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Length-dry mass relationships for a typical shredder in Brazilian streams (Trichoptera: Calamoceratidae)

September 2009
Aquatic Insects 31(3):227-234

DOI:10.1080/01650420902787549

Authors:

Bárbara Becker

Pontifical Catholic University of Minas Gerais

Marcelo S Moretti

Universidade Vila Velha

The aims of this study were to determine which linear body dimensions are best suitable and which mathematical functions can be used to describe length–dry mass relationships for a population of Phylloicus sp. (Trichoptera: Calamoceratidae) larvae. We measured three linear body dimensions (body length, head capsule width and interocular distance) of 54 larvae to use as dry mass predictors. For the description of length–dry mass relationships we used linear, exponential and power function models. Body length provided the best fitted equations to estimate biomass, followed by head capsule width and interocular distance. The highest coefficients of determination were found in power function and exponential models. These relationships can be useful to determine the growth rate and/or secondary production of Phylloicus larvae in future laboratory experiments, as well as to understand the importance of these shredders in the energy flux of shaded tropical streams.

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Length–dry mass relationships for a typical shredder in Brazilian

streams (Trichoptera: Calamoceratidae)

´rbara Becker, Marcelo S. Moretti and Marcos Callisto*

Universidade Federal de Minas Gerais, Instituto de Cie

ˆncias Biolo

´gicas, Departamento de

Biologia Geral, Laborato

´rio de Ecologia de Bentos, Belo Horizonte, MG, Brasil

(Received 29 June 2008; ﬁnal version received 15 December 2008)

The aims of this study were to determine which linear body dimensions are best

suitable and which mathematical functions can be used to describe length–dry

mass relationships for a population of Phylloicus sp. (Trichoptera: Calamocer-

atidae) larvae. We measured three linear body dimensions (body length, head

capsule width and interocular distance) of 54 larvae to use as dry mass predictors.

For the description of length–dry mass relationships we used linear, exponential

and power function models. Body length provided the best ﬁtted equations to

estimate biomass, followed by head capsule width and interocular distance. The

highest coeﬃcients of determination were found in power function and

exponential models. These relationships can be useful to determine the growth

rate and/or secondary production of Phylloicus larvae in future laboratory

experiments, as well as to understand the importance of these shredders in the

energy ﬂux of shaded tropical streams.

Keywords: size-mass equations; biomass estimation; linear body dimensions;

Phylloicus; tropical shredders

Introduction

Biomass of aquatic macroinvertebrates is important to determine growth rates and/

or secondary production, as well as to understand life histories, seasonal patterns

and trophic relationships between functional feeding groups (Benke 1996; Burgherr

and Meyer 1997). Data on macroinvertebrate biomass can also be useful in

colonisation studies or quantifying the role of detritivores on leaf decomposition

(Cressa 1999).

Among the diﬀerent approaches to biomass determination, the most common is

the direct weighing of individual specimens (Dermott and Paterson 1974; Smock

1980; Meyer 1989). However, this approach is often very time consuming, and prone

to error if the insects have been previously stored in chemical preservatives (e.g.

formalin or alcohol), which can cause alterations in their dry mass (Donald and

Paterson 1977; Downing and Rigler 1984; Kato and Miyasaka 2007). Direct

determination of dry mass has the added disadvantage of rendering the specimen

*Corresponding author. Email: callisto@icb.ufmg.br

Aquatic Insects

Vol. 31, No. 3, September 2009, 227–234

ISSN 0165-0424 print/ISSN 1744-4152 online

!2009 Taylor & Francis

DOI: 10.1080/01650420902787549

http://www.informaworld.com

Downloaded By: [Callisto, Marcos] At: 14:37 7 August 2009

useless for further examination as a result of the drying process (Towers, Henderson

and Veltman 1994).

An alternative to avoid such disadvantages is to estimate the biomass indirectly,

using length–dry mass conversions (Gould 1966; Peters 1983; Burgherr and Meyer

1997; Benke, Huryn, Smock and Wallace 1999). Estimating dry mass indirectly from

linear body dimensions (e.g. body length, head capsule width) is more rapid than

direct mass determination, particularly for small invertebrates. Moreover, in

laboratory experiments assessing invertebrate feeding behaviour, this approach allows

the estimation of initial biomass without stressing and/or killing the organisms.

