanobacteria dominance is predicted to occur,is shown in panel C.K.E.Havens et al./Environmental Pollution 122(2003)379–390383SRP concentrations relative to porewater conditions that were measured one decade ago provides additional support for this hypothesis.The nutrient loading study by Janus et al.(1992)occurred just after a large pelagic bloom of Anabaena circinalis occurred in summer 1986(Jones,1987;Swift et al.,1987).However,despite a consistently low N:P residence time ratio,large pelagic Anabaena blooms have not re-occurred on the lake.Blooms of hetero-cystous cyanobacteria are instead frequently observed in sheltered regions near the lake shore,where there is a strong positive correlation between algal blooms and concentrations of TP in the water (Havens and Walker,2002).4.3.Other water quality attributesCoincident with the increasing TP concentrations in Lake Okeechobee there has been a decline in Secchi disk transparency (Fig.6A).There has not,however,been a corresponding increase in phytoplankton chlorophyll a (Fig.6B),suggesting that the lake may have experienced an increase in the amount of mineral turbidity in its water column,possibly due to greater sediment resus-pension.There is unfortunately no long-term record of non-volatile suspended solids for this lake,so it is not possible to test this hypothesis directly.However,Havens and James (1999)documented that there has been lateral expansion of the soft ﬂuid mud sediments that occur in the lake’s central pelagic area,and that site-speciﬁc declines in Secchi disk transparency coin-cide temporally with sediment migration into certain lake regions.The observed decline in average Secchi depth may therefore indicate a progressive increase in the number of pelagic stations with low transparencies,as mud sediment has migrated outward over time from the lake’s center.Other hypotheses,such as tightly cou-pled primary production/zooplankton grazing/detritus production,seem less likely,because it has been experi-mentally documented that zooplankton grazing has no signiﬁcant eﬀects on phytoplankton in this lake (Havens et al.,1996).Diminished light conditions in the lake might favor Oscillatoriaceae,as noted above.Alternatively,the lower light levels could suppress dominance by all spe-cies of cyanobacteria,in favor of other phytoplankton,if the concentrations of inorganic suspended seston become suﬃciently high (van Duin et al.,1995;Knowl-ton and Jones,1996;Smith and Bennett,1999).4.4.Cyanobacteria biomass and dominanceIn 1974,the biovolume of cyanobacteria averaged ca.3Â106m m 3ml À1,accounting for roughly 30%of the total phytoplankton biovolume in the lake (Fig.7A,B).The total biovolumes of cyanobacteria in 1989,1990,Fig.6.Yearly average Secchi disk transparencies (A)and concentra-tions of plankton chlorophyll a (B)in Lake Okeechobee from 1973to 2000.The data are means calculated from monthly or semi-monthly sampling at the eight pelagic stations shown in Fig.1.Fig.5.Ratio of nitrogen to phosphorus residence time (t N /t P )in Lake Okeechobee from 1973to 2000(A).The solid line is a least-squares linear regression model ﬁt to the phosphorus assimilation by the lake from 1973to 2000(B).The solid line is a polynomial regres-sion model ﬁt to the data.Methods for calculating residence time and assimilation are described in the text.384K.E.Havens et al./Environmental Pollution 122(2003)379–3901992and 1997–2000were not dramatically diﬀerent than in 1974,but their contribution to the total phyto-plankton biovolume was consistently higher than in 1974,with the relative biomass of all cyanobacteria ranging from 50to 80%.This increase in cyanobacterial dominance agrees with expectations based on the observed reductions in lake water TN:TP ratios,and with the widespread N-limitation of phytoplankton production that has been documented in Lake Okee-chobee during the past decade (Aldridge et al.,1995;Phlips et al.,1997).In the document containing phytoplankton data from 1974(Marshall,1977),there are no quantitative data regarding individual taxa of algae.Therefore it is not possible to evaluate the relative biomass of N 2-ﬁxing vs.non N 2-ﬁxing cyanobacterial species in that year.How-ever,in 1989,1990and 1992,the contributions of het-erocystous cyanobacteria to the total (Fig.8A)were only 20–40%,and similar results were obtained in 1997to 1999.A much higher relative biomass (80%)of N 2-ﬁxing cyanobacteria occurred in 2000,a year when water levels dropped by nearly 1.5m during a regional drought,and large near-shore areas exhibited con-siderably enhanced light penetration through the water column (Havens et al.,2001).These improved lightconditions might have stimulated growth of N 2-ﬁxing cyanobacteria,which subsequently were transported to the pelagic region.In 2000,the cyanobacteria was dominated by Anabaena spp.(A.circinalis and A.lim-netica ),whereas Oscillatoria and Lyngbya were domi-nant in the other years when water column light availability was lower (Fig.8B).In certain years (1989and 1997),Cylindrospermopsis also had a relatively high biovolume.This alga is a N 2-ﬁxer in the family Nosto-caceae,but it has morphological and ecological char-acteristics resembling members of the family Oscillatoriaceae (see below).The dominance by Oscillatoria and Lyngbya in most years of the survey,when Secchi disk transparency was low,is consistent with the general model presented in Havens et al.(1998),and with research results from other shallow turbid lakes.Berger (1989)concluded that lakes with mean depth of <3.0m and low Secchi depth are expected to be dominated by Oscillatoriaceae,which have adaptations to permit eﬀective light harvesting under low irradiance conditions.These adaptations include high chlorophyll-to-biovolume ratios,high con-centrations of accessory photo-pigments,and a large surface-to-volume ratio (Zevenboom et al.,1982;Fig.8.Percent of yearly averaged cyanobacteria biovolumes due to N 2-ﬁxing and non-N 2-ﬁxing taxa (A)in Lake Okeechobee in 1989–1992,and 1997–2000.Corresponding data for the dominant cyano-bacteria genera (B).There are no comparable data at this level of resolution available from the 1974study.Fig.7.Yearly average biovolumes (A)of total phytoplankton and cyanobacteria in Lake Okeechobee in 1974,1989–1992,and 1997–2000.The data are means of monthly sampling at the four pelagic stations shown in Fig.1.Relative cyanobacterial biomass (percent of total biovolume due to cyanobacteria)(B)based on the same data.K.E.Havens et al./Environmental Pollution 122(2003)379–390385Hosper,1997;Phlips et al.,1997).Reynolds(1984) called these taxa the‘‘shade plants’’of the phyto-plankton,and there are many reports in the literature of near-complete dominance of the plankton by Oscilla-toria,Lyngbya,and Planktothrix in strongly light-lim-ited lakes(e.g.Berger1989;Rucker et al.,1997;Scheﬀer et al.,1997).A detailed evaluation of phytoplankton responses to light and nutrients in Lake Okeechobee(Phlips et al., 1997)supports the hypothesis that low light conditions have a strong controlling inﬂuence on phytoplankton community structure.A series of controlled experiments were performed in1994and1995to evaluate growth responses of the lake’s phytoplankton to a range of irradiances and N and P concentrations;these experi-ments were coupled with simultaneousﬁeld observa-tions of heterocyst abundance,N2ﬁxation,and DIN concentrations.The experiments conﬁrmed that low light availability in the pelagic zone,during winter to spring,limits algal growth to a level below that poten-tially supported by available supplies of N and P. Nitrogen limits algal growth in summer and early fall,at which time there is a signiﬁcant relationship in the lake between heterocyst density,N2ﬁxation,and the deple-tion of DIN.Phlips et al.