10 Water Hyacinth Biomass Valuation Using Emergy Luz S. Buller, Enrique Ortega, Ivan Bergier ABSTRACT The water hyacinth (Eicchornia spp), characterized by elevated growth rates, is a native aquatic weed in the Pantanal and represents the main species in aquatic floating mats that are carried by the Paraguay River according to the wetland flood pulse dynamics. The floating mats have a role in nutrient cycling to consumers of detritivorous food webs, such as typical fish of the region. Nonetheless there are potentials of using water hyacinth biomass to produce biofuels and biomaterials through biomass conversion techniques like anaerobic digestion and pyrolysis. Biomass growth of water hyacinth was modeled in the floodplain of the Upper Paraguay River basin to identify the underlying dynamics by means of emergy analysis. Emergy modeling has permitted to obtain monthly unit emergy values useful to evaluate the viability of water hyacinth biomass use in phase with the flood pulse of the Pantanal. The emdollar per kilogram of biomass ranging from 0.01 to 0.86 could be applied to give a value to water hyacinth biomass usually considered as free in the nature. This approach can be useful to establish environmental compensation policies to ensure the long term sustainable development for a local biomass-to-products economy.

INTRODUCTION Water hyacinth (Eicchornia crassipes and E. azurea) is an aquatic floating macrophyte dominant in Pantanal; it reaches 70% (Castro et al., 2010) of the aquatic vegetation. Pantanal, a major wetland in Central South America, is located on the Upper Paraguay River basin. Water hyacinth is distributed over the riverine lagoons (locally known as baías), the riverbanks and is also found as free floating mats flowing in the Paraguay River. The elevated growth rates and fast dispersion in natural and constructed wetlands made this aquatic weed a problem in many regions of the world and, thereafter, intense research on water hyacinth biomass for energy production was done in the last decades (Gunnarsson and Petersen, 2005). A management strategy is desirable to use the excess of water hyacinth biomass in beneficial ways including technical, economic and social aspects (Malik, 2007). Water hyacinth biomass sustainably managed in natural ecosystems could be a biomass resource for biofuels, mitigating energy costs and greenhouse gas emissions associated to fossil fuels (Bhattacharya and Kumar, 2010). Due to the incentive for renewable energy as a strategy to mitigate greenhouse gas emissions from fossil fuels, there is a real potential of using the excess of water hyacinth biomass in Pantanal to produce biofuels and biomaterials (Bergier and Salis, 2011). The present proposal of this paper concerning the biomass management in Pantanal is based on a fractional exploitation of the riverine outflow of macrophyte as free floating mats. Such exploitation must consider mechanisms for continuous assessment of environmental and socioeconomic activities (Bergier et al., 2012). In order to assure an embracing sustainable concept, some ecological features related to water hyacinth seasonality were studied and modeled. The seasonal availability of water hyacinth biomass was considered to ensure that biomass shortage is contemplated in the calculations presented in this article and, also, to properly consider its influence in ecological, social and economic aspects. Because of the annual flood pulse (aquatic and terrestrial phases) and inter-annual variability, Pantanal is characterized by a marked fluctuations in water flow and nutrient recycling in the 79   

wateershed; the peaak of riverine water w hyacinth h mats flow occcurs between March and Auugust (Bergier et all., 2012). The fractional harv vest of floating g mats aims too preserve any ecological funnctions related to aquatic weeds role r in the Pan ntanal food web b. It is importaant to concentrrate harvestingg efforts in the peak k season, wheere floating mats m availabilitty is higher inn order to avvoid downstreaam ecological distu urbance, if any y. Another beneefit related to the t harvest in thhe peak seasonn is the econom mies of scale. This paper deals with emerg gy accounting to t obtain monthhly unit emerggy values in useeful to valuate natu ural resource efficiency e nam mely water hyaacinth biomasss valuation in Pantanal aiminng to provide usefful and importtant informatio on for the stak keholders. The importance too have a valuee for a natural reso ource such as water hyacintth is the appliiance of the hholistic sustainnability concept integrating ecollogical aspects in the accountting method. A natural resouurce value is ann indispensablee input for the conv version techno ology assessmeent needed forr a project of biomass to biioenergy produuction. Water hyaccinth biomass valuation is a starting pointt to evaluate thhe ecological eefficiency of thhis weed as a reso ource for bioen nergy. Also, a natural resou urce ecologicaal valuation coould support eenvironmental com mpensation poliicies to rule thee biomass exploitation.

MA ATERIAL AND A METH HODS  

Stu udy Area an nd Water Hy yacinth Biomass Quanttification The floodplaiin of the Upp per Paraguay River R was bouunded by Souuza et al. (20111) aiming to iden ntify regions where w aquatic vegetation v is deenser and perm manently presennt on the coursse of 17 years in th he area, Figure 1. Based on a previous p remote sensing evalluation of aquaatic weeds occcupation durinng 17 years in Panttanal (Souza ett al., 2011) and d aquatic weed floating mats density measuured in field (V Vianna et al.,

 

Figu ure 1. Topograph hic gradient of the t Pantanal wettland measured w with NASA/SRTM TM (Shuttle Radaar Topography Misssion); the area outlined o with a da ashed line correesponds to the rivver floodplain inn 100 to 125 metters asl (above sea level) l in Brazil.  80   