Length–dry mass relationships have been used to estimate the biomass of

invertebrates from diﬀerent geographical locations and of taxa with similar body

shapes (Johnston and Cunjak 1999). Most of the length–dry mass relationships for

stream invertebrates were estimated for North American and European taxa (Smock

1980; Meyer 1989) and, until now, only a few data were proposed for the tropical

region. Furthermore, previous studies suggested the need to use taxa-speciﬁc

relationships because they are more precise, once diﬀerent taxa may diﬀer in body

shape and volume (Schoener 1980; Smock 1980; Gowing and Recher 1985; Cressa

1986).

Only few invertebrate taxa have been mentioned as shredders in neotropical

streams. Among them, larvae of the genus Phylloicus Mu

¨ller, 1880 (Trichoptera:

Calamoceratidae) are well distributed throughout Latin America and, in some

streams, can be found easily on leaf patches with low water current (Prather 2003).

Because these larvae are also easy to manipulate and keep alive in laboratory

conditions, they have been used in many experiments (e.g. feeding preference,

growth, survival and case building) that aimed to better understand the behaviour of

shredders and their inﬂuence on leaf decomposition in tropical streams (Grac¸ a et al.

2001; Rinco

´n and Martı

´nez 2006).

In this study, we analysed the length–dry mass relationships for a population

of Phylloicus sp. by using three diﬀerent regression functions (linear, power

and exponential) and three body dimensions in order to determine the best

relationship.

Materials and methods

Phylloicus sp. larvae were collected on July 2007 in Taboo

˜es spring (2080303800S–

4480300300W), located in the Serra do Rola Moc¸ a State Park, Minas Gerais State,

southeastern Brazil. The Taboo

˜es spring is inside a forest fragment, presenting a well

developed riparian area, which forms a closed canopy. Leaves fall throughout the

year and accumulate in the streambed.

Larvae were found visually, collected with a hand net, and taken to the

laboratory in an isothermic box with stream water. In the laboratory, undamaged

individuals of the same morphospecies were carefully removed from their cases and

placed individually in Petri dishes. Three linear body dimensions were chosen among

the most common used as biomass predictors: body length, head capsule width and

interocular distance (Meyer 1989). Body length (BL) was measured as the distance

from the anterior of the head to the posterior of the last abdominal segment. Head

capsule width (HW) was measured across the widest section of the head. Interocular

distance (ID) was measured as the minimum distance between eyes, parallel to head

width. Body dimensions were measured to the nearest 0.1 mm with a Zeiss dissecting

228 B. Becker et al.

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microscope ﬁtted with an ocular micrometer (magniﬁcation: 8 x for BL measure-

ments and 50 x for HW and ID measurements). Animals were then placed

individually in pre-weighed aluminium foils, dried at 608C for 48 h (Meyer 1989), left

to cool in a desiccator, and their dry mass (DM) was measured to the nearest 0.1 mg.

Three regression models were calculated for the three Phylloicus body

dimensions, using the method of least squares. The ﬁt of regression equations was

judged by the coeﬃcient of determination (r

), the signiﬁcance level (p, obtained

from regression ANOVA) and residual analysis. All statistical analyses were

performed based on Zar (1999).

Results

Body dimensions measures and dry weights of 54 larvae were used for statistical

analyses. Phylloicus dry mass presented the highest coeﬃcient of variation, with

values ranging from 1.3 to 26.6 mg (Table 1). Among body dimensions, body length

presented higher range (10.4–28.9 mm) and coeﬃcient of variation (Table 1).

The following regression models were chosen because they provided the best ﬁts.

Conversion of Phylloicus body dimensions to dry mass was determined by linear (1),

exponential (2) and power function (3) models or its logarithmic equivalents:

DM ¼aþb#Lð1Þ

DM ¼a#ebL in linear form:ln DM ¼ln aþb#Lð Þ ð2Þ

DM ¼a#Lbin linear form:ln DM ¼ln aþb#ln Lð Þ ð3Þ

where a/bare regression constants, DM is dry mass, Lis the linear body dimension

(BL, HW, ID) and eis a mathematical constant (Euler’s number: 2.718).