(1997)also documented that during1994–1995(a period not covered by our routine sampling program),the dominant phytoplankton taxa were non-heterocystous cyanobacteria(Oscillatoria and Lyngbya),small centric diatoms,and1–2m m pico-phy-toplankton.The authors suggested that the small cell size/ﬁlament diameter of these species allows them to make better use of the low amounts of light in the water column,and that this largely determines their dom-inance.On one occasion(May–June1994),however,the phytoplankton at a northern station(L001)was instead dominated by Anabaena.This species shift coincided with high rates of N2ﬁxation,a high density of hetero-cysts,a peak in total phytoplankton biomass,and importantly,an increase in the mean water column irradiance.Taken together,these results support the hypothesis that in Lake Okeechobee a low lake water TN:TP ratio provides nutrient conditions that are potentially favorable for dominance by N2-ﬁxing cya-nobacteria,but that their occurrence is often modiﬁed or restricted by low light availability.The occurrence of Cylindrospermopsis in Lake Okee-chobee is consistent with the hypothesis that low irra-diances aﬀect taxonomic structure in the cyanobacteria assemblage(Havens et al.,1998).Although this alga can ﬁx N2,it often does not produce heterocysts,and unlike other members of the family Nostocaceae,when it pro-liferates,theﬁlaments remain mixed through the water column(i.e.it does not form surface blooms;St. Amand,2002).The cells are very small(2–3m m),pro-viding a large surface to volume ratio,and active growth can occur under low light conditions.Cylindrospermopsis has invaded many eutrophic Florida lakes(Chapman and Schelske,1997;St. Amand,2002),ﬁlling a niche typically exploited by Oscillatoria and Lyngbya.Further research is needed to quantify competition between Cylindrospermopsis and the native phytoplankton taxa for resources,including dissolved inorganic N.Research should also be designed to tease apart the interactive eﬀects of nutrient supply, light levels,and turbulence on control of cyanobacterial community structure and competitive interactions with eukaryotic phytoplankton.parisons with published data and empirical modelsSmith(1985)presented data fromﬁve sources in Eur-ope and North America,which when plotted as growing season averages,indicate an inverse relationship between cyanobacterial dominance and TN:TP ratios. When his data were re-plotted with the data from Lake Okeechobee(Fig.9A),it is apparent that our new resultsﬁt the general inverse pattern,with percent cya-nobacteria values at the higher end of the range observed by Smith(1985),except for the1974datum. Fig.9.Relationship between percent of total phytoplankton biovo-lume due to cyanobacteria(A)and percent due to N2-ﬁxing cyano-bacteria(B)and water column TN:TP ratios.Open circles are data from various lakes compiled by Smith(1985);closed triangles are the data from Lake Okeechobee.In panel B there are only7data points, because the report of phytoplankton studies from1974(Marshall, 1977)did not quantify the percentage of N2-ﬁxing cyanobacteria in the community.386K.E.Havens et al./Environmental Pollution122(2003)379–390。

Observations of volcanic ash by lidar and MODIS

Calculations for different possible refractive indices: median diameter greater than 800
microns
Upper bound ~2 microns assuming not liquid water
Colour ratios
it did over Chilbolton…
As over Chilbolton, ash much more depolarizing than ordinary
boundary-layer aerosol
Calipso lidar 16th April
Ash higher at leading (southern) edge, explaining the descending appearance to groundbased lidar
• The amounts are much less that UK air quality objective (1 hr average exceeds 350 mg m-3 less than 24 times per year)
No convincing sign of ash
Aerosol particles (PM10s)
microns
Colour ratios: 905/1500
Note contrast with ordinary boundary layer different possible refractive indices: median diameter greater than 800
Ultraviolet EZ-lidar, Cardington Bedfordshire, 16th April

专题05 阅读理解D篇(2024年新课标I卷) (专家评价+三年真题+满分策略+多维变式) 原卷版

《2024年高考英语新课标卷真题深度解析与考后提升》专题05阅读理解D篇（新课标I卷）原卷版(专家评价+全文翻译+三年真题+词汇变式+满分策略+话题变式)目录一、原题呈现P2二、答案解析P3三、专家评价P3四、全文翻译P3五、词汇变式P4(一)考纲词汇词形转换P4(二)考纲词汇识词知意P4(三)高频短语积少成多P5(四)阅读理解单句填空变式P5(五)长难句分析P6六、三年真题P7(一)2023年新课标I卷阅读理解D篇P7(二)2022年新课标I卷阅读理解D篇P8(三)2021年新课标I卷阅读理解D篇P9七、满分策略（阅读理解说明文）P10八、阅读理解变式P12 变式一：生物多样性研究、发现、进展6篇P12变式二：阅读理解D篇35题变式（科普研究建议类）6篇P20一原题呈现阅读理解D篇关键词: 说明文;人与社会;社会科学研究方法研究;生物多样性; 科学探究精神;科学素养In the race to document the species on Earth before they go extinct, researchers and citizen scientists have collected billions of records. Today, most records of biodiversity are often in the form of photos, videos, and other digital records. Though they are useful for detecting shifts in the number and variety of species in an area, a new Stanford study has found that this type of record is not perfect.“With the rise of technology it is easy for people to make observation s of different species with the aid of a mobile application,” said Barnabas Daru, who is lead author of the study and assistant professor of biology in the Stanford School of Humanities and Sciences. “These observations now outnumber the primary data that comes from physical specimens(标本), and since we are increasingly using observational data to investigate how species are responding to global change, I wanted to know: Are they usable?”Using a global dataset of 1.9 billion records of plants, insects, birds, and animals, Daru and his team tested how well these data represent actual global biodiversity patterns.“We were particularly interested in exploring the aspects of sampling that tend to bias (使有偏差) data, like the greater likelihood of a citizen scientist to take a picture of a flowering plant instead of the grass right next to it,” said Daru.Their study revealed that the large number of observation-only records did not lead to better global coverage. Moreover, these data are biased and favor certain regions, time periods, and species. This makes sense because the people who get observational biodiversity data on mobile devices are often citizen scientists recording their encounters with species in areas nearby. These data are also biased toward certain species with attractive or eye-catching features.What can we do with the imperfect datasets of biodiversity?“Quite a lot,” Daru explained. “Biodiversity apps can use our study results to inform users of oversampled areas and lead them to places – and even species – that are not w ell-sampled. To improve the quality of observational data, biodiversity apps can also encourage users to have an expert confirm the identification of their uploaded image.”32. What do we know about the records of species collected now?A. They are becoming outdated.B. They are mostly in electronic form.C. They are limited in number.D. They are used for public exhibition.33. What does Daru’s study focus on?A. Threatened species.B. Physical specimens.C. Observational data.D. Mobile applications.34. What has led to the biases according to the study?A. Mistakes in data analysis.B. Poor quality of uploaded pictures.C. Improper way of sampling.D. Unreliable data collection devices.35. What is Daru’s suggestion for biodiversity apps?A. Review data from certain areas.B. Hire experts to check the records.C. Confirm the identity of the users.D. Give guidance to citizen scientists.二答案解析三专家评价考查关键能力，促进思维品质发展2024年高考英语全国卷继续加强内容和形式创新，优化试题设问角度和方式，增强试题的开放性和灵活性，引导学生进行独立思考和判断，培养逻辑思维能力、批判思维能力和创新思维能力。

