Soil fertility and changes caused by slash and burn agriculture in two watersheds of the upper Amazon, Peru

Photo: Karin Olsson

Author: Karin Olsson.

Supervisor: Lina Lindell, University of Kalmar

Examiner: Professor Dan Berggren Kleja, SLU

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ABSTRACT ........................................................................................................................................................ 3

RESUMEN ......................................................................................................................................................... 3

SAMMANFATTNING ......................................................................................................................................... 4

1. INTRODUCTION ............................................................................................................................................ 5

1.1 OBJECTIVE ................................................................................................................................................. 5 1.2 DEFORESTATION AND SLASH AND BURN AGRICULTURE ......................................................................................... 5 1.3 FERTILITY OF TROPICAL SOILS.......................................................................................................................... 6 1.4 SOIL FERTILITY INDICATORS ............................................................................................................................ 8

1.4.1 Chemical soil properties................................................................................................................... 9 1.4.2 Macronutrients ............................................................................................................................. 12 1.4.3 Micronutrients .............................................................................................................................. 14

1.5 PLANT REQUIREMENTS ................................................................................................................................ 16 1.5.1 Perennial crops.............................................................................................................................. 16 1.5.2 Annual crops ................................................................................................................................. 17 1.5.3 Pasture ......................................................................................................................................... 17

2. MATERIAL AND METHODS.......................................................................................................................... 17

2.1 STUDY AREAS ........................................................................................................................................... 17 2.2 LAND COVER CLASSES ................................................................................................................................. 19

2.2.1 Primary forest (class 1) .................................................................................................................. 20 2.2.2 Secondary forest (class 2) .............................................................................................................. 20 2.2.3 Pasture (class 3) ............................................................................................................................ 20 2.2.4 Plantations (class 4) ...................................................................................................................... 20 2.2.5 Burned fields (class 5) .................................................................................................................... 20

2.3 FIELD METHODS ........................................................................................................................................ 21 2.4 LAB METHODS .......................................................................................................................................... 21 2.5 STATISTICAL METHODS ................................................................................................................................ 22

3. RESULTS AND DISCUSSION ......................................................................................................................... 23

3.1 GENERAL SOIL FERTILITY ............................................................................................................................. 23 3.1.1 Sisa and Saposoa versus San Martín .............................................................................................. 23 3.1.2 Sisa ............................................................................................................................................... 25 3.1.3 Saposoa ........................................................................................................................................ 26 3.1.4 Sisa versus Saposoa ....................................................................................................................... 28

3.2 SOIL FERTILITY AND LAND COVERS ................................................................................................................. 29

4. CONCLUSIONS ............................................................................................................................................ 33

5. ACKNOWLEDGEMENTS ............................................................................................................................... 35

6. REFERENCES ............................................................................................................................................... 35

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Abstract Migration and changes in population and land use in the upper Amazon in Peru affects nature

and the surrounding landscape. The purpose of this study was to investigate how soil fertility

differs in two watersheds in upper Amazon, Sisa and Saposoa, and how the fertility changes

from slash and burn agriculture. Five different land covers were compared; Primary

vegetation, Secondary vegetation, Pasture, Plantation and Burned fields. Soil N, base cations

and other soil properties were used as a measure of fertility. Fertility refers to preferable

values of soil properties according to the low-high scale by Landon. Results show that the

soils from Sisa have a higher fertility level than generally soils have in the region. The

differences between the land covers were not as big and clear as expected. The most

significant result is nitrate which is at a higher level in the Burned fields. This ought to be due

to the increased nitrification following from disturbance of the soil and the concentrated

addition of organic matter. The reason for not seeing clearly falling levels of fertility would be

due to the shifting geology in the area, comparing with the more homogeneous geology of the

lowlands.

Resumen Migración y cambios en la populación y el uso de tierra en la selva alta en el norte de Perú

afecta la naturaleza y el paisaje alrededor. El propósito de este estudio era investigar cómo la

fertilidad se diferencia en dos cuencas en el norte de Perú, Sisa y Saposoa, y cómo la

fertilidad cambia de la agricultura de tala y quema. Cinco differentes coberturas de vegetación

han sido comparadas; Vegetación primaria, Vegetación secundaria, Pasto, Plantaciones y

Parcelas quemadas. Nitrógeno, cationes básicos y otros propiedades de los suelos han sido

utilizados como medida de la fertilidad. Fertilidad se refiere a niveles preferidos según la

escala low-high de Landon. Los resultados muestran que los suelos de Sisa tienen un nivel

más alto de fertilidad que suelos en general en la región. Las diferencias entre las coberturas

no eran tan grandes y claras de lo esperado. El resultado mas significativo es de nitrato que es

a un nivel mas alto en las Parcelas quemadas. Esto se debe probablemente a la nitrificación

aumentada siguiendo la perturbación y la adición concentrada de materia organica. La razón

de no ver niveles de fertilidad disminuyendo claramente será debido a la geología cambiando

en la area, comparando con la geología mas homogenio de la selva baja.