The parameters of Equations (1), (2) and (3) are listed in Table 2. All

body dimensions showed a very high level of signiﬁcance in the three models

(p50.01). Body length provided the best relationships to estimate biomass

(Table 2), followed by head capsule width and interocular distance. These

relationships were best ﬁtted by power function and exponential models that

presented very similar coeﬃcients of determination to each body dimension. Figure 1

shows the relations of dry mass as a function of body length, head capsule width and

interocular distance for Phylloicus larvae. The regression lines and curves were given

by power function.

Table 1. Ranges, mean, standard deviation (SD) and coeﬃcient of variation (CV, in

percentage) for body length, head capsule width, interocular distance (mm) and dry mass (mg)

of Phylloicus sp. larvae; n¼54. CV ¼(SD/mean)6100.

Range Mean SD CV

Body length 10.4–28.9 16.7 2.7 16.2

Head capsule width 0.8–1.5 1.3 0.2 14.0

Interocular distance 0.6–1.1 1.0 0.1 14.3

Dry mass 1.3–26.6 12.1 6.7 54.2

Aquatic Insects 229

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Discussion

Even though all relationships between body dimensions and biomass were highly

signiﬁcant, body length was the best predictor, explaining 75–76% of the variation in

mass. This linear body dimension is widely used for determining length–dry mass

relationships of aquatic invertebrates (e.g. Smock 1980; Towers et al. 1994; Burgherr

and Meyer 1997) mainly because it has a broader measuring range. Body length also

provides slightly higher coeﬃcients of determination than head capsule width and

interocular distance (Gonza

´lez, Basaguren and Pozo 2002).

Although body length usually gives the best relationships, some authors (see

Cressa 1999; Marchant and Hehir 1999; Gonza

´lez et al. 2002) prefer to use other

linear body dimensions, like head capsule width, case width, pronotum length or

tarsus length. This probably owes to the fact that, among other reasons, these

structures are sclerotised and less subject to distortion or breakage under

manipulation than body length. In addition, Becker (2005) found that pronotum

length is the best measurement to distinct larval instars of Agapetus fuscipes

(Trichoptera) in a German ﬁrst-order stream. In the present study, larvae were

measured on the same day they had been sampled. So, all measurements were done

on fresh, undamaged and completely stretched animals, which allowed a precise and

reliable determination of the three studied body dimensions.

The exponential and power function models did not diﬀer between the body

dimensions determined. Most authors found the highest ﬁt between body length and

dry mass when they use the power function model (e.g. Smock 1980; Meyer 1989;

Burgherr and Meyer 1997) but exponential regressions have also been used by

Dudgeon (1995) and Pera

´n, Velasco and Milla

´n (1999) for length–dry mass

relationships of Hydrocyphon (Coleoptera) and Caenis luctuosa (Ephemeroptera),

respectively. Wenzel, Meyer and Schwoerbel (1990) pointed out that diﬀerences

between the results obtained using diﬀerent regression models are low and they

decrease when a higher number of animals is used. Although power function is more

often used, the exponential model should not be discarded when looking for the best

ﬁt of length–dry mass relationships.

Table 2. Parameters (with 95% conﬁdence intervals) of the linear, exponential and power

function models for the relationship between a linear body dimension (L¼body length [BL],

head capsule width [HW] or interocular distance [ID], in mm) and dry mass (DM, in mg) of

Phylloicus sp. larvae.

Function Conversion a ln a b r

Linear BL.!DM 720.24 +3.44 1.93 +0.20 0.64**

DM ¼aþb#L HW.!DM 721.20 +4.58 26.49 +3.61 0.51**

ID.!DM 719.97 +4.62 33.51 +4.78 0.49**

Exponential BL.!DM 71.63 +0.32 0.23 +0.02 0.75*

ln DM ¼

ln a þb#L

HW.!DM 72.05 +0.40 3.45 +0.32 0.70**

ID.!DM 72.00 +0.39 4.48 +0.41 0.70**

Power BL.!DM 77.73 +0.77 3.58 +0.28 0.76*

ln DM ¼

ln a þb#ln L

HW.!DM 1.43 +0.09 3.95 +0.35 0.71**

ID.!DM 2.50 +0.06 3.84 +0.34 0.71**

a, b ¼regression constants, r

¼coeﬃcient of determination (*p50.01, **p50.001). n¼54.