the tyndall effect thus implies

the tyndall effect thus implies“The Tyndall Effect”is a phenomenon often observed in everyday life, in which the scattering of light by suspended particles in a medium leads to the appearance of a visible beam of light. In this article, we will explore the underlying principles behind the Tyndall Effect and delve into its implications in various fields.Firstly, let us understand the basic concept of the Tyndall Effect. Named after the 19th-century physicist John Tyndall, this effect occurs when light encounters particles within a medium, causing some of the light rays to scatter in different directions. The scattered light is then reflected or refracted, creating a visible beam or cone of light. This phenomenon is most noticeable when a beam of light passes through a cloudy liquid or a dusty room, where suspended particles are abundant.To comprehend why the Tyndall Effect occurs, we must delve into the behavior of light waves. Light is composed of electromagnetic waves, which consist of alternating electric and magnetic fields. When light interacts with particles in a medium, such as smoke particles or water droplets, the electric and magnetic fields can induce a dipole moment within the particles. As a result of thisinteraction, the light waves are scattered in various directions.The intensity and color of the scattered light depend on the size of the particles and the wavelength of light. If the particles are larger than the wavelength of incident light, the scattered light will contain various colors, resulting in white light. However, if the particles are smaller than the wavelength of light, the scattering will be more pronounced for shorter wavelengths, such as blue and violet light. This explains why the scattered light appears blue, while the transmitted light through the medium appears yellow or red, as blue light is scattered more strongly in the atmosphere.Now that we have grasped the fundamental principles of the Tyndall Effect, let us explore its implications in various fields. One significant area where the Tyndall Effect is commonly observed is in atmospheric science. This phenomenon plays a crucial role in the scattering of sunlight in the Earth's atmosphere, giving rise to the blue color of the sky. As sunlight encounters tiny molecules and particles in the atmosphere, the shorter blue and violet wavelengths of light are scattered more efficiently, creating the appearance of a blue sky.Additionally, the Tyndall Effect has significant applications in the field of medical diagnostics. This effect is often exploited in technologies such as turbidimetry and nephelometry, which measure the concentration of suspended particles in a liquid sample. By analyzing the scattered light, these techniques allow healthcare professionals to identify abnormalities or monitor the progress of certain diseases, such as kidney disorders or bacterial infections.Furthermore, the Tyndall Effect has numerous applications in industrial processes. For instance, in the field of cosmetics, manufacturers use this phenomenon to create shimmering or sparkling effects in products. By incorporating finely suspended particles that scatter light, such as mica or titanium dioxide, cosmetics can enhance the perceived appearance of skin or add an iridescent quality to lipsticks or nail polishes.In conclusion, the Tyndall Effect is a fascinating phenomenon that arises from the scattering of light by suspended particles in a medium. This effect has implications in various fields, ranging from atmospheric science to medical diagnostics and industrialapplications. By understanding the underlying principles behind the Tyndall Effect, we can appreciate the beauty of everyday occurrences and harness its potential in diverse areas of research and development.。

层序地层学的名词英语解释

层序地层学的名词英语解释GlossaryAccommodation. Another term for relative sea-level. Can be thought of as the space in which sediments can fill, defined at its base by the top of the lithosphere and at its top by the ocean surface.Basinward Shift in Facies. When viewed in cross-section, a shifting of all facies towards the center of a basin. Note that this is a lateral shift in facies, such that in vertical succession, a basinward shift in facies is characterized by a shift to shallow facies (and not a vertical shift to more basinward or deeper-water facies).Bed. Layer of sedimentary rocks or sediments bounded above and below by bedding surfaces. Bedding surfaces are produced during periods of nondeposition or abrupt changes in depositional conditions, including erosion. Bedding surfaces are synchronous when traced laterally; therefore, beds are time-stratigraphic units. See Campbell, 1967 (Sedimentology 8:7-26) for more information.Bedset. Two or more superposed beds characterized by the same composition, texture, and sedimentary structures. Thus, a bedset forms the record of deposition in an environment characterized by a certain set of depositional processes. In this way, bedsets are what define sedimentary facies. Equivalent to McKee and Weir's coset, as applied to cross-stratification. See Campbell, 1967 (Sedimentology 8:7-26) for more information.Condensation. Slow net rates of sediment accumulation. Stratigraphic condensation can occur not only through a cessation in the supply of sediment at the site of accumulation, but also in cases where the supply of sediment to a site is balanced by the rate of re moval of sediment from that site. Where net sediment accumulation rates are slow, a variety of unusual sedimentologic features may form, including burrowed horizons, accumulations of shells, authigenic minerals (such as phosphate, pyrite, siderite, glauconite, etc.), early cementation and hardgrounds, and enrichment in normally rare sedimentary components, such as volcanic ash and micrometeorites.Conformity. Bedding surface separating younger from older strata, along which there is no evidence of subaerial or submarine erosion or nondeposition and along which there is no evidence of a significant hiatus. Unconformities (sequence boundaries) and flooding surfaces (parasequence boundary) will pass laterally into correlative conformities, most commonly in deeper