INTRODUCTION



INTRODUCTION

In 2001, global aquaculture production exceeded 37 million tons (FAO 2002) and has become a continuingly growing multi-billion dollar per year industry in the United States. In the southwestern U.S., the largest sectors of agriculture are uniquely situated in relation to aquaculture in that many necessary input resource requirements of field agriculture can be provided through utilizing the waste outputs of aquaculture. Therefore, the agriculture industry in southwestern states has a great potential to benefit from incorporating aquaculture into its current management practices.

In 1998, aquaculture produced 25% of the total shrimp supply (FAO, 1998). Demand for shrimp and high market value have led to rapid expansion in shrimp aquaculture (Deb, 1998). Use of coastal areas for aquaculture often conflicts with other users, such as recreationalists and homeowners, or impacts sensitive mangrove habitat (Alongi, 2002). The high concentration of farms in coastal areas also leads to a self-polluting industry (Corea et al., 1998), as nutrient rich waters or disease exit one farm near the intake of the next. As a result of these factors, inquiries into the feasibility of inland low-salinity aquaculture operations are becoming more common (Smith and Lawrence, 1990; Flaherty and Vandergeest, 1998; Flaherty et al., 2000). Inland aquaculture reduces coastal conflicts and the risk of disease (Menasveta, 2002), but requires a new approach to water management.

Several studies have focused on water quality parameters and acclimation of marine shrimp for inland growth in low salinity water (McGraw et al., 2002; McGraw and Scarpa, 2003; Saoud et al., 2003). Lab and field experience has shown the importance of maintaining proper mineral ratios in the water (Zhu et al., 2004), and has identified potential areas to establish aquaculture facilities based on water quality. Reduced water exchange in inland culture should not affect yields (Thakur and Lin, 2003), but total shrimp farm groundwater use has not been quantified.

In achieving a more effective use of aquaculture pond effluent, farmers could make an important contribution to agricultural industries in arid regions, particularly by maximizing farm production without increasing water consumption (McIntosh & Fitzsimmons 2003). In many areas, integrating aquaculture with agriculture has become a channel for increasing the use of limited water resources (Prinsloo & Schoonbee 1993; Ingram et al. 2000), decreasing dependence on chemical fertilizers (Fernando & Halwart 2000), and providing a greater economic return per unit of water. In Arizona alone, over a trillion liters of irrigation water per year are used in agriculture that could be used for aquaculture first. In return, fish waste and algae production have the potential to sustain crop growth and yield, while lowering the usage and cost of chemical fertilization. There is a great need for an environmentally safe best management practice that will alleviate the use of these fertilizers, but which will also continue to profit growers.

Effluent and sludge from aquaculture ponds can act as valuable inputs into arid climate agricultural systems where natural irrigation water may be insufficient and depleted of nutrients (Hosetti & Frost 1995). Sludges, which may be discharged with liquid effluent, are most often comprised of sand, mud, uneaten feed, particulate matter, organic matter, bacteria, dead algal biomass, or fish waste. They can become thick, hard to move, and difficult to transport or collect. Algae, which assimilate available, aqueous forms of N and P into biomass, may settle at the bottom of ponds after death, sequestering nutrients. In areas where clays line the bottom of ponds, ammonium ions are weakly attracted to and retained by negatively charged cation exchange sites of clays and organic colloids in pond bottom solids (Boyd & Tucker 1998). Phosphates are more strongly adsorbed by pond muds, which become the eventual recipients of most PO4 added through feed input (Hepher 1958). Adsorption of both N and P to pond muds or poor spatial distribution may allow the benthic region of an aquaculture pond to become a temporary nutrient sink, which is unfortunate because they are cost-effective by-products useful for agriculture and they represent valuable sustainable resources as raw materials (Hosetti & Frost 1995).

It is not yet clear as to what kinds of integrative aquaculture-agriculture (IAA) systems are able to produce sustainable, positive production increases of field crops through land application of effluents. Regardless of increases, there may still be economic gain using IAA through simply maintaining original field crop yields and then raising fish in excess water to sell for profit. Stocking fish crops into ponds or irrigation reservoirs can provide greater economic security for farmers through diversification, as well as provide further income that would help to offset heavy irrigation costs of farming in the desert. It has been proposed that even a simple IAA system, such as introducing high densities of fish into irrigation systems may enhance land crops, alleviate the pressure of terrestrial and aquatic pests, and lower the populations of vectors of diseases of man and domestic animals (Fernando & Halwart 2000). In Arizona and other arid regions, where water costs continue to rise and where crop values are considered marginal, it is extremely sensible for fish to be cultured in pre-irrigation water before it is used to irrigate crops (Fitzsimmons 1988; Brooks 1989; Budhabhatti 1991; Fitzsimmons 1992).