2010), Buller (201 12) has estimatted that the tottal biomass prooduced in the Upper Paraguay floodplain, Figu ure 1, may be in i the range of4 f4.8 x 1010 to 1..7 x 1011 kg off dry biomass ddepending on thhe flood pulse mag gnitude that ch haracterizes a dry or a wet year. y Based onn data collecteed in the Paraaguay river in Coru umbá (Ramirees, 1993) and weekly w videogrraphic data anaalysis (Viannaa et al., 2010), Buller (2012) estim mated that the riverine outflo ow of macroph hyte mats may lie in betweenn 5.3 x 108 to 1.2 x 109 kg of dry biomass. This outflow of flo oating mats rep presents roughlly 1 to 2% of tthe total biomaass production in th he Upper Parag guay floodplain n. The inundatio on regime in Pantanal P showss a complex tim me-space dynaamics related tto fluctuations in flood f amplitud de, extension and a duration. Different biom mass productioon in dry andd wet years is obseerved due to the t flood pulsee and nutrientt inputs in thee system. The coefficient off variation for biom mass productio on, considering the 17 yearrs data for weeed occupationn, is 37%. Thhe calculation conssidered the meean and the stan ndard deviation between a loower flood cut--off (dry year)) and an upper floo od cut-off (wet year).

Sysstem Diagra am and Biom mass Growtth Model The system diagram d built with w emergy laanguage symb ols, Figure 2, shows energyy and material flow ws (natural inp puts) that prom mote the vegetaation growth w with the internnal relations annd the outputs conssidered for thiss study. The main m nutrient cy ycling mechaniism in Pantanaal is heterotrophhic (Hamilton et al., 1997). Biom mass decomposition and its related r food w web, including the regional bbiodiversity in Panttanal, are partiially representeed in Figure 2. 2 Weed tissuess and phytoplaankton are the main detritus sourrces in aquatic sediment and during the deccomposition prrocesses methan ane is producedd by anaerobic meth hanogens (Marrinho et al., 20 009; Bianchini Jr. et al., 20100). Methane cyycling was not considered in the following mod deling and emeergy accountin ng because metthanogenesis is intense in thhe growth area and less intense in n the fraction of o biomass that forms the floaating mats; thee inclusion of m methane in the diag gram was done to demonstratte the recognition of its imporrtance and rolee in the study reegion.

 

Figu ure 2. System dia agram of aquaticc vegetation biom mass growth * [[*The box corressponds to the sysstem limits, solid d lines correspon nd to storages an nd interrelationss that were consiidered in this stuudy, the dashed lines indicate otheer existing storag ges and interrela ations and the thinner dashed linnes indicate the ddegraded energyy.]

81   

Fish hery is regionaally important to the econom my hence it waas included in the diagram aand for further emeergy accounting g of labor efforrts. Before the em mergy accountin ng, a differentiial equation moodel was develloped to simulate the annual seassonality of biom mass growth an nd the averagee monthly quanntities. The moodel also allow wed simulating the quantification and understan nding of water hyacinth’s rolle in phosphorrous cycling inn the bounded areaa. Phosphorouss was chosen because b it is ussually related iin scientific litterature as the main limiting nutrrient in tropicall aquatic enviro onment (Esteves, 1988). Figure 3 preseents the state variables, v the energy e and matterial inflows aand outflows aand the related coeffficients consid dered to simullate biomass growth g and phoosphorous cyccling. The set oof differential equaations to repreesent the increemental chang ges in the statte variables naamely biomasss growth (Q), phosphorous (P) and a detritus fro om senescent biomass b (D) annd its related ccoefficients aree presented in Table 1. The values fo or flows and in nitial storages are presented in Table 2. A brief descripttion of values assignment is pressented here (th he complete deescription of vvalues assignm ments can be foound in Buller (201 12)). Solar eneergy flow (J0) and albedo (R R) were obtain ed to the studyy area in EOS SWEB on-line softw ware developeed by NASA (eosweb.larc.na ( asa.gov). Biom mass flow (J1) is the averagee between the max ximum and thee minimum quaantities of biom mass in the boounded area. D Detrital producction flow (J2) was established ass 35% of biom mass flow based on Mitsch (11975). The floow of biomass consumed by herb bivores (J3) was considered as 10% of biiomass flow bbased on Frannceschini et al. (2010). The biom mass flow corrrespondent to phosphorous p feedback f to thee water colum mn (J4) is propoortional to the biom mass quantity converted c into detritus; it waas calculated baased on the esttimate that 70% % of the water hyaccinth tissues phosphorous p co ontent returns to the system m by lixiviationn. Phosphorouus consumers’ feed dback to the waater column flo ow (J5) was ap pproximated ovver reptiles’ phhosphorous exccreta contents. Initiial biomass sto ock (Q1) corressponds to the minimum m quanntity observed in the system.. Phosphorous initiial stock (P) an nd phosphorouss seasonal quan ntities were obbtained from lim mnological datta of Paraguay river and its tributaaries. System steady y state conditiion values werre used to obttain the differeential equationns coefficients that were adjusteed to satisfy the t phosphoro ous content inn water hyacinnth tissues. Calculated and calib brated coefficiients are presen nted in Table 3. 3 The model developed is aan important siimulation tool to an nalyze weeds biomass b producction, mats flow w and phosphoorous stocks. A Additional tempporal data