marine sediments.Eustatic Sea Level. Global sea level, which changes in response to changes in the volume of ocean water and the volume of ocean basins.Flooding Surface. Shortened term for a marine flooding surface.Highstand Systems Tract. Systems tract overlying a maximum flooding surface, overlain by a sequence boundary, and characterized by an aggradational to progradational parasequence set.High-Frequency Cycle. A term applied to a cycle of fourth order or higher, that is, having a period of less than 1 million years. Parasequences and sequences can each be considered high-frequency cycles when their period is less than 1 million years. Isostatic Subsidence. Vertical movements of the lithosphere as a result of increased weight on the lithosphere from sediments, water, or ice. Isostatic subsidence is a fraction of the thickness of accumulated material. For example, 100 meters of sediment will drive about 33 meters of subsidence (or less, depending on the rigidity of the lithosphere).Lowstand Systems Tract. Systems tract overlying a type 1 sequence boundary, overlain by a transgressive surface, and characterized by a progradational to aggradational parasequence set.Marine Flooding Surface. Surface separating younger from older strata, across which there is evidence of an abrupt increase in water depth. Surface may also display evidence of minor submarine erosion. Forms in response to an increase in water depth.Maximum Flooding Surface. Marine flooding surface separating the underlying transgressive systems tract from the overlying highstand systems tract. This surface also marks the deepest water facies within a sequence. This flooding surface lies at the turnaround from retrogradational to progradational parasequence stacking, although this turnaround may be gradational and characterized by aggradational stacking. In this case, a single surface defining the point of maximum flooding may not be identifiable, and a maximum flooding zone is recognized instead. The maximum flooding surface commonly, but not always, displays evidence of condensation or slow deposition, such as burrowing, hardgrounds, mineralization, and fossil accumulations. Because other flooding surfaces can have evidence of condensation (in some cases, more than the maximum flooding surface), condensation alone should not be used to define the maximum flooding surface. Meter-Scale Cycle. A term applied to a cycle with a thickness of a couple of meters or less. Parasequences and sequences can each be considered meter-scale cycles when they are thinner than a couple of meters.Parasequence. Relatively conformable (that is, containing no major unconformities), genetically related succession of beds or bedsets bounded by marine-flooding surfaces or their correlative surfaces. Parasequences are typically shallowing-upward cycles.Parasequence Boundary. A marine flooding surface.Parasequence Set. Succession of genetically related parasequences that form a distinctive stacking pattern, and typically bounded by major marine flooding surfaces and their correlative surfaces. Parasequence set boundaries may coincide with sequence boundaries in some cases. See progradational, aggradational and retrogradational parasequence sets.Peritidal. All of those depositional environments associated with tidal flats, including those ranging from the highest spring tides to somewhat below the lowest tides.Relative Sea Level. The local sum of global sea level and tectonic subsidence. Locally, a rise in eustatic sea level and an increase in subsidence rates will have the same effect on accommodation. Likewise, a fall in eustatic sea level and tectonic uplift will have the same effect on accommodation. Because of the extreme difficulty in teasing apart the effects of tectonic subsidence and eustatic sea level in regional or local studies, sequence stratigraphy now generally emphasizes relative changes in sea level, as opposed to its earlier e mphasis on eustatic sea level.Sequence. Relatively conformable (that is, containing no major unconformities), genetically related succession of strata bounded by unconformities or their correlative conformities.Sequence Boundary. Form in response to relative falls in sea level.Sequence Stratigraphy. The study of genetically related facies within a frameworkof chronostratigraphically significant surfaces.Shelf Margin Systems Tract. Systems tract overlying a type 2 sequence boundary, overlain by a transgressive surface, and characterized by a progradational to aggradational parasequence set. Without regional seismic control, most shelf margin systems tracts may be unrecognizable as such and may be inadvertently lumped with the underlying highstand systems tract as part of one uninterrupted progradational parasequence set. If this occurs, the overlying transgressive surface may be erroneously inferred to also be a type 1 sequence boundary.Systems Tract. Linkage of contemporaneous depositional systems, which are three-dimensional assemblages of lithofacies. For example, a systems tract might consist of fluvial, deltaic, and hemipelagic depositional systems. Systems tracts are defined by their position within sequences and by the stacking pattern of successive parasequences. Each sequence consists of three systems tract in a particular order. For a type 1 sequence, these are the lowstand, transgressive, and highstand systems tracts. For a type 2 sequence, these are the shelf margin, transgressive, and highstand systems tracts.Tectonic Subsidence. Vertical movements of the lithosphere, in the absence of any effects from changes in the weight of overlying sediments or water. Also called driving subsidence. Tectonic subsidence is generated primarily by cooling, stretching, loading (by thrust sheets, for example), and lateral compression of the lithosphere.Transgressive Surface. Marine flooding surface separating the underlying lowstand systems tract from the overlying transgressive systems tract. Typically, this is the first major flooding surface following the lowstand systems tract. In depositionally updip areas, the transgressive surface is commonly merged with the sequence boundary, with all of the time represented by the missing lowstand systems tract contained within the unconformity. The transgressive surface, like all of the major flooding surfaces within the transgressive systems tract, may display evidence of stratigraphic condensation or slow net deposition, such as burrowed surfaces, hardgrounds, mineralization, and fossil accumulations.Transgressive Systems Tract. Systems tract overlying a transgressive surface, overlain by a maximum flooding surface, and characterized by a retrogradational parasequence set.Type 1 Sequence Boundary. Characterized by subaerial exposure and associated erosion from downcutting streams, a basinward shift in facies, a downward shift in coastal onlap, and onlap of overlying strata. Forms when the rate of sea-level fall exceeds the rate of subsidence at the depositional shoreline break (usually at base level or at sea level). Note that this means that if such changes can be observed in outcrop and the underlying strata are marine, then