Previous studies have shown that synergisms existing between inland aquaculture and agriculture contribute to positive ecological and environmental effects (Bacon et al. 1993; Edwards 1993; Gomiero et al. 1999; Fernando & Halwart 2000; Jamu & Piedrahita 2002; Prein 2002). Integrative methods used in some of these studies may allow for nutrient recycling of otherwise unused waste materials, nutrient and energy recovery, better sanitation, increased natural resource efficiency, low environmental loading, and little dependence on fossil energy inputs. Other studies have shown that utilizing an integrated system has the potential to positively affect crop production, net income, and/or sustainability (Bacon et al 1993; Hopkins & Bowman 1993; Lightfoot et al. 1993; Olsen et al. 1993; Shereif et al. 1995; Mosher 1996; Dalsgaard & Oficial 1997; Devendra 1997; Duong et al. 1998; Edwards 1998; Hosetti and Frost 1995; ICLARM 2000; Fernando & Halwart 2001; Prein 2002; McIntosh and Fitzsimmons 2003).

In 1993, a study by Olsen et al. in Maricopa, AZ, found that by integrating tilapia and channel catfish farming with cotton farming, there was an increase in total nitrogen (N) and phosphorous (P) content of irrigation water. However, effluent irrigations did not produce higher cotton yields or increase N and P in the soil. This was attributed to low fish densities, and therefore, low effluent concentrations. Our research has built upon this study and has taken into account the fact that concentrations of N and P in many integrated systems may be limited by two things working in conjunction: 1.) large quantities of diatoms, cyanobacteria, and green algae which assimilate available nutrients in the water and 2.) the inability of most pond systems to effectively transport nutrients in the form of sludge (sediment, ammonia, urea, solid fish waste, and dead algal biomass) from a pond to a field. With respect to pond nutrient content, specific attention must be paid, not only to feed input, absorption, and excretion, but also to all algae and bacteria communities because of their enormous impact on water quality and nutrient flow within aquatic systems.

The aim of our studies were to use integrated systems that would allow us to determine the effects of fish and shrimp effluent irrigations on the growth and yield of field crops in an arid region. This was accomplished by making comparisons between different irrigation and fertilization treatments. We also measured the nutrient content of irrigation water in an IAA system as a function of increasing fish densities to compare with studies done by Olsen et al. (1993). Through this study, we can determine if healthy and profitable amounts of fish and field crops may be grown in this sort of pond-field system. Perhaps most importantly, we plan on discussing the significance of pond biosolids in the IAA system. Each study was designed so that biosolids not exported during effluent discharge could accumulate at the bottom of the pond. Therefore we have made a determination as to what effect the collection and application (or lack thereof) would have upon the system as a whole. Finally, we plan to discuss the environmental and economic benefits of this particular system and make assumptions about the sustainability of IAA in arid regions. Within IAA, sustainability has become a major objective, and is surrounded by many questions. Prein (2002) notes that on-farm performance of IAA systems have been successful, yet not sustainable in large scale systems, but Jamu and Piedrahita (2002) argue that IAA systems are increasingly being promoted as an environmentally sustainable method for producing aquatic and terrestrial crops. Therefore, these studies were designed in order to further test the prospects and procedures.

Objectives

There are five specific objectives in undertaking this project:

1. Determine the benefits of irrigating olives with low-salinity aquacultural effluents by measuring growth of trees

2. Determine any detrimental effects on soil caused by the application of saline irrigation water through the monitoring of soil salinity and macro-nutrients

3. Reduce the reliance on chemical fertilizers through close monitoring of nutrients applied and through the application of nutrient rich aquacultural effluents

4. Efficient utilization of scarce water resources through the multiple use of water for shrimp production and irrigation

5. Initiate an integrated aquaculture/agriculture extension program in Arizona by hosting an integrated agriculture field day, distributing a newsletter, and developing a bulletin and website reporting the findings of the research and attitudes of the farmers involved with the trials.

Materials and Methods

Shrimp Trials

Experimental Design

We hypothesized that the use of shrimp effluent as an irrigation source would increase olive tree growth and water use efficiency over the use of well water, with no detrimental effects on soil salinity and productivity. We compared differences in tree height as a response to irrigation treatments between effluent, well water and irrigation with standard fertilization. The goal was to determine changes in growth due to the effluent irrigation and to compare those changes to growth expected with recommended fertilizer application. The economic savings from growing two crops with the same water was also examined.