Figure 3. Wateer hyacinth grow wth and nutrient removal r model. 82   

 

Table 1. Differential equations. State variable Inflows Q1 (Water hyacinth k1*R*P biomass) D (Detritus composed k2*Q1 of senescent biomass) P (Phosphorous in P1, k4*D e water column) k5*C

Outflows k2*Q1 k3*Q1 k4*D

Coefficients k1, k2 e k3

Differential equations dQ1/dt= k1*R*P - k2*Q1 - k3*Q1

k 2 e k4

dD/dt = k2*Q1 - k4*D

k1*R*P

k1, k4 e k5

dP/dt = P1 + k4*D + k5*C - k1*R*P

Table 2. Initial flows and storages. Flows and storages J0 R = J0/(1+k0 * P) J1 = k1 * R * P J2 = k2 * Q1 J3 = k3 * Q1 J4 = k4 * D J5 = k5 * C Q1 P D C

Description Solar energy Albedo Water hyacinth biomass produced Biomass converted into detritus Biomass consumed Biomass quantity that contributes to Consumers Phosphorous cycling Water hyacinth biomass storage Total Phosphorous storage in water Detritus initial storage Consumers biomass storage

Value Unit 100 % 6% 8.00E+09 kg dry matter of hyacinth month-1 2.80E+09 kg dry matter of hyacinth month-1 8.00E+08 kg dry matter of hyacinth month-1 1.96E+09 kg dry matter of hyacinth month-1 12.80 kg P month-1 4.07E+09 kg dry matter of hyacinth 2.30E+05 kg P 0 kg detritus 2.54E+06 kg fresh matter

Table 3. Model coefficients. CoDescription efficient Coefficient related to solar energy use k0 Coefficient related to biomass production k1 Coefficient related to biomass conversion in detritus k2 Coefficient related to biomass consumption k3 Coefficient related to P cycling from detritus k4 Coefficient related toP cycling from consumer metabolism k5

Equation

Calculated Calibration value adjusted value

k0 = J0/(R*P) k1 = J1/(R*P) k2 = J2/Q1 k3 = J3/Q1 k4 = J4/D k5 = J5/C

0.06808 31000 0.68730 0.19637 0 0.00001

0.05000 ---------0.35000 0.10000 0.70000 ------------

regarding phosphorous dynamics in the ecosystem are useful to better approximate the model. Nonetheless, the simulation herein shown is a reasonable approach to the knowledge and understanding of the water hyacinth and phosphorous stocks seasonality in the studied flooding environment.

Emergy Accounting The model previously developed and described was applied to simulate water hyacinth growth and phosphorous removal to obtain monthly and mean energy and material flows of water hyacinth biomass and phosphorous stocks in the dry and wet seasons in the bounded area in order to perform the emergy accounting. As the production of water hyacinth biomass is a natural process taking place in the Pantanal ecosystem, natural resources inflows were accounted and divided in atmospheric inputs (solar energy, wind, rain and earth heat flow) and hydrographic basin inputs (phosphorous and water flows). The usual procedure that considers only the highest emergy inputs among the natural resources flows was adopted here to avoid double accounting of nature’s contributions. The inflows considered here for the emergy accounting are chemical potential of rain and phosphorous input. To the accounting of fishery efforts performed in the study regions, the labor flows were accounted. A distinction between professional and sporting fishery was done because of the significant differences in biomass of fishes collected, time devoted to the activity and its related costs. The outputs of interest considered here are water hyacinth biomass, biomass of fish collected in the study region and the flow of “cleaned” water (cleaned here means with less nutrients as a result of aquatic weeds acting as water 83   

filters) selected among other outflows related to the Pantanal ecosystem functions. Here, the outputs were accounted and measured as a result of the proportional inflows designated to the products or services considered. The proportionality factor was established based on energy allocation calculated through the calorific value of the outputs. This procedure for calculating co-products transformities follows the energy-based allocation method proposed by Kamp and Østergård (2013). In order to obtain the average monthly emergy values, data for each flow was calculated based upon their respective equation listed below. Data from ANA (acronym for Brazilian National Waters Agency) has been used for acquiring average monthly rainfall. The equation used to obtain the monthly biomass quantities, considering its seasonal behavior, dependent on the monomodal flood pulse, is: Q(t) = Qaverage + amplitude * sin(6.28 t / period)

(Eq. 1),

where: Q is the biomass quantity; t is the number of months; amplitude is the variation of biomass against its average, and; period is the total number of months. Similarly, the equation for seasonal phosphorous loading is: P(t) = Paverage + amplitude * sin(6.28 t / period)

(Eq. 2),

where: P is the phosphorous loading; t is the number of months; amplitude is the variation of P against its average, and; period is the total number of months. The rain emergy flow corresponds to the sum of the monthly rain emergy flows, Erain, calculated as considering the area of the study region and the unit emergy value of the rain, TRrain (transformity of the rain), according to the equation 3: Erain = Rain emergy flow = ∑ (Raint * area * G * water density * TRrain) (Eq. 3), where: G is the Gibbs free energy of water. The phosphorous emergy flow is obtained by the sum of monthly P emergy flows considering the correspondent unit emergy value, TRphosphorous (transformity of Phosphorous): Ephosphorous = Phosphorous emergy flow = ∑ (Phosphoroust * TRphosphorous)

(Eq. 4).