the boundary is a type 1 sequence boundary.Type 2 Sequence Boundary. Characterized by subaerial exposure and a downward shift in onlap landward of the depositional shoreline break (usually at base level or at sea level). Overlying strata onlap this surface. Type 2 sequence boundaries lack subaerial erosion associated with the downcutting of streams and lack a basinward shift in facies. Forms when the rate of sea-level fall is less than the rate of subsidence at the depositional shoreline break. Note that the lack of a basinward shift in facies and the lack of a relative fall in sea level at the depositional shoreline break means that there are essentially no criteria by which to recognize a type 2 sequence boundary in outcrop.Unconformity. Surface separating younger from older strata, along which there is evidence of subaerial erosional truncation or subaerial exposure or correlative submarine erosion in some areas, indicating a significant hiatus. Forms in response to a relative fall in sea level. Note that this is a much more restrictive definition of unconformity than is commonly used or used in earlier works on sequence stratigraphy (e.g., Mitchum, 1977).Walther's Law states that "...only those facies and facies areas can be superimposed, without a break, that can be observed beside each other at the present time" (Middleton translation from German). At a Waltherian contact, one facies passes gradationally into an overlying facies, and those two facies represent sedimentary environments that were originally adjacent to one another.Water Depth. The distance between the sediment surface and the ocean surface. Water depth is reflected in sedimentary facies. A very large number of studies that purport to describe sea-level changes (both eustatic and relative) are actually only describing changes in water depth. The effects of isostatic subsidence and compaction must be removed from water depth to calculate relative sea level. This is typically done through backstripping. To calculate eustatic sea level, the rate of tectonic subsidence must then be subtracted from the relative sea-level term.。

阐释现象考博英语作文模版

阐释现象考博英语作文模版Expounding the Phenomenon.Expounding a phenomenon encompasses an exhaustive exploration of its various facets, encompassing its genesis, underlying mechanisms, and far-reaching implications. To accomplish this endeavor effectively, a systematic approach is paramount, guided by a precise outline that ensures both clarity and coherence.I. Introduction.A compelling introduction serves to captivate thereader's attention and establish the significance of the phenomenon under investigation. It should succinctly define the phenomenon, emphasizing its unique characteristics and relevance to a broader context. Furthermore, theintroduction should provide a concise overview of thepaper's structure, outlining the key arguments and evidence that will be presented.II. Theoretical Framework.The theoretical framework section provides a comprehensive analysis of the phenomenon through the lens of established theories and concepts. It draws upon relevant literature to construct a coherent explanation of the phenomenon's origins, mechanisms, and dynamics. This section should demonstrate a thorough understanding of the theoretical underpinnings of the phenomenon and their application to the specific context under study.III. Empirical Evidence.Empirical evidence serves as the backbone of any scientific investigation. This section presents a comprehensive analysis of data collected through various research methods, such as surveys, experiments, interviews, or observations. The data should be presented in a clear and concise manner, using tables, graphs, or other visual aids as necessary. The analysis should demonstrate a systematic approach to data interpretation, highlightingpatterns, trends, and relationships that support the theoretical framework.IV. Discussion and Implications.The discussion section provides an in-depth interpretation of the findings, linking them back to the theoretical framework and the broader context. It explores the significance of the results, considering their implications for theory, policy, and practice. This section should also address any limitations or weaknesses of the study, as well as suggest directions for future research.V. Conclusion.The conclusion provides a concise summary of the main arguments and findings of the paper. It reiterates the significance of the phenomenon, emphasizing itsimplications and the broader contributions it makes to the field of study. The conclusion should leave the reader with a clear understanding of the phenomenon's multifaceted nature and its enduring relevance.In conclusion, expounding a phenomenon requires a systematic and rigorous approach that encompasses a thorough theoretical framework, empirical evidence, discussion, and a comprehensive conclusion. By adhering to this framework, researchers can effectively unravel the intricacies of complex phenomena, advancing our understanding and paving the way for further exploration and discovery.。

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a r X i v :h e p -p h /9709255v 1 5 S e p 1997OBSERVATION OF LOW x PHENOMENA IN HADRONIC FINAL STATES ∗G ¨UNTER GRINDHAMMERMax-Planck-Institut f¨u r Physik,(Werner-Heisenberg-Institut)80805M¨u nchen,Germany E-mail:guenterg@desy.de(On behalf of the H1and ZEUS collaborations)ABSTRACTThe expectations for and the measurements of transverse energy ﬂows,single particle p T spectra,and the rate of forward jets in deep inelastic ep events from the H1and ZEUS experiments at HERA are reported and discussed.It is shown that together they oﬀer a good chance to establish deviations from the DGLAP paradigm.At the present level of limited statistics the measurements are compatible with predictions using BFKL resummation and with the color dipole model.Models based on DGLAP evolution describe the p T spectra and forward jets less well but are not ruled out yet.1.Expectations and ObservablesIn deep inelastic scattering (DIS)at low x the simple picture of the quark parton model,where a virtual photon interacts with a point-like parton in the proton and nothing else happens,has to be modiﬁed.The probability that additional partons,particularly gluons,are radiated increases with decreasing x .An example,where a low x parton,which interacts with the photon,originates from a parton shower initiated by a gluon with large x ,is shown in Fig.1.In the approximation of just one gluon being radiated in the initial or the ﬁnal state,such processes have been calculated in next to leading order (NLO).Two programs,MEPJET 1and DISENT 2,using diﬀerent methods,are available,and a new program,DISASTER++3,has been announced at this meeting.These programs generate partons only;no full event generators exist.e 'x 1, k T1x i , k T i x i+1, k T i+1current jet(s)proton remnant}γ*-p CMS photon fragm.central rapidity proton fragm.HERAdetector central part of detector forward regionbeam pipeFig.1.Diagram of an ep collision at low x .In the leading log approxima-tion any number of more or less collinear or soft gluons may be