230 B. Becker et al.

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In practice, when interpreting a length–dry mass regression equation, ‘‘b’’

values represent the rate of increase (i.e. slope) of dry weight against length in a

linear relationship, whereas the constant ‘‘a’’ only represents the dry mass of

an organism at a unit length (i.e. 1 mm). It is known that for tropical aquatic

insects the constant bfalls short of the expected value of 3, which means that

body mass of insects is more inﬂuenced by surface than by volume (Engelmann

1961). Our results support those from Cressa (1999) who found that Phylloicus

sp. is one of the few taxa of tropical invertebrates whose slope is higher than 3,

so it is possible that in this genus volume could inﬂuence body mass more than

surface.

Figure 1. Scatter diagrams of (A) dry mass versus body length, (B) head capsule width and

for Phylloicus sp. larvae. The regression equations (power function) are DM ¼a#L

and ln

DM ¼ln aþb#ln L.

Aquatic Insects 231

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Some variations in length–dry mass relationships for the populations of the

same species, but from diﬀerent locations, can be caused by physical–chemical

diﬀerences of the environment, trophic conditions or genetics. In this way, it is

recommended to determine the relationships for populations under study or use

relationships that were determined for populations from the same streams and/or

regions. For example, Rinco

´n and Martinez (2006), studying the growth rates of

Phylloicus in laboratory experiments, used the empirical relationship described by

Cressa (1999) who had studied populations from a similar region of Venezuela.

On the other hand, length–dry mass relationships are not much aﬀected by

seasons, as shown by Kato and Miyasaka (2007). These authors suggested that it

is not necessary to measure larvae in dry and wet seasons to have a consistent

relationship.

When sampling organisms to determine length–dry mass relationships, one

must be sure that organisms from diﬀerent sizes (cohorts) have been collected. If

not, only part of the logistic curve of population growth is quantiﬁed and the

resulting relationships may not represent the whole population (Begon, Mortimer

and Thompson 1996). In this study, if we consider Dyar’s law, an empirical law

that suggests an increase of 1.5 in growth at each instar (Wigglesworth 1972), and

the ranges of each body dimension measured, we can infer that only larvae from

the last two instars were sampled. Based on this, our equations were determined

with data from the right side of the curvilinear relationships between dry mass and

body dimensions of this population of Phylloicus (see Majecki, Grzybkowska and

Reddy 1997). On the other hand, as we have been monitoring this population for

several months, larvae used in this study presented the same range of size of the

ones that are found visually in most part of the year, suggesting that our equations

were adequate to determine the dry mass of larvae destined to laboratory

experiments.

In conclusion, the length–dry mass relationships presented here can be useful to

determine the growth rate and/or secondary production of Phylloicus. Besides, our

results also reinforce the necessity of more studies focusing on the life cycles of

aquatic insects in the tropical region. We do hope that the present study encourages

future research assessing the population dynamics of tropical shredders, as well as to

understand the importance of these individuals on leaf processing, trophic

relationships, colonisation rates, and even to compare populations within and

between habitats.

Acknowledgements

This study was supported by FAPEMIG, IEF-MG, CoPASA, CNPq, CAPES, Eawag, US Fish

and Wildlife Service. We appreciated the help of our laboratory colleagues Lurdemar Tavares

and Juliana Franc¸ a during ﬁeld and laboratory activities. We are also thankful to Joa

˜o Jose

Leal, Leandro Oliveira, Vicenc¸ Acun

˜a and two anonymous reviewers who provided useful

comments on the manuscript.

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AQUAT INSECT

Apatania crymophila McLachlan, 1880 is the most abundant species among trichopterans of the Yenisei River. The density of its free-moving larvae associated with water moss in the Yenisei River downstream of the high-pressure Krasnoyarsk Hydroelectric Plant dam was studied from June through November 2022. The biomass of A. crymophila larvae best correlated with case length, and the correlation was well fitted by linear equation; case length was also used to distinguish instars in this study. The abundance and biomass of A. crymophila larvae on water moss increased most rapidly (0.12 and 0.18day−1, respectively) from early July to early August, when water temperature approached its seasonal maximum. The maximum value of the larval density on water moss was reached in October (1084 larvae per kg of fresh moss). The relationship between larval growth and water temperature suggests that altered environmental conditions in the Yenisei River downstream of the HEP can be considered as a factor favoring the abundancy of A. crymophila.