The biomass emergy flow is obtained by the sum of monthly emergy flows for rain and P loading considering energy use factors (based on energy) according to equation 5: Ebiomass = Biomass emergy flow = ∑ [(Erain (t) + Ephosphorous (t)) * %Energy Use] (Eq. 5). At last, monthly unit emergy values for the biomass produced in the Paraguay river flood plain are obtained by the definitions (Odum, 1996; Brown and Ulgiati, 2004) according to equations 6 to 8: Specific Emergybiomass (t) = Ebiomass /Q (t) [=] seJ/kg (Eq. 6), Transformitybiomass (t) = Specific Emergybiomass (t)/Energy value [=] seJ/J (Eq. 7), Emergetic Dollars biomass (t)/kg = (seJ/g) / (seJ/GNP) [=] EM$/kg (Eq. 8), where: energy value is the correspondent value of calorific content of the biomass, and; GNP is the gross national product.

84   

RESULTS Energy inputs, their respective flows, UEVs for the conversion, emergy flows for the mean behavior of the system, and mean outflows and its respective emergy flows are presented in Table 4. All the calculation procedures and assumptions associated to inflows and outflows values are shown in the Appendix. Figure 4 illustrates the emergy flows of Table 4. Mean UEVs obtained for a year scale for the system are presented in Table 5. The water hyacinth transformity obtained was compared to scientific values reported for other wetlands. The magnitude of the transformity for this work is comparable to these previously reported values. Refer to Table 6. The water hyacinth transformity obtained here is smaller than the other scientific transformities. This can be explained observing that the biomass growth in this region requires less nature’s effort (the region is plentiful of solar radiation and has availability of nutrients, in special P). Monthly emergy flows for rainfall, phosphorous and biomass for dry years and wet years were calculated using equations 1 to 8. Refer to Table 7. Applying the same procedure for dry and wet years (respectively, minimum and maximum biomass production) a compilation of monthly UEVs obtained for dry and wet years is shown in Table 8. Monthly water hyacinth biomass transformity and EM$ kg-1 values are presented in Figure 5. UEVs were calculated with a coefficient of variation of 37% that Table 4. Emergy table. Description

Flow

Unit

UEV

Ref.

(seJ unit-1)

Emergy (seJ year-1)

Inflows Renewable natural resources - R Atmospheric inputs R1 R2 R3 R4 R5

Solar energy Wind, kinetic energy Rain, chemical potential Rain, potential energy Earth heat flow

R7 R8

Phosphorous (flood pulse + river) Water flow, chemical potential Water flow, potential energy

Professional fishermen Sport fishermen

Outflows

P1

Aquatic vegetation biomass

Odum, 1996 Odum, 1996

1.40E+20 3.07E+21

5 0.1 2.2

1.19E+07 2.60E+08

1.19E+17 J year-1

3.06E+04

Odum, 1996

3.63E+21

2.6

3.08E+08

6.59E+15 J year-1 2.24E+13 J year-1

1.76E+04 5.76E+04

Odum, 1996 Odum, 1996

1.16E+20 1.29E+18

0.1 0.001 95.0

9.84E+06 1.09E+05

2.63E+06 Kg year-1

4.87E+16

Brandt1.28E+23 Williams, 2000

92.5

1.09E+10

1.96E+16 J year-1

8.14E+04

Odum, 1996

1.60E+21

1.2

1.35E+08

4.08E+16 J year-1

4.68E+04

Odum, 1996

1.91E+21

1.4

1.62E+08

7.41E+10 J year-1 6.69E+11 J year-1

Flow

7.68E+10

P2a Professional fishing

8.31E+04

P2b Sport fishing

2.21E+05

P3

4.08E+13

Water

Unit

kg dry mass year-1 kg wet mass year-1 kg wet mass year-1 kg year-1

3.72E+08 1.22E+08

1.32E+23

1.12E+10 100

Calculated Calculated

2.76E+19 8.19E+19

Energy

Energy

Emergy Emergy Energy use allocation allocation factor in Energy in Energy basis basis

(J kg-1)

(J year-1)

(%)

(seJ year-1) (Em$ year-1)

1.41E+07

1.08E+18

13.53

1.78E+22

1.51E+09

2.09E+07

1.74E+12

0.00002

2.76E+19

2.34E+06

2.09E+07

4.36E+12

0.00006

8.20E+19

6.95E+06

1.69E+05

6.91E+18

86.47

1.14E+23

9.65E+09

85   

(Em$ year-1)

1.00E+00 2.51E+03

Sum of major contributions: chemical potential of rain and phosphorous input Economy services -S S1 S2

Emergy

1.40E+20 J year-1 1.22E+18 J year-1

Basin inputs R6

%

25.2 74.8

2.34E+06 6.94E+06

 

Figu ure 4. Emergy flo ows.  