ra-diated.By resumming terms of theform (αs ln Q2∗To appear in Proc.of “New Trends in HERA Physics”,Ringberg,Tegernsee,Germany,May 1997.implies weakly ordered fractional gluon energies(longitudinal momenta)x i>x i+1 and strongly ordered gluon virtualities or transverse gluon momenta k T,i<<k T,i+1 along the ladder(Fig.1).Diﬀerent implementations of“DGLAP-like”parton showers and of matching5,6them to leading order(LO)exact matrix elements for the QCD-Compton(QCDC)and the boson-gluon fusion(BGF)process exist in LEPTO7, RAPGAP8,and HERWIG9.For the hadronisation of the perturbative partons to the observable hadrons,these programs include phenomenological models.HERWIG uses the cluster model10;all other programs,including ARIADNE11,use the LUND string model12,as implemented in the JETSET13code.These fragmentation models have been well tested at LEP14.At HERA and at hadron colliders,the additional complication of proton remnant fragmentation arises,about which much less is known.At low x,terms of the form(αs ln1It has been shown that all models provide a fair description of basic event prop-erties20,21,22.At very low x the gluon density may possibly become so high in regions(“hot spots”)of the proton that the gluons will no longer act as free particles but will interact with each other.In this saturation regime of QCD,the strong coupling is still small,but the incoherent scattering approximation is no longer valid.It is not clear whether this new regime could be observed at HERA.What do we expect to see at HERA?Which observables will be most sensitive to the underlying parton dynamics?As x decreases below10−3we anticipate deviations from the DGLAP predictions due to the missing(αs ln1a Rapidity is here always pseudo-rapidity,i.e.η=−ln tan(θ/2).b E T= E i sinθi,i runs over calorimeter cells.radiation or hadronisation.As indicated in Fig.1the central rapidity in the hcms corresponds to the forward region in the frame of the HERA detectors.1/N d E T /d η*(G e V )CMS η*Fig.2.Transverse energy ﬂow as a function of rapidity η∗in the hcms.The H1data points show statistical errors only,except for two points measured with the plug calorimeter where the statistical and systematic errors are given.The lines are the Monte Carlo predictions of three diﬀerent models.First results on the E T -ﬂows have been published by the H1collaboration 27,28,29.In ref.29they have been reported for DIS events with 5GeV 2<Q 2<50GeV 2and with 10−4<x <10−2in the hcms and have been compared to the then current model predictions of LEPTO 6.1and ARIADNE 4.03.In the largest x and Q 2bin,i.e.x ≈5×10−3and Q 2≈33GeV 2,the data and the two models were found to agree.With decreasing x for ﬁxed Q 2the E T from LEPTO 6.1was found to fall more and more below the data for rapidities away from the current jet,while ARIADNE 4.03still managed to give a level of E T in agreement with the data.At this point in time one could have had the impression that models with DGLAP-like dynamics like LEPTO fail to describe the data at low x ,while models with someBFKL-like features like ARIADNE are successfull.However,soon after,two new phenomenological features have been added to LEPTO which allowed a reasonably good description of the transverse energy ﬂows also for decreasing x .The new features are soft color interactions 30,with the intention to describe rapidity gap events without modeling a Pomeron and its structure function,and a modiﬁed sea-quark/remnant treatment,giving a smoother transition from BGF events to events where the photon interacts with a sea-quark.The H1collaboration in the meantime has produced new preliminary data 31,32,covering a larger range in the kinematic plane from 3<Q 2<70GeV 2and 8×10−5<x <7×10−3.The extension to lower Q 2was achieved by analysing data from special runs,where the point of the ep interactions was shifted from the nominal position in the direction of the proton beam in order to have access to smaller lepton scattering angles.In addition,the E T at two very forward rapidity bins was measured by H1using their plug calorimeter (0.72◦<θlab <3.3◦),which closes the gap between the beam-pipe and the forward part of their liquid Argon calorimeter.The data as a function of rapidity c in the hcms are shown in bins of x and Q 2in Fig.2.They are compared to predictions from ARIADNE 4.08,HERWIG 5.8,and LEPTO 6.4.The models give only a fair description of the data over the large range in x and Q 2.The average E T in the central rapidity −0.5<η∗<0.5as a function of x in bins of ﬁxed Q 2increases with decreasing x 31,32.This is demonstrated in Fig.3a for the bin Q 2=14GeV 2,together with data from ZEUS 33,and with predictions fromx<E T >x0.250.50.7511.251.51.7522.252.51010Fig.3.Mean transverse energy in the central rapidity bin in the hcms for the bin Q 2=14GeV 2.Besides the data from H1and ZEUS,QCD model predictions (lines)are shown for hadrons in a)and for partons in b).An analytic BFKL calculation at the parton level is shown as open circles.diﬀerent generators at the hadron level.For LEPTO the predictions are shown with the new soft color interactions (SCI)and the new sea-quark treatment (SQT)turned on and oﬀ.The data of both experiments are in good agreement and can be describedby all models,DGLAP and BFKL-like.In Fig.3b the predictions of the models at the hadron level are contrasted with those at the parton level and with an analytic parton level BFKL calculation 25.At the parton level the DGLAP-like models LEPTO and HERWIG show the opposite slope in x than ARIADNE,the BFKL calculation,the hadron level of all models,and the data.The BFKL calculation gives the highest transverse energy,40%to 50%above the partons from the color dipole model.There are large diﬀerences in the contribution from fragmentation to the total E T between the models.It is about 15%for the BFKL calculation (comparing it to data),35%for ARIADNE,and about 70%for LEPTO and HERWIG.10-510-310-11/N d N /d E T (1/G e V )10-510-310-110-510-310-110-510-310-110-510-310-1Fig.4.Transverse energy distribution in the central rapidity bin in the hcms.Only statistical errorsare shown.Concerning the measurement of the mean E T in the central rapidity bin,we are now in the situation that all models describe the data.Although the models diﬀer in their underlying parton dynamics,the mean E T can be made to agree by exploiting as yet unconstrained variations in hadronisation models.Another observable investigated by H1is the distribution of the E T in the central rapidity bin per event.The E T originating from hadronisation is expected to be limited,while high values of E T are more likely to be produced by hard partonradiation.Preliminary data31,32,in the same bins of x and Q 2as in Fig.2,are displayed in Fig.4together with predictions from ARIADNE 4.08,HERWIG 5.8,and LEPTO 6.4.While at the largest x and Q 2the data and the models agree,with decreasing x and Q 2the data and ARIADNE appear to exhibit harder tails than the DGLAP-like models.As can be seen from the ﬁgure a ﬁrm conclusion can only be drawn with more statistics extending the range in E T to larger paring the E T distribution for the highest and lowest x