Contrasting effects of agriculture and urban land use on macroinvertebrate secondary production in Neotropical streams

Article

Full-text available

Apr 2024
ECOL INDIC

We compared the structural and functional attributes of Neotropical macroinvertebrate communities between two natural, two agricultural, and two urban streams. We quantified food resource availability, community structure, secondary production, and consumer-resource interaction strength, attributing them to environmental characteristics. In agricultural streams, secondary production was significantly reduced compared to natural streams, reaching the lowest reported estimates for tropical streams (0.08-0.69 g DW⋅m − 2 ⋅year − 1 in agricultural streams vs. 1.1-15.8 g DW⋅m − 2 ⋅year − 1 in natural streams). This decline was primarily attributed to habitat degradation caused by siltation and channelization, alongside stronger top-down pressure in agricultural streams. Conversely, urban streams exhibited a substantial increase in secondary production, ranking among the highest estimates for tropical streams (25.6-191.2 g DW⋅m − 2 ⋅year − 1). The high secondary production in urban streams was primarily due to substantial increases in fine benthic organic matter, likely originating from poorly treated wastewater. Along with higher resource availability, we also observed a lack of, or insufficient, top-down control by macroinvertebrate predators or fish, which may have promoted higher secondary production in urban streams. This study is the first to quantify land use impacts on energy flows in stream communities in a region particularly threatened by land use change. Future studies should address multifunctional responses to land use changes in both the tropical and temperate realms to shed new light on how stream ecosystem functions in different biomes respond to human impacts. Our findings highlight the urgent need for effective management strategies tailored to address the environmental characteristics of tropical stream ecosystems.

Trichoptera Life Stages Present Distinct Responses to Environmental Conditions in Amazonian Streams

Article

Dec 2023
NEOTROP ENTOMOL

Biological communities have their biodiversity patterns affected by environmental, spatial, and biogeographic factors that vary from taxa to taxa, and often between life stages. This is especially true when there are differences in the habitat the species use in each of them. Individuals of the insect order Trichoptera are mostly aquatic in their larval stage and terrestrial in their adult stage, which may result in different behaviors and environmental requirements. Our goal was to evaluate the congruence between the larval and adult stages of Trichoptera in Amazonian streams regarding their abundance, richness, and assemblage composition. Additionally, we tried to identify the main environmental factors related to each life stage. For this, larvae and adults of Trichoptera were sampled in the same sites at 12 streams in the Caxiuanã National Forest, Pará state, Brazil. Adult assemblages had greater richness of genera and abundance of individuals than the larval ones, and there was no congruence in the genera composition between these life stages. Our results also showed that different environmental variables structured Trichoptera larvae and adults. Since the sampling of larvae and adults proved to be complementary in the studied streams, we advise that Trichoptera diversity surveys consider both life stages of these organisms.

Relaciones entre el peso seco y la longitud total de los géneros de invertebrados acuáticos Helobdella (Hirudinea: Glossiphoniidae) y Asellus (Crustacea: Asellidae) de un humedal andino de Colombia

Article

Full-text available

Oct 2017

Existen dificultades para determinar el peso de los macroinvertebrados y conocer así su importancia energética dentro de un ecosistema acuático. Por lo tanto, el objetivo de este estudio fue hallar relaciones matemáticas entre la longitud y la biomasa en dos géneros de invertebrados, representativos en el humedal Jaboque (Engativá) Bogotá D. C., Colombia, que faciliten hallar el peso de los individuos. Para ello, se realizaron cuatro muestreos desde abril de 2009 a enero de 2010. Se obtuvieron ecuaciones para estimar el peso seco a partir de medidas de la longitud total del cuerpo, para los géneros Helobdella y Asellus. Las relaciones halladas entre longitud total y peso seco fueron significativas y explicaron al menos el 69% de la varianza, expresada en los coeficientes de correlación (r2 = 0,69 y 0,85). Estos modelos permitirán calcular la biomasa para determinar el crecimiento y la producción secundaria de estos taxones en posteriores estudios de laboratorio o de campo. También podrían ayudar a conocer la importancia de estos organismos en el flujo de energía en los ecosistemas acuáticos, principalmente en los humedales andinos urbanos, donde son muy abundantes.