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Sammanfattning

Migration och förändringar i befolkningen och markanvändningen i höglandsdjungeln i norra

Peru påverkar naturen och det omgivande landskapet. Syftet med denna studie var att

undersöka hur bördigheten skiljer sig åt mellan två avrinningsområden i norra Peru, Sisa och

Saposoa, och hur bördigheten förändras när man börjar tillämpa svedjebruk. Fem olika

vegetationstäcken jämfördes; primärvegetation, sekundärvegetation, betesmark, plantage och

svedjade fält. Kväve, baskatjoner och andra egenskaper har använts som ett mått på

bördigheten. Bördighetsbegreppet avser önskvärda nivåer enligt Landons low-high-skala.

Resultaten visar att jordarna i Sisa har en högre bördighet än andra jordar i regionen.

Skillnaderna var inte så stora och tydliga som väntat. Det mest signifikativa resultatet är nitrat

som ligger på en högre nivå i de svedjade fälten. Detta beror sannolikt på den ökade

nitrifikationen som följer efter störningen av jorden och det koncentrerade tillskottet av

organiskt material. Förklaring till varför man inte ser tydligt fallande bördighetsnivåer skulle

kunna vara den skiftande geologin i området, jämfört med den mer homogena geologin i

låglanddjungeln.

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1. Introduction

1.1 Objective

This master thesis is carried out within the framework of an ongoing PhD research project run

by Lina Lindell at the University of Kalmar, Sweden. The objective of the research is to get

an overview of how deforestation of two watersheds of northern Peru affects the soil quality

and the chemical composition of stream water.

The objective of this thesis is to investigate the changes in soil chemical fertility when an area

in the highlands of the Peruvian rainforest is deforested and used for pasture and plantations.

Based on the soil chemical properties, an evaluation of the suitability of the current land uses

will be performed.

1.2 Deforestation and Slash and Burn Agriculture

The total Peruvian Amazon has the size of 775 650 km2 (FAO; 1993. p.22). The ecological

zone where this thesis investigation has been performed is called Selva alta and is divided into

two sub zones based on differences in precipitation; moist tropical sub-montane forest and

very moist tropical sub-montane forest (FAO; 1993.p. 23). Deforestation has become a severe

problem in the Amazonian forests. In 1990 Peru had a surface of 68.5 million ha covered with

amazonian forest. An estimated level of deforestation is 260 000 ha per year. San Martín, the

region where this study has been performed, is one of the regions in Peru with highest

deforestation rates. In San Martín an estimated 57 500 ha is deforested every year. That equals

approximately 160 ha per day (Predes; 2008). Logging and timber companies and small scale

farming are the main contributors to the deforestation.

Slash-and-burn agriculture is the traditional form of agriculture in the tropics where land is

cleared for cultivation. After a couple of years of use it is left to recover for a period of time.

This type of agriculture is unsustainable when population pressure is too high as it is in the

San Martín region (Troeh & Thompson; 2005). Approximately 21.000 persons migrate into

San Martín every year, a number that equals about seven families per day (Paitán; 2006).

Increases in population leads to heavier pressure on the soil since the soil no longer is left to

recover for enough time (Troeh & Thompson; 2005).

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The Peruvian forest law, Ley Forestal y de Fauna Silvestre, is from 1975 (with ratification in

1979) and includes all natural resources. The law has sufficient content to support a

sustainable forest management but it is not applied to full extent. According to a FAO report

in 1989 (DT No.20) the law is only practiced to 40%. It is economical issues that create

conflicts between conservation and industrial production of the forests (FAO; 1993. p.36-37).

Deforestation brings a variety of problems e.g. diminishing water flows, soil degradation and

loss of biodiversity. It also leads to leakage of nutrients since the nutrients accumulated in the

vegetation are released to the soil without cycling back since there is an insufficient land

cover. Nutrients can therefore be lost to ground water and stream water and other areas and

will not be brought back to the original area by natural means. The nutrient status commonly

declines over time and after some years the nutrient levels are too low to support e.g. pasture

production and new land must be cleared to continue the agricultural activity (Wood & Porro;

2002. p.17-18).

1.3 Fertility of Tropical Soils

The tropics are characterized by a hot and humid climate. Due to the high temperature

weathering processes in tropical soils are faster. When soils weather the amount of iron oxides

increases in the soil and contribute to give the soil a red color. There is a great variety in soil

colors and while the red tropical soils are common there are also areas where both grayish and

blackish soils occur. The color of the soils varies with the location and soil properties

influence on the soil color (Troeh and Thompson; 2005. p.58). The degree of weathering can

be divided into four different stages where stage 1 is least weathered and stage 4 is most

weathered. Tropical soils are almost all intensively weathered (stage 4) and almost all

nutrients are found in the organic matter. The organic matter is scarce in these soils and

decomposed at a high rate. Since the nutrients are present in the living organic matter it is

very important to keep an intact vegetation cover in tropical soils (Troeh and Thompson;

2005. p.140). Not only weathering is affected by temperature but when soil temperature

increases all chemical soil processes are enhanced and also the solubility of many compounds

increases. Combined with heavy rain high temperatures cause intense chemical weathering

and soil formation. Soil forming processes depends on the amount of water that is infiltrated

in the ground, the higher amount infiltrated the higher is the humidity level. It also depends on

the distribution of rainfall over time, the intensity and the air temperature at the time of rain

fall. The level of humidity has a great effect on leaching of nutrients and acidifying process in

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soil. Climate also indirectly affects soil formation processes through its effects on microbial

activity and type of vegetation. The natural vegetation of an area can tell a lot about the soil

type beneath it and the other way around. The vegetation affects soil forming process by its

degree and type of soil cover, root distribution and composition of litter that falls from the

vegetation (Eriksson et.al.; 2005).