value for ﬁxed Q 2,one ﬁnds that the data have harder tails 31,32with decreasing x ,suggesting a rise in parton activity.3.Single Particle p T SpectraThe E T measured by the calorimeter can be due to many soft particles,predom-inantly from hadronisation,or due to a few hard particles,mainly from hard gluon emission,or due to both.Therefore it has been suggested 34that the hard tail of the10-310-210-11101/N d n /d p T (G e V -1)10-310-210-1110-310-210-1110-310-210-11p T (GeV)Fig.5.The transverse momentum spectra of charged particles in the hcms.The data are shown for nine diﬀerent kinematic bins and the combined sample (bin 0).Statistical and full errors are given.p T distribution of single charged particles in the hcms might oﬀer better sensitivity to the basic parton dynamics since it is more directly linked to hard gluonemissions.The charged particle p T distributions in bins of x and Q 2as measured by H135in the rapidity interval from 0.5to 1.5are shown in Fig.5.At large x all three models presented agree with the data.With decreasing x ,LEPTO and HERWIG signiﬁcantly fall below the data for increasing p T .Predictions 36based on BFKL resummation and convolution with fragmentation functions for the transition from partons to charged hadrons 37have been made for the three lowest bins in x ,i.e.bins 1,2,and 3.As demonstrated in Fig.6for bin 3,the data and the BFKL result agree quite well for p T ≥1.5GeV.The absolute normalization was derived from a comparison of the BFKL calculation of the forward jet cross section with data from H1to be discussed later.Also displayed in the ﬁgure is the calculation with BFKL eﬀects turned oﬀ,which falls below the data.It is apparent from the ﬁgure101010101p T (GeV)1/N d n /d p T (G e V -1)Fig.6.The transverse momentum spectra of charged particles in the hcms for ﬁxed low x and Q 2(bin 3).The data and predictions from a BFKL calculation,with BFKL eﬀects oﬀand on,and with two diﬀerent choices for the scale µof the fragmentation function are compared.that the signiﬁcance of the agreement can be increased with more data at higher p T .In addition,BFKL eﬀects would become stronger,if the measurement of charged particles could be extended further in the direction of the proton remnant,i.e.to the rapidity interval −0.5<η∗<0.5.4.Forward JetsThe cross section for forward jets in DIS as a function of x has been advertised 38for some time now as an observable enhancing the eﬀects of BFKL resummation.Diagrammatically the situation is described in Fig.7.The forward jet is deﬁned bythe azimuthal angle θjet between the jet and the proton direction and its transversex jet , k Tjetx i , k T ii+1, k T i+1Fig.7.Parton evolution withforward jet.momentum k T jet .The energy of the jet is then given by E jet =k T jet /sin θjet and x jet ≈E jet /E p .We now re-quire that k 2T jet ≈Q 2which suppresses the phase space for forward jet production and for gluon emission be-tween the forward and the current jet in the DGLAPcase.In addition,we demand that x jet /x be as large aspossible which maximizes the phase space for the pro-duction of a forward jet and gluon radiation betweenit and the current jet in the BFKL scenario.For this particular kinematic conﬁguration the resummation of αs ln x jet /x terms should lead to a sizeable growth of the forward jet cross section with decreasing x .Another ad-vantage of this observable is that the parton densitiesof the proton are probed at rather large scales,x jet and k 2T jet ≈Q 2,where they are well known.Published results on forward jets are available from H129and new preliminary results from H139and from ZEUS 40.The cuts for the selection of DIS events and the requirements on the forward jet are summarized in Table 1.Both experiments use a cone algorithm,requiring a minimum p T jet in a cone of radius R =√H111GeV 0.1173◦160◦cone in lab,R1.0θjet >10◦p T jet >5.0GeV x jet >0.035θjet <-p 2T jet0.5Q 2<4.0experiments in the cuts on θjet ,p T jet ,and the upper limit on p 2T jet /Q 2which will be discussed later.With the CDM the transverse energy ﬂow around the forward jet axis can be well described for diﬀerent values of p T jet 39as well as many other distributions 41,42.In Fig.8the ZEUS forward jet cross section corrected to the parton level of ARIADNE is shown and compared to several parton level calculations:an analytic BFKL calculation 43,the same calculation but without any gluon emission between the forward and the current jet system (Born BFKL),and a ﬁxed NLO QCD cal-culation using MEPJET.The data show a much faster rise with decreasing x than the calculations without BFKL resummation.The BFKL calculation shows an even more dramatic rise.The authors 43,however,point out that several eﬀects which have not been taken into account might lower their prediction.ZEUS presents their preliminary result corrected to the parton level in order to compare to parton level ing ARIADNE correction factors are found to vary between 0.6for the lowest x bin and ≈1for larger x .It will be useful to have the ZEUS cross section also at the hadron level,since it is not clear,what the relationship is between the parton level of the CDM and BFKL.It could also allow comparisons with H1data which are corrected to the hadron level.50100150200250x Bjorkend σ/d x B j [n b ]Fig.8.The diﬀerrential forward jet cross section as a function of x .The ZEUS data have been corrected to the parton level.Statistical and systematic errors (not yet complete)are included.BFKL calculations,with BFKL eﬀects on (dash-dotted line)and oﬀ(dotted line),calculations in NLO QCD using MEPJET,and parton level results from the color dipole model are shown.The preliminary H1results on the forward cross section are shown in Fig.9a and are compared to predictions from LEPTO (MEPS)with and without soft color interactions (SCI)and to ARIADNE (CDM).Again a fast rise of the cross section is observed with the CDM falling only slightly below the data.In Fig.9b models and calculations at the parton level are shown:ARIADNE,LEPTO,two BFKL calculation 43,36,and a NLO calculation using DISENT.ARIADNE shows a similar x dependence at the parton and hadron level with hadronisation eﬀects amounting to less than 20%.The parton level forward jet cross sections of LEPTO and ofDISENT in NLO agree as expected and show a moderate increase.In LEPTO,with soft color interactions turned on,up to 80%of the forward jets are created in the hadronisation phase causing LEPTO to only slightly undershoot the data with decreasing x .The BFKL calculations basically can only predict the dependence on xbut not the normalization.As mentioned before,the computation by Kwiecinski et al.36ﬁxed the normalization to the data from H1while the calculation by Bartels et al.43did not.Scaling the cross section by Bartels et al.down by a factor 0.8brings the two BFKL calculations in agreement.The color dipole model provides the0.0010.0020.003 x Bj σ (p b /b i n )0.0010.0020.003x BjFig.9.The forward jet cross section as a function of x .The H1data have been corrected to the hadron level.Statistical and systematic errors are included.QCD model predictions for hadrons are superimposed in (a)and for