conssiders the meaan and the stan ndard deviation n between a low wer flood cut--off (dry year) and an upper floo od cut-off (wet year). These th hresholds are presented p in thhe emergetic vaalues graph onn the right side of Figure F 5. Other than th he appliance of o the biomasss growth modeel to obtain seasonal quantiities of water hyaccinth biomass, the simulatio on model allo ows the underrstanding of pphosphorous ccycling in the boun nded area. In Figure F 6 it is possible to verify three distincct fractions of phosphorous sstocks derived from m the biomass growth model described befo fore. Phosphoroous (henceforthh referred to as P) dissolved in th he wetland watter column is th he P fraction th hat is not impllicated in aquattic vegetation ggrowth or any otheer biogeochemiical processes in the bounded d area. P retainned in the wetland is the fracttion related to aquaatic vegetation n, senescent biomass b detrittus productionn, food web biomass conssumption and deco omposers recy ycling. P exp ported by aqu uatic macrophhyte corresponnds to the ffraction of P imm mobilized in waater hyacinth flloating mats th hat detach and fflow downstreaam the wetlandd.

DIS SCUSSION N The curves off the variation of o water hyacin nth biomass UE EVs, Figure 5,, indicate that, for the period wheen the environ nmental conditiions are not favorable, f i.e. lower nutrientt availability tto the aquatic vegeetation growth, the transform mity and EM$ kg k -1 values are tthe highest oveer the year. -1 In special, EM$ kg k is very high h in the period d from Novemb mber to March, that also correesponds to the lower production level of aquatic vegetation biomass. b Durinng this period,, inspite of thee total rainfall that affects the bassin in the north h (upstream of the study regioon), the nutriennt concentratioon in the water colu umn is lower th han in other seaasons. This pheenomenon occuurs by virtue oof the seasonal flood pulse in the middle portion n of the basin that is 3 to 4 months laggedd from highlannd (upstream) rainfall. As a t nutrrient recycling is out of phasse with respecct to the rainy conssequence, the flooding and terrestrial seasson in the boun nded area of stu udy. Aquatic weed ds floating maats take part on the predom minant heterootrophic nutrient cycling of detrritivorous species since theirr decompositio on is very impportant in the nnutrient budgeet of wetlands duriing the aquaticc and terrestriial phases of the t hydrologic cycle (Piedaade et al., 2010). Because of the heterotrophic characteristicss of tropical wetlands, inteernal nutrient cycling is afffected by the seassonal pulse (Pieedade et al., 20 010; Affonso ett al., 2011). 86   

Table 5. Mean UEVs. Outputs Water hyacinth Collected fishes –professional Collected fishes –sport Water

Unit emergy value Specific emergy (seJ kg-1) Transformity (seJ J-1) 2.32E+12 1.65E+04 3.32E+14 1.59E+07 3.70E+14 1.77E+07 5.65E+05

Em$ per 1000 kg 19.66 28155.66 31374.90 0.21

Table 6. Comparison of the magnitude of biomass transformity and other scientific values. Study site Pantanal - bounded area - this work Tropical dry savanna Tropical mangroves Subtropical herbaceous wetland Subtropical shrub-scrub wetland (titi and willow dominated) Subtropical depressional forested wetland

Water hyacinth biomass Savanna biomass Biomass growth Live biomass Live biomass

Value 1.65E+04 1.76E+04 2.47E+04 1.23E+05 1.16E+05

Unit Reference seJ J-1 This work seJ J-1 PradoJatar & Brown, 1997 seJ J-1 Odum and Arding, 1991 seJ J-1 Bardi and Brown, 2001 seJ J-1 Bardi and Brown, 2001

Live biomass

1.23E+05 seJ J-1

Bardi and Brown, 2001

Table 7. Mean seasonal flows and UEVs Phosphorous flow

Rain flow

Inputs Flow Flood pulse Emergy Emergy (seJ input(kgP Flow Rainfall Flow -1 month-1) (seJ month-1) (m month-1) (seJ month-1) month ) Jan 8.88E+04 4.33E+21 0.192 5.21E+20 6.56E+20 Feb 1.74E+05 8.48E+21 0.158 4.29E+20 1.21E+21 Mar 2.77E+05 1.35E+22 0.112 3.04E+20 1.87E+21 Apr 3.65E+05 1.78E+22 0.066 1.78E+20 2.43E+21 May 4.11E+05 2.00E+22 0.032 8.59E+19 2.72E+21 Jun 4.01E+05 1.95E+22 0.019 5.16E+19 2.65E+21 Jul 3.37E+05 1.64E+22 0.031 8.45E+19 2.23E+21 Aug 2.40E+05 1.17E+22 0.065 1.76E+20 1.60E+21 Sep 1.40E+05 6.81E+21 0.111 3.01E+20 9.62E+20 Oct 6.79E+04 3.31E+21 0.157 4.27E+20 5.06E+20 Nov 4.67E+04 2.28E+21 0.191 5.19E+20 3.78E+20 Dec 8.28E+04 4.03E+21 0.204 5.54E+20 6.20E+20

Biomass UEVs produced (kg dry Specific Transmatter emergy formity month-1) (seJ kg-1) (seJ J-1) 9.34E+08 7.02E+11 4.99E+04 3.23E+09 3.73E+11 2.65E+04 6.38E+09 2.92E+11 2.08E+04 9.53E+09 2.55E+11 1.81E+04 1.18E+10 2.30E+11 1.63E+04 1.27E+10 2.08E+11 1.48E+04 1.19E+10 1.88E+11 1.33E+04 9.58E+09 1.68E+11 1.19E+04 6.43E+09 1.50E+11 1.06E+04 3.28E+09 1.54E+11 1.10E+04 9.59E+08 3.94E+11 2.80E+04 9.81E+07 6.32E+12 4.49E+05