Biovolume of Naidinae and Pristininae (Clitellata: Oligochaeta) in neotropical environments

Article

Dec 2022
BIOLOGIA

Mass or volume estimators using body surface areas can be useful for environmental quality biomonitoring programs. We propose models of biovolume estimate through biometric information of Aulophorus, Dero, Nais and Pristina. The samples were collected in 51 freshwater systems in the state of São Paulo, between 2004 and 2016. Specific dimensions for each genus of 1,814 total animals were measured and individual biovolume was calculated. The conversion model was performed by linear regression analysis between the biovolume and the specific dimensions, then transformed into a power function, established by allometric law. The biovolume of Aulophorus and Dero can be estimated by the diameter of segment four (DIV), by the equation Be = 0.775DIV4.387 (adjusted r2 = 0.84). For Nais species, the biovolume can be estimated by the diameter of segment seven (DVII), by the equation Be = 0.913DVII1.6 (adjusted r2 = 0.59). For Pristina, the biovolume can be estimate by the diameter of segment eight (DVIII), by the equation Be = 0.875DVIII2.11 (adjusted r2 = 0.69). The application of these models can help us better understand population structure, secondary production and flow of matter and energy in neotropical environments.

Estimating Macroinvertebrate Biomass for Stream Ecosystem Assessments

Article

Full-text available

Mar 2022
Int J Environ Res Publ Health

We propose a field procedure for estimating the dry biomass of stream macroinvertebrates. Estimates are calculated using the mean values of the a and b regression coefficients from unpublished data and an extensive review of the relevant literature. The regression equation employed for calculating dry biomass is one that has been extensively used: Y = aXb, where Y = mg dry mass of an individual macroinvertebrate; X = mm total body length of an individual macroinvertebrate; a = intercept coefficient of the Y on X regression; and b = slope coefficient Y on X. The procedure was developed for use in the field, but dry mass estimates can also be made on preserved specimens. The case is made for presenting stream macroinvertebrate dry biomass data categorized by functional feeding groups (FFGs) and their component higher level taxa. The tables summarize the FFGs and their food resources, mean regression coefficients, dry biomass estimates for FFG-taxa by size and a comparison of their numerical-to-gravimetric surrogate FFG ratios to predict the stream environmental condition. A sizing template for rapidly sorting macroinvertebrates in the field is described. Thresholds for surrogate FFG ratios that directly predict measured stream ecosystem conditions are described.

Relations length-dry weight of nymphs Anacroneuria caraca Stark, 1995 and A. marta Zúñiga & Stark, 2002 (Plecoptera:Perlidae) from a neotropical mountain river

Article

Full-text available

Dec 2020

Yesely Hurtado-Borrer

Antecedentes: El estudio de la morfometría de los insectos acuáticos es importante para comprender algunos procesos ecológicos como la ganancia de la biomasa, el tiempo de desarrollo de una especie y la dinámica de las cohortes. En Colombia, no existen estudios sobre relaciones talla-peso seco a nivel de especie en ninfas de Anacroneuria. Objetivos: El objetivo de este trabajo fue analizar algunas características morfológicas de ninfas de Anacroneuria marta y A. caraca para determinar la eventual existencia de funciones lineales que expliquen la relación entre algunas dimensiones del cuerpo (la longitud total y el ancho de la cabeza) versus el peso seco. Métodos: Los organismos se recolectaron en zonas de rápidos y pozos del río Gaira (Sierra Nevada de Santa Marta, Colombia) entre octubre de 2014 y marzo del 2015. Las ninfas se identificaron a nivel de especie y las entidades taxonómicas se confirmaron mediante un análisis discriminante utilizando mediciones de diez variables morfológicas de las ninfas inmaduras. En algunos organismos se obtuvo el peso seco, el cual se correlacionó con medidas de longitud mediante regresiones lineales simples. Resultados: Las especies A. marta y A. caraca mostraron diferencias morfológicas estadísticamente significativas que permitieron confirmar estos taxones. El modelo potencial fue el que se ajustó mejor para mostrar las relaciones de la longitud total (LT) y el ancho de la cabeza (AC) con el peso seco (p<0.01). Conclusiones: Las relaciones entre las dimensiones corporales y el peso seco fueron altamente significativas, para A. marta el mejor ajuste fue con el AC y para A. caraca con la LT, con explicaciones del 86% y el 95% de la variación en la biomasa, respectivamente. Estas ecuaciones servirán como base para estudios de determinación de la biomasa en ninfas de Plecoptera.