An experimental plot covering 0.133 ha (0.329 acres) was laid out on a commercial shrimp farm growing Litopenaeus vannamei, the Pacific white shrimp, in Gila Bend, Arizona. Soils in this area have been classified as a torrifluvent association (Hendricks, 1985). The experimental plot was isolated from other olive groves, and the top layer of soil had been removed and used as a source of soil during pond building. Olive trees (one year old from cuttings) were planted in ten rows of twelve trees (120 trees total)(Figure 1). The design was a randomized complete block. It was unbalanced with respect to the effluent treatment in order to gain more knowledge about response to effluent. The treatment assigned to each row was randomized by lottery and trees to be planted within the rows were selected randomly, with order assigned by a random number generator. Each row was an experimental unit, with data reported as mean height for trees in each row. There was not a significant difference in tree height between treatments at the beginning of the study (F2, 117 = 0.31, p = 0.73).

The experiment was designed to approximate farm conditions. For this reason, trees were placed in rows receiving furrow irrigation. We planted as many rows as would fit across the experimental plot, with the extra row assigned as an effluent replicate to gain more information on response to effluent. Trees were planted in the bottom of a single furrow 30 cm wide and 30 cm deep, and watered by flood irrigation. Tree height was measured monthly, from a mark painted on the trunk, five cm above the original soil level, to the end of the longest branch. Trunk diameter was also measured initially, but was found to vary considerably depending on placement of the calipers. Due to this variability, this measurement was abandoned.

Irrigation

Trees were irrigated every week in the summer and every third week in the winter, approximating farm procedures. On the rest of the farm, trees were irrigated weekly in the summer, and as trees showed signs of water deficiency the rest of the year. Irrigation rates were 2.5 cm for each application from March through May and October through December, and five cm for each application from May through October. During shrimp production (approximately June to October), effluent from pond water discharge was used to irrigate the effluent treatment rows. The well water + fertilization treatment groups received urea fertilizer applications with the scheduled fertilizer applications for the rest of the farm (March through April). The rest of the year, all trees received well water.

Fertilizer was applied in four applications the first year and five during the second, with a target of a total of 0.23 kg of N per tree per year, or 188 kg/ha. This is half of what is recommended in the literature for large olive trees (Freeman et al., 1994), to account for the small starting size. In year one, 1.64 kg of urea (45% N) was applied per row in four applications, and a total of 10 cm of irrigation water (a rate of 112 kg/ha). In year two, five fertilizer treatments totaling 5.56 kg urea/row were applied in 12.5 cm of irrigation water (371 kg/ha), the full recommendation for olive trees. Urea was mixed with well water in 7,571-L water tanks before application in irrigation water.

Duplicate water samples were taken for each treatment during every irrigation event, to determine levels of nitrogen and salinity addition. A HACH DR-890 spectrophotometer (Hach Co., Loveland, CO) was used to analyze the samples (Table 1) for ammonia-nitrogen (NH3-N), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N) and total nitrogen. To confirm the nitrate-nitrogen results, a standard curve was developed, and all nitrate-nitrogen samples were adjusted accordingly.

Statistical methods

We compared mean tree growth among treatments from beginning to end of the experiment and the mean water quality parameters, using a one-way analysis of variance (ANOVA). We performed all analyses with JMP IN 4 statistical software (SAS Institute Inc., Pacific Grove, CA)

Fish-Pond Trials

Construction of the IAA system began in 2001at the Maricopa Agricultural Center (M.A.C.) in Maricopa, AZ. An elevated, oval-shaped pond, holding 1.8x106 L of water was used as an irrigation reservoir. A drain manifold was constructed using long PVC pipe, and uniform perforations were made along the top and sides of the entire pipe to allow for nutrient extraction from a wider distribution of the pond area. An aerator and floating, stationary cages were added to the pond, and fastened into place. Fish were then added to the pond, both in the cages and free-swimming, depending on the species. Water was siphoned from an adjacent reservoir in order to replace evaporated or discharged water as needed. Water discharge occurred only during irrigation events, and was carefully directed onto randomized plots of an agricultural field through slotted irrigation pipe. Some of the randomized plots received pond effluent applications, which were pumped from the pond near the southwestern corner of the field, while the others received well water applications, which were tapped from an alfalfa well at the eastern end of the field. The same slotted irrigation pipe was used for each treatment, with the water source location being the only variable factor.