The surplus of water in soil forms ground water or continues to other recipients such as

streams. When the water moves down and away from the soil profile it brings nutrients with it

and that is how leaching of nutrients occurs. This process causes a decline in pH and base

saturation. Due to greater surface runoff in steep areas, infiltration and thereby leaching can

be lower than on plains (Wood & Porro; 2002. p.201). Most nutrients originating from

weathering of minerals leach out to the waters, if they are not taken up by plants or kept in the

cation exchange between mineral and solution. The amount of cations in rivers is so high that

its mass is greater than that of soil particles carried with the rivers. The most abundant cation

in rivers is Ca2+

and for anions it is CO32-

(Troeh and Thompson; 2005. p.149).

Soil fertility depends on texture and mineral composition. The less fertile a soil is the more

root mass is found in the soil as a way for the plant to try to access as much nutrients as

possible. In the Amazon phosphorus is found to be the most limiting soil nutrient and many

times the concentration of Pav in the soil is less than 1 ppm. Approximately 90% of the soils in

the Amazon are poor in phosphorus content, 50% are poor in potassium and around 73%

suffer from aluminum toxicity (Wood & Porro; 2002. p.17-18, 201). An explanation to this is

the adsorption of phosphorus and potassium to Fe- and Al-oxides (Brady, 2002).

To increase pH level and avoid the problems that come with acid soils, such as e.g.

unavailability or excess of nutrients, liming is a common method. One of the most used

substance is CaCO3 (calcite).When considering liming the required amount depends on soil

type. Tropical soils rich in oxide clays only need enough lime to avoid aluminum toxicity

which can be a problem when pH is below 5.0. A desired pH in tropical soils is 5.5 (Troeh

and Thompson; 2005. p.170).

Levels of available and total potassium are often lower in humid areas compared to arid since

there are not so many 2:1 clays present that contain and release potassium. In humid areas

potassium is often present in feldspars or similar minerals that weather slowly. That is why

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the difference between humid and arid areas is greater in available potassium than in total

amounts (Troeh and Thompson; 2005. p.255).

1.4 Soil Fertility Indicators

Essential elements for plant growth are divided into macro- and micronutrients. The

macronutrients are N, P, K, S, Ca, and Mg (Havlin; 2005) with an uptake of 10-300 kg/ha

(Eriksson et. al.; 2005). The micronutrients are Fe, Mn, Cu, Zn, Cl, B, Ni and Mo (Havlin;

2005) with an uptake of <1 kg/ha (Fe<10kg/ha) (Eriksson et. al.; 2005). The elements are

present in different places of the soil, some are present in the soil solution (NO3-, Cl) and

others are present in exchangeable form (e.g. Ca, Mg and K) and generally increase with base

saturation, clay and humus content. The ones that are present in non exchangeable form (e.g.

S) can be found in i) primary and secondary minerals or in ii) organic litter, humus and

microorganisms. Elements in i) e.g. metal cations, P and K (99% of the total K can be found

here) need weathering or other processes to be available. Elements in ii) are foremost N (in

organic compounds), S and P. The organic matter has to be mineralized for them to be

available. Some non essential elements can be toxic for plants at high levels e.g. Pb, Cd and

Hg (Eriksson et. al.; 2005). In table 1 a classification scheme for different soil elements is

presented. This classification will be used as basis for fertility classification of the soils. When

using the fertility concept in this study it refers to a soil that has properties with preferable

values according to Landon’s classification (table 1). Preferable is not always equal to high,

e.g. for pH medium level is the better range for most plants.

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Table 1. Classification levels for different elements in soil (Landon; 1991)

Very Low Low Medium High Very High

pH <5.5 5.5-7.0 >7.0

CEC (meq/100g) <5 5-15 15-25 25-40 >40

BS (%) <20 20-60 >60

OM (%) <4 4-10 >10

Pav (ppm) <5 5-15 >15

Ntot (%) <0.1 0.1-0.2 0.2-0.5 0.5-1.0 >1.0

Caex (meq/100g) <4 4-10 >10

Mgex (meq/100g) <0.5 0.5-4.0 >4.0

Kex (meq/100g) <0.2 0.2-0.6 >0.6

Cuav (ppm) <6 >100

Fetot (ppm) 200-100 0001

Mntot (ppm) >2000

Motot (ppm) <0.01 0.10-1.00

Zntot (ppm) 2-501 >150

1.4.1 Chemical soil properties

pH

Results