Life history, secondary production and microdistribution of Hydrocyphon (Coleoptera: Scirtidae) in a tropical forest stream

Article

Full-text available

Jun 1995
Arch Hydrobiol

David Dudgeon

Population Ecology: A Unified Study of Animals and Plants

Book

Sep 2009

The Principles of Insect Physiology

Book

Jan 1982

V. B. Wigglesworth

I Development in the Egg.- References.- II The Integument.- Properties of the cuticle.- Formation and shedding of the cuticle.- References.- III Growth.- Moulting.- Metamorphosis.- Determination of characters during post-embryonic development.- Regeneration.- Diapause.- References.- IV Muscular System and Locomotion.- Anatomy and histology.- Physiological properties of insect muscles.- Locomotion.- References.- V Nervous and Endocrine Systems.- Nervous system.- Visceral nervous system.- Endocrine system.- References.- VI Sense Organs: Vision.- Compound eye.- Simple eyes.- References.- VII Sense Organs: Mechanical and Chemical Senses.- Mechanical senses.- Hearing.- Chemical senses.- Temperature and humidity.- References.- VIII Behaviour.- Kinesis and related phenomena.- Orientation.- Co-ordinated behaviour.- References.- IX Respiration.- Tracheal system.- Development of the tracheal system.- Transport of oxygen to the tracheal endings.- Elimination of carbon dioxide.- Respiration of aquatic insects.- Respiration of endoparasitic insects.- Respiratory function of the blood.- Regulation of respiratory movements.- References.- X The Circulatory System and Associated Tissues.- Circulatory system.- Haemolymph.- Haemocytes.- Pericardial cells and so-called 'nephrocytes'.- Fat body.- Oenocytes.- Light-producing organs.- References.- XI Digestion and Nutrition.- Fore-gut.- Peritrophic membrane.- Mid-gut.- Hind-gut.- Secretions of the alimentary canal.- Digestion of some skeletal and other substances of plants and animals.- The role of lower organisms in digestion.- Nutrition.- References.- XII Excretion.- Urine.- Intermediary nitrogen metabolism.- Malpighian tubes.- Histophysiology of the Malpighian tubes.- Accessory functions of Malpighian tubes.- Malpighian tubes during moulting and metamorphosis.- Cephalic excretory organs and intestinal excretion.- Storage excretion.- References.- XIII Metabolism.- Chemical transformations.- Some chemical products of insects.- Pigment metabolism.- Respiratory metabolism.- References.- XIV Water and Temperature.- Water relations.- Temperature relations.- References.- XV Reproductive System.- Female reproductive system.- Male reproductive system.- Mating, impregnation and fertilization.- Some factors controlling fertility and fecundity.- Special modes of reproduction.- Sex determination.- Transmission of symbiotic micro-organisms.- References.- Index of Authors.- General Index.

The relationship between body length parameters and dry mass in running water invertebrates

Article

Dec 1989
Arch Hydrobiol

Elisabeth I. Meyer

Morphometry and biomass determination of dominant mayfly larvae (Ephemeroptera) in running waters

Article

Mar 1990
Arch Hydrobiol

Regression analysis of linear body dimensions vs. Dry mass in stream macroinvertebrates

Article

Apr 1997
Arch Hydrobiol

The regression equations for predicting dry mass from linear body dimensions presented in this study allow to calculate biomass of benthic macroinvertebrates from mountain streams of Central Europe. For the description of length-dry mass relationships, the power function y = a · xb or in a few cases the quadratic function y = a + b · x + c · x2 proved to be the best models. The relationships between linear body dimensions - e.g. body length (BL) vs. head capsule width (HW) - followed a simple linear model of the type y = a · x + b or again a quadratic one. Data of literature imply that the relationships derived from this study should be restricted to carbonate streams.

Secondary production of macroinvertebrates

Chapter