The agricultural portion of the study was sectioned into a randomized complete block (RCB) with four treatments and four repetitions in a 4x2 factorial design (four treatments x two types of field crops). The four treatments differed according to their source of irrigation and chemical fertilizer application, and are defined as (1) well water irrigations only (W.W.), (2) well water irrigations + standard chemical fertilizer applications (W.W. + S.F.), (3) fish effluent irrigations only (F.E.), and (4) fish effluent irrigations + standard chemical fertilizer applications (F.E. + S.F.). Sixteen total plots were used, each containing a surface area of 0.024 ha with dimensions ([6]1.02m rows x 39.6m). Of the six rows in each plot, only plants in the center four were used in the study. During barley season, however, a 5.5m combine harvested the center of the 6.1m wide plots. Therefore, each harvestable plot area was approximately 0.021ha for cotton trials and 0.022ha for barley trials.

Prior to the study, the field was tilled, lasered, disked, and groomed with a bed-shaper. The soil type in the field was classified as sandy loam, and herbicide, insecticide, and defoliant applications were used as needed. For plots requiring chemical fertilizer treatment, ammonium sulfate (21-0-0) was applied as needed during all growing seasons, and monoammonium phosphate (11-52-0) was applied prior to each barley season. Approximately 106kgN/ha and 1157kgP/ha during every barley season, and 179 kgN/ha during cotton season was applied using chemical fertilizers. After each field crop harvest, a conservation tillage system was implemented, in which soils were tilled horizontally within their own plots in order to reduce contamination.

Irrigation

McCrometers were fastened onto the pipes nearest to the functioning water sources on each side of the field to measure the total volume and rate of water flow onto the agricultural field. The 6-row plots were diked along the edges and corners of rows one and six to allow for equal distribution of nutrients within each plot, and to eliminate treatment contamination between plots. Barley and cotton were both watered up by allowing irrigation water to reach the end of the row and slowly rise to cover the tops of irrigation beds, thereby saturating the soil around the planted seeds completely. Irrigation scheduling was outlined using data from the Arizona Meteorological Network for the city of Maricopa, and AZSCHED, a software program designed to manage and schedule watering events. Irrigation most often occurred when the amount of water used was at 50% depletion of plant available water (PAW) in the rooting zone. Multiple water samples were also taken from each irrigation treatment to determine the concentration of nutrients in the water applied to the field. Initially, the applied volume of water (per irrigation and total) differed between treatments of well water and pond water because of flow-rate differences between the gas-powered pump and the alfalfa well, but during the second half of the study, BMPs were developed to increase flow rates for well water treatments. A total of 667.6cm of water were applied to the 0.386 ha research field over three cropping seasons. Because of slight differences in water pressure, 17.98% more water was applied to plots receiving well water. The amount of N and P applied through irrigation was adjusted proportionally by increasing nutrient concentrations of effluent by the same percentage.

At the start of each irrigation event the effluent was concentrated and black in color, but then became slightly less concentrated. Therefore, time trials were performed on 8/25/02 to determine the rate of change in nutrient concentration over time during effluent irrigations. It was concluded from these trials that the surge of concentrated water had a negligible effect upon the total amount of N and P added to the field during each irrigation event.

Fish Cropping

Different species of fish were stocked into and harvested from the pond throughout the year (see Table 1). Koi (Cyprinus carpio), tilapia (Oreochromis niloticus), and channel catfish (Ictalurus punctatus) were selected for this study because of their abundance in M.A.C ponds and because of their pertinence to U.S. arid lands aquaculture. Tilapia and catfish are popular in inland aquaculture because of their favorable food market values, while koi are raised primarily for ornamental purposes.

Koi fingerlings were purchased from an independent distributor (Pisces Aquaculture Inc.), and were stocked into the research pond, while juvenile tilapia and catfish were seasonally added to floating cages in the north end of the pond. The 765m3 floating cages were made of mesh wire, metal, and styrofoam. They were tied together and fastened to the edges of the pond using rope and iron stakes. Additional juvenile and adult koi were added at different times during the season to increase the total pond biomass.

All fish were fed 2-3% of their biomass once per day as recommended by Tucker and Robinson (1990), five days per week, from 12/27/01 through 4/17/03 with a floating aquaculture feed (see Table 2 for nutritional information). Caged fish were fed through long pipes that allowed the feed to drop through and remain in the cage. A total of 449.6kg of feed were given over a 441d period. Fish were also allowed to feed upon pond algae, which were prolific during the summer. The pond’s pH level was routinely monitored and was found to be between 7.66 and 8.01 on a consistent basis. The concentration of total dissolved salts also slightly increased over the course of the study.