EM$ kg-1 0.060 0.032 0.025 0.022 0.019 0.018 0.016 0.014 0.013 0.013 0.033 0.536

The Paraguay river level steadily increases from December to July and when it reaches a certain geomorphological threshold in the bounded region shown in Figure 1, the water invades the terrestrial ecosystem in the floodplain. At this time several bacterial-mediated reactions take place making nutrients available to the water column and to the aquatic vegetation growth (Piedade et al., 2010). When river level is falling (locally know as “vazante”) usually from August to November/December the process is reversed; a fraction of the aquatic vegetation dies in the dried flood plains and, in turn, makes nutrients available to the terrestrial vegetation regrowth. The retraction of the flooded areas makes the total quantity of aquatic vegetation biomass much lower when compared to a well-developed flood. The total growth and spread of the aquatic vegetation is therefore related to the flood pulse intensity (days) and magnitude (height) that characterize drier or wetter years and triggers ecological processes in the annual cycle between the aquatic and the terrestrial phase (Schöngart and Junk, 2007). As can be observed in Figure 6, during the flood season, from December to July, a significant fraction of P is retained in the wetland by internal nutrient cycling and assimilation by aquatic vegetation growth and expansion. At the “vazante” period, from August to November, the opposite is observed; the major fraction of P is dissolved in the wetland water column and retained in the drained floodland. 87   

Tab ble 8. Dry and wet w years mon nthly UEVs. Dry yearr Q(t) Specific (kg dry matterr emergy (seJ kg-1) month-1)

Jan Feb Marr Aprr May y Jun Jul Aug g Sep Oct Nov v Decc

5.85E+08 8 2.03E+09 9 4.00E+09 9 5.97E+09 9 7.42E+09 9 7.96E+09 9 7.44E+09 9 6.00E+09 9 4.03E+09 9 2.05E+09 9 6.01E+08 8 6.15E+07 7

1.12E+12 5.95E+11 4.67E+11 4.07E+11 3.66E+11 3.33E+11 3.00E+11 2.67E+11 2.39E+11 2.46E+11 6.29E+11 1.01E+13

W Wet year

Trransformity EM M$ kg-1 (seJ J-1)

7.96E+04 4.22E+04 3.31E+04 2.89E+04 2.60E+04 2.36E+04 2.13E+04 1.90E+04 1.70E+04 1.75E+04 4.47E+04 7.17E+05

Q(t)) Specificc Transformityy EM$ kg-1 (kg dry m matter emergy (seJ kg-1) (seJ J-1) month -1)

0.095 0.050 0.040 0.034 0.031 0.028 0.025 0.023 0.020 0.021 0.053 0.855

1.28E E+09 4.44E E+09 8.76E E+09 1.31E E+10 1.63E E+10 1.74E E+10 1.63E E+10 1.32E E+10 8.83E E+09 4.50E E+09 1.32E E+09 1.35E E+08

5.11E+111 2.71E+111 2.13E+111 1.86E+111 1.67E+111 1.52E+111 1.37E+111 1.22E+111 1.09E+111 1.12E+111 2.87E+111 4.61E+112

3.63E+044 1.93E+044 1.51E+044 1.32E+044 1.19E+044 1.08E+044 9.72E+03 8.66E+03 7.74E+03 7.98E+03 2.04E+044 3.27E+05

0.043 0.023 0.018 0.016 0.014 0.013 0.012 0.010 0.009 0.010 0.024 0.390

The amount of P incorporaated in free flloating mats tthat travels doownstream the wetland is a mod dest fraction off the total P in the system at any time of thee year. This m means that the eexploitation of a fraaction of the riverine r outflow w of macrophy yte mats from the Pantanal is not supposeed to suppress sign nificant amoun nts of nutrients used in primaary productionn at any area oof the Pantanall downstream. Mosst of the P to th he La Plata bassin is therefore provided by thhe P dissolved fraction in thee river water. Buller (2012) has indicated that the harveest level is posssible in the raange of 1 to 400% of the free floaating mats, dep pending upon the t scalability of the biorefinnery design: a single large uunit or several smaall units along the Paraguay River R course in n the La Plata Basin. The jooint analysis off UEVs and P stoccks allowed thee evaluation of o water hyacin nth biomass haarvesting from m the system eecological and econ nomic behavio ors. UEVs variaation along thee year and in thhe drier and weetter years is ddirectly related to th he flood pulse dynamics abov ve described. The T fractional exploitation off floating matss should occur duriing the higherr production leevel of aquaticc vegetation bbiomass whichh takes place ffrom April to Aug gust and corressponds to the lower UEVs. Also, the quaantities that coould be harvestted should be deteermined accord ding to the low wer and upper thresholds forr drier and wettter years to aassure the best ecollogical and eco onomic perform mance.

  Figu ure 5. Water hya acinth biomass seeasonal UEVs. 88   

 

ure 6. Phosphoro ous seasonal fra actions. Figu

CO ONCLUSIONS Mean UEVs of o water hyacinth vary along g the year and depend on thee magnitude annd duration of the seasonal flood d pulse that ch haracterizes dry y and wet yearrs. Regarding the EM$ kg-1 the minimum valu ue is around 0.0 01 for wetter years y and 0.02 for drier years . The use of w water hyacinth bbiomass is not reco ommended in the austral su ummer (Decem mber to Marchh) when its vaalue significanntly increases, reacching 0.39 EM M$ kg-1 of biom mass in wetter years y and 0.866 in drier yearss and biomass quantity (free floaating mats) is lo ower. Monthly EM$ $ kg-1 obtained for the loweer and upper thresholds forr drier and weetter years are read dily applicable to give econom mic values forr water hyacintth biomass connsidering the nature’s efforts invo olved in its pro oduction. Thesee values, in turrn, are useful too evaluate the economic viabbility of water hyaccinth biomass usage accordiing to the flood dynamics off the wetland. Also, the sim mulation of the seassonal emergy evaluation e of water w hyacinth h biomass is a useful tool foor supporting eenvironmental com mpensation focu used on fossill reductions in n the energy seector. Also, tthe new econoomy based on locaally developed d biomass indu ustry can creatte social incluusion by improoving city servvices and job creaation. The valu uation of naturaal resource effficiency, like thhe one presentted here, is useeful for social poliicies formulatio on to ensure th he long term sustainable s devvelopment for a local biomasss-to-products econ nomy, protectin ng important ecosystem e services of the wettland for the enntire La Plata bbasin. The methodollogy herein sho own for Pantan nal in the Uppeer La Plata bassin can be exteended to other natu ural or manmaade wetlands to t provide praactical guidelinnes for policym makers and sttakeholders to prom mote the sustaiinable biomasss exploitation of o wetland vegeetation.

AC CKNOWLEDGEMENT TS Thiss work was paartially funded d by the Projeect “Biofuel prroduction from m floating bioomass mats in Brazzilian floodplaains: a case stu udy in Pantanaal” (MCT/CNP Pq/CT-Energ522-2008, 5780884/2008-2 and EMB BRAPA Macrroprograma 2 Infoseg 02.0 09.00.015.00.000). The authoors gratefully acknowledge finaancial support from the Natiional Council for Scientific and Technoloogical Developpment (CNPq, Brazzil). Special th hanks to our colleague c Luiz Alberto Pelleegrin (Embrapaa Pantanal) forr his valuable supp port with Uppeer Paraguay Baasin image.

RE EFERENCE ES Affo onso, A., Barb bosa, C., Nov vo, E., 2011. Water W quality changes in ffloodplain lakees due to the Amazon Riveer flood pulse: Lago L Grande de d Curuaí (Paráá). Braz J Biol 71, 601-610. 89   

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Malik, A., 2007. Environmental challenge vis a vis opportunity: the case of water hyacinth. Environ Int 33, 122-138. Marinho, C.C., Silva, C.P., Albertoni, E.F., Trindade, C.R., Esteves, F.A., 2009. Seasonal dynamics of methane in the water column of two subtropical lakes differing in trophic status. Braz J Biol 69, 281-287. Mitsch, W.J., 1975. Systems analysis of nutrient disposal in cypress wetlands and lake ecosystems in Florida. PhD Thesis, University of Florida, Gainesville, Florida. Odum, H.T., 1996. Environmental Accounting: Emergy and environmental decision making. John Wiley, New York, USA. Odum, H.T., Brown, M.T., Brandt-Williams, S.L., 2000. Handbook of Emergy Evaluation: A Compendium of Data for Emergy Computation Issued in a Series of Folios.  Folio 1. Available at: www.emergysystems.org/folios.php [accessed 06.10.11]. Odum HT, Arding JE. Emergy analysis of shrimp mariculture in Ecuador. Report to Coastal Studies Institute, University of Rhode Island, Narragansett. Center for Wetlands, University of Florida, Gainesville: 1991. Piedade, M., Junk, W., D’Ângelo, S., Wittmann, F., Schöngart, J., Barbosa, K., Lopes, A., 2010. Aquatic herbaceous plants of the Amazon floodplains: state of the art and research needed. Acta Limnologica Brasiliensia 22, 165-178. PradoJatar MA, Brown MT. Interface Ecosystems with an Oil Spill in a Venezuelan Tropical Savannah. Ecol Eng 1997 Mar; 8 (1), 49-78. Ramires, J.R.S., 1993. [Floating macrophyte mats transport as a function of the Paraguay River level, Pantanal – MS]. Monograph, Federal University of Mato Grosso do Sul, Corumbá. Portuguese. Schöngart, J., Junk, W., 2007. Forecasting the flood-pulse in Central Amazonia by ENSO-indices. Journal of Hydrology, 124-132. SCPESCA/MS. [Embrapa’s Fishery Bulletins from 1995 to 2007]. Boletim de Pesquisa Sistema de Controle da Pesca de Mato Grosso do Sul SCPESCA/MS de 1995 a 2007 [Internet]. Available at: www.cpap.embrapa.br/publicacoes/ficha.php?topicobusca=BP&titulo=BPBoletim+de+Pesquisa+%26+Desenvolvimento [accessed 02.10.11]. Portuguese. Souza, R.C.S., Vianna, E.F., Pellegrin, L.A., Salis, S.M., Costa, M., Bergier, I., 2011. [Location of permanent area occupied by aquatic vegetation in Paraguay River floodplain and surroundings]. [Proceedings of the XV Brazilian Symposium of Remote Sensing – SBSR]; 2011 Apr 30- May 5; Curitiba, PR, Brazil. São José dos Campos, Brazil: MCT/INPE; DVD + Internet, pp. 2036-43. Available at: http://www.dsr.inpe.br/sbsr2011/files/p0813.pdf [accessed 02.07.13]. Portuguese. Sweeney, S., Cohen, M.J., King, D., Brown, M.T., 2008. Creation of a Global Emergy Database for Standardized National Emergy Synthesis, in: Bardi, E. (Ed.), 4th Biennial Emergy Research Conference, 2006 Jan. Center for Environmental Policy, Gainesville, pp. 56-78. Vianna, E.F., Souza, R.C.S., Castro, W.J.P., Ishii, I.H., Salis, S.M., Lima, I.B.T., 2010. [Estimation of aquatic macrophyte biomass export with videographic images in the Paraguay river, Pantanal, Corumbá-MS]. [Proceedings of the 3th Symposium of Geotechnologies in Pantanal-GeoPantanal]; 2010 Oct 16-20; Cáceres, MT, Brazil. São José dos Campos: INPE; Campinas: Embrapa Informática Agropecuária, pp. 16-20. Available at: ainfo.cnptia.embrapa.br/digital/bitstream/item/28239/1/p156.pdf [accessed 02.07.13]. Portuguese.

APPENDIX Data and calculations related to Table 4. 1.18E+13 seJ US$-1 15.83E+24 seJ US$-1

Emdollar Brazil Transformity values baseline R1. Solar Energy Annual average radiation Albedo Incident light Area

8.29E+09 6 100 17948.50

91   

J m-² year-1 % % km2

Sweeney et al., 2008 Odum et al., 2000 EOSWEB EOSWEB Open water

Energy flow=annual avg. radiation*(1-albedo/100)*area R2. Wind Kinetic Energy Drag coefficient Geostrophic wind Energy flow = (geostrophic wind.)³ x air density x drag coefficient x area R3. Rain Chemical Potential Energy Rainfall (50 years average) Gibbs free energy Energy flow = rainfall x Gibbs free energy x water density x area R4. Rain Geopotential Energy Average elevation Runoff coefficient Energy flow = rainfall x average elevation x runoff coefficient x gravity x area x water density R5. Earth Heat Flow Average heat flow (for Guarani aquifer system) R6. Phosphorous Energy Material flow = Total Phosphorous loading = carried by the flood pulse + river water column R7. River Chemical Potential Energy Evapotranspiration (EVT) Water balance = rainfall - EVT Energy flow = water balance x Gibbs free energy x water density x R8. River Geopotential Energy Water flow (Porto da Manga average from 1993 to 2003) River geopotential energy flow = water flow x average elevation x gravity x density S1. Professional fishermen Professional fishermen Prof. fishermen energy consumption for living, 365 days a year Total annual days of fishing activities Year salary considering taxes and charges Transformity = year salary x emdollar/(energy consumption for S2. Sport fishermen Sport fishermen Sport fishermen energy consumption for living, 365 days a year Total annual days of fishing activities Year salary considering taxes and charges Transformity = year salary x emdollar/(energy consumption for P1. Aquatic vegetation biomass Biomass Phosphorous embodied in dry mass P2. Fish production Fish collected in the study region (estimated from 1995 to 2007 Embrapa’s Fishery Bulletins) Phosphorous embodied in dry mass (approx. 0.5%) P2a. Professional fishing P2b. Sport fishing P3. Clean water Water volume (Porto da Manga average from 1993 to 2003) Gibbs free energy of phosphorous concentration in water column = G = RT (M ln (C2/C1))-1 Energy of water with P = water volume x Gibbs free energy x water density x area

  92   

1.40E+20 J year-1 0.001 11.86

m s-1

1.22E+18 J year-1 1.34 m year-1 4.94E+03 J kg-1 1.19E+17 J year-1

ANA

70 40

Gonçalves et al., 2011

m %

6.59E+15 J year-1 2.24E+13 J year-1

Hamza et al., 1978

2.63E+06 KgP year-1

Buller, 2012

1.12 m year-1 0.22 m year-1 1.96E+16 J year-1

IMASUL

5.94E+10

m³ year-1

ANA

-1

4.08E+16

J year

590 4.58E+09 10 3963.63 3,72E+08

men J year-1 days US$ year-1 seJ J-1

12781 3.82E+09 5 39636.36 1,22E+08

men J year-1 days US$ year-1 seJ J-1

SCPESCA/MS

Authors assumption

SCPESCA/MS

Authors assumption

7.68 E+10 kgdry matter year-1 Buller, 2012 1.25E+05 kgP year-1 Buller, 2012 SCPESCA/MS

3.04E+05

kgfresh matter year-1

1.52E+03 8.31E+04 2.21E+05

kgP year-1 kgfresh matter year-1 SCPESCA/MS kgfresh matter year-1 SCPESCA/MS

4.08 E+10 m³ year-1 -1

1.E+05

J kg

6.91E+18

J year-1

ANA Buller, 2012