partons in (b).Two analytic BFKL calculation (open squares and triangles)and a NLO calculation using DISENT (open circles)are also shown in (b).best description of the data.However,it should be pointed out that its prediction is rather sensitive to the power of soft suppression of gluon emission (µ/p T )αdue to the proton remnant.The parameter αis related to the dimensionality of the extended proton remnant and is expected to be ≈1.The H1forward jets prefer α≤1.0while non-jet observables like energy ﬂows prefer α≈1.520.One may wonder about the choice for the minimum p T jet ,3.5GeV by H1and 5.0GeV by ZEUS.A small value is desirable from the point of view of statistics and sensitivity to BFKL eﬀects 44.With increasing p T jet the slope in x for the forward jet cross section decreases.The requirement p T jet ≈Q 2forces the Q 2to increase,which in turn increases the minimum x which is probed.On the other hand,to suppress hadronisation eﬀects,one would want p T jet to be large.Another question concerns the choice of the upper limit on p 2T jet /Q 2which is 2.0for H1and 4.0for ZEUS.Increasing this limit from 2.0to 4.0increases in the lowestx bins the contribution from O(αs)matrix elements to the forward jets by roughly a factor of two.One would also expect an increased contribution from resolved photoproduction which is not included in the calculations.After this workshop the author of RAPGAP has shown45that for example the H1result can also be described with direct(same as in LEPTO without SCI)and resolved contributions.5.ConclusionsThe tails of the single particle p T spectra and of the calorimetric E T distribution, and the forward jet cross sections oﬀer a good chance to pin down deviations from the DGLAP paradigm.Other interesting observables in this quest,like the decorrelation of the azimuthal angle between the forward jet and the lepton43,the forwardπ◦cross section46,and the production of more than one forward jet47should be pursued.Along the way,we probably will and have to get a better understanding of hadro-nisation eﬀects,particularly of the proton remnant.On the theory side,higher order eﬀects48have to be included in the calculations and a BFKL Monte Carlo genera-tor49,50is needed.In addition to collecting more data at HERA,it would be desirable to access smaller forward angles for jets44and particles and to increase the HERA center of mass energy.6.AcknowledgementsI want to thank T.Carli,M.Wobisch,and S.W¨o lﬂe for providing me with plots and J.Dainton,J.Hartmann,and D.Kr¨u cker for a careful reading of the manuscript.I am also happy to thank the organizing committee,in particular B.Kniel,for the excellent workshop and the pleasant atmosphere.7.References1.E.Mirkes and D.Zeppenfeld,Phys.Lett.B380(1996)205.2.S.Catani and M.Seymour,Proc.Workshop on Future Physics at HERA1995/96,Hamburg,eds.G.Ingelman,A.De Roeck,and R.Klanner,vol.1(1996)519,CERN-TH/96-240(1996)[hep-ph/9609521],and Acta Phys.Polon.B28(1997)863.3.D.Graudenz,these proceedings.4.V.N.Gribov and L.N.Lipatov,Sov.J.Nucl.Phys.15(1972)438and675;G.Altarelli and G.Parisi,Nucl.Phys.B126(1977)298;Yu.L.Dokshitzer,Sov.Phys.JETP46(1977)641.5.M.Bengtsson,G.Ingelman,and T.Sj¨o strand,Proc.HERA Workshop1987,Hamburg,ed.R.D.Peccei,vol.1(1988)149;M.Bengtsson and T.Sj¨o strand,Z.Phys.C37(1988)465.6.M.H.Seymour,LU-TP-94-12,Nucl.Phys.B436(1995)443and Comput.mun.90(1995)95.7.G.Ingelman,Proc.Workshop on Physics at HERA1991,Hamburg,eds.W.Buchm¨u ller and G.Ingelman,vol.3(1992)1366;G.Ingelman,A.Edin,and J.Rathsman,mun.101(1997)108.8.H.Jung,mun.86(1995)147.9.G.Marchesini et al.,mun.67(1992)465.10.B.R.Webber,Nucl.Phys.B238(1984)492;G.Marchesini and B.R.Webber,Nucl.Phys.B310(1988)461.11.L.L¨o nnblad,m.71(1992)15and Z.Phys.C65(1995)285.12.B.Andersson,G.Gustafson,G.Ingelman,and T.Sj¨o strand,Phys.Rep.97(1983)31.13.T.Sj¨o strand,mun.82(1994)74;T.Sj¨o strand,PYTHIA5.7and JETSET7.4,CERN-TH7112/93(1993)and LU TP95-20(1995).14.I.G.Knowles et al.,Proc.LEP2Physics Workshop1995[hep-ph/9601212].15.E.A.Kuraev,L.N.Lipatov,and V.S.Fadin,Sov.Phys.JETP45(1977)199;Ya.Ya.Balitsky and L.N.Lipatov,Sov.J.Nucl.Phys.28(1978)822.16.G.Gustafson,Phys.Lett.B175(1986)453;G.Gustafson and U.Petterson,Nucl.Phys.B306(1988);B.Andersson,G.Gustafson,L.L¨o nnblad,and U.Petterson,Z.Phys.C43(1989)625.17.L.L¨o nnblad,M.Seymour,et al.,Proc.Physics at LEP2Workshop,eds.G.Altarelli,T.Sj¨o strand,and F.Zwirner,CERN/96-01,vol.2,(1996)187.18.J.Rathsman,Phys.Lett.B393(1997)181.19.A.H.Mueller,Nucl.Phys.B415(1994)373.20.N.Brook et al.,Proc.Workshop on Future Physics at HERA1995/96,Ham-burg,eds.G.Ingelman,A.De Roeck,and R.Klanner,vol.1(1996)613. 21.T.Carli,Proc.4th Int.Workshop on Deep Inelastic Scattering and RelatedPhenomena(DIS96),Roma,eds.G.D’Agostini and A.Nigro,(1997)415.22.H.Jung,private communication.23.L.Favart,these proceedings.24.A.D.Martin,these proceedings.25.K.Golec-Biernat,J.Kwiecinski,A.D.Martin,and P.J.Sutton,Phys.Rev.D50(1994)217and Phys.Lett.B335(1994)220.26.J.Bartels,H.Lotter,and M.Vogt,Phys.Lett.B373(1996)215.27.H1Collaboration,T.Ahmed et al.,Phys.Lett.B298(1993)469.28.H1Collaboration,I.Abt et al.,Z.Phys.C63(1994)377.29.H1Collaboration,S.Aid et al.,Phys.Lett.B356(1995)118.30.A.Edin,G.Ingelman,and J.Rathsman,Z.Phys.C75(1997)57and Phys.Lett.B366(1996)371.31.H1Collaboration,C.Adloﬀet al.,contrib.paper pa02-073,ICHEP’96,War-saw,Poland,July1996.32.M.F.Hess,Ph.D.Thesis,University of Hamburg(1996).33.N.A.Pavel,Proc.4th Int.Workshop on Deep Inelastic Scattering and RelatedPhenomena(DIS96),Roma,eds.G.D’Agostini and A.Nigro,(1997)502.34.M.Kuhlen,Phys.Lett.B382(1996)441.35.H1Collaboration,C.Adloﬀet al.,Nucl.Phys.B485(1997)3.36.J.Kwiecinski,ng,and A.D.Martin,DTP-97-56(1997)[hep-ph/9707240].37.J.Binnewies,B.A.Kniehl,and G.Kramer,Phys.Rev.D52(1995)4947.38.A.H.Mueller,Nucl.Phys.B(Proc.Suppl.)18C(1990)125and J.Phys.G17(1991)1443;W.K.Tang,Phys.Lett.B278(1992)363;J.Bartels,A.De Roeck,and M.Loewe,Z.Phys.C54(1992)635;A.De Roeck,Nucl.Phys.B(Proc.Suppl.)29A(1992)61;J.Kwiecinski,A.D.Martin,and P.J.Sutton,Phys.Lett.B287(1992)254, Nucl.Phys.B(Proc.Suppl.)29A(1992)67,and Phys.Rev.D46(1992)921.39.J.G.Contreras,Proc.XXXI Rencontres de Moriond in QCD and High EnergyHadronic Interactions,ed.J.Tran Thanh Van,Edition Frontieres(1996)411;H1Collaboration,C.Adloﬀet al.,contrib.paper pa03-049,ICHEP’96,War-saw,Poland,July1996.40.S.W¨o lﬂe,to be published in Proc.5th Int.Workshop on Deep Inelastic Scat-tering and QCD,Chicago,April1997,eds.D.Krakauer and J.Respond.41.J.G.Contreras,Ph.D.Thesis,University of Dortmund(1997).42.E.M.Lobodzinska,Ph.D.Thesis,Inst.of Nucl.Physics,Cracow(1997).43.J.Bartels et al.,Phys.Lett.B384(1996)300.44.J.Bartels,A.De Roeck,and M.W¨u sthoﬀ,Proc.Workshop on Future Physicsat HERA1995/96,Hamburg,eds.G.Ingelman,A.De Roeck,and R.Klanner, vol.1(1996)598.45.H.Jung,to be published in Proc.Madrid Workshop on Low x Physics,Mi-raﬂores de la Sierra,June1997.46.J.Kwiecinski,ng,and A.D.Martin,Phys.Rev.D55(1997)1273.47.J.Kwiecinski, C.A.M.Lewis,and A.D.Martin,DTP-97-58(1997)[hep-ph/9707375].48.J.Bartels,these proceedings.49.C.R.Schmidt,Phys.Rev.Lett.78(1997)4531.50.L.H.Orr and W.J.Stirling,DTP-97-48(1997)[hep-ph/9706529],to be pub-lished in Phys.Rev.D.。