Field Cropping

Short-season barley (Poco variety) was planted on 12/21/01 using a JD 8200 planter with a seeding rate of 122kg/ha. Seeds were planted 4cm deep on rows and in furrows with 18cm spacing. During the first barley season, chemical fertilizers for selected treatments were deposited onto the field using a standard applicator prior to irrigation. In Arizona, short-season barley requires one to three irrigations after emergence, whereas late season cotton can require between eight and ten. Although it is not common to find barley planted on rows and in furrows, it was necessary to select a crop that would fit into a rotational-crop system with late-season upland cotton, an important agricultural product of central Arizona. Yield and repetitive growth measurements were collected and calculated from barley plants at random (seeTable 3 for all field crop measurements and techniques). Poco barley was harvested on 5/13/02 using a 5.5m wide International 1440 axial flow combine and weigh wagon.

DP-458 BR late-season cotton was planted using a MF-4263 Monosoem planter on 5/15/02 at a seeding rate of 83kg/ha. During the cotton season, both mechanical side-dressing techniques and manual techniques were used in the application of chemical fertilizers. Cotton was harvested using a four-row spindle picker, sampled for fiber analysis, and weighed using an SK-CrustBuster Boll Buggy, and harvested stalks were extracted using a root puller. DP-458 BR cotton was selected for this study based on its importance to the Arizona agricultural market, and because of the ease with which it can permit a field to be double cropped, allowing for year-round production. Yield and repetitive growth measurements were collected and calculated from cotton plants at random (see Table 3).

A second term of short-season barley (Quick variety) was planted on 12/19/02 using methods identical to those used for Poco Barley. Quick barley was deemed most similar to the Poco variety, which was taken off the market in 2002. Because of heavy rains in the winter of 2003, Quick barley received one less irrigation than Poco barley during the 2001-2002 season. Quick barley was harvested on 4/29/03. Heavy and unexpected rains fell during the winter of 2003 and did not allow for the necessary application of 2,4-D herbicide. Therefore, weed production increased and the number of total barley irrigations decreased form four to three. The abundance of weeds caused some proportional clogging of the grain hopper weigh station, but final yields were able to be adjusted proportionally.

Fiber Quality Analysis

Ginned samples (400g) of harvested cotton were sent to USDA labs in Phoenix, AZ for fiber quality analysis and were tested for color grade (a measure of cotton whiteness), micronaire (a measure of fiber thickness or fineness), staple (a measure of how long cotton fibers reach in a season), strength (how difficult it is to break a single fiber), and uniformity (consistency and similarity between cotton fibers). These measurements are used by ginning and processing plants to determine what prices and discounts cotton farmers will receive. For instance, cotton fibers with low micronaire ratings will receive more money per bale of cotton than fibers with high micronaire ratings; favorable staple and ratings combined with a low color grade will produce average returns for farmers. These analyses were important in determining if fish-effluent irrigations would affect cotton fiber quality.

Water Analysis

Three to four water samples were taken at each irrigation event of both fish effluent and well water. Concentrated sulfuric acid (H2SO4) was added to every other sample in order to eliminate any contaminating effects of algae. All samples were frozen until they could be analyzed for levels of electrical conductivity (EC), total dissolved solids (TDS), total Kjeldhal nitrogen (TKN), ammonia (NH4-N), organic nitrogen (Org-N), nitrates (NO3-N), phosphates (PO4-P), and total N (Total N) according to standard methods in the lab.

Soil Analysis

Soil samples were taken to determine the impact of nutrient leaching and adsorption. Using a 2m auger, replicate samples were taken from the soils of each treatment following the 2002 cotton season on 11/19/02. Samples were taken from the soil column at 15cm, 30cm, 60cm, and 90cm and were analyzed by IAS Labs in Phoenix, AZ.

Pond Biosolid Analysis

Pond sludge was sampled from the bottom of the research pond after the final fish harvest and analyzed for nutritive value at IAS Labs in Phoenix. In preparation for this harvest, however, many biosolids were uncontrollably lost during draining. Therefore, a total sludge production mass could only be estimated. Samples were taken from several different depths and locations within the pond and compiled to analyze the total sludge nutrient content.

Data Analysis

Because several dependant variables were measured in order to accurately characterize plant growth, the analytical data were summarized in a fashion that provides the greatest clarity (See Figure 4 for a list of comparisons). One-way ANOVAs with Bonferroni Post Hoc tests were used in comparing treatments, and a level of significance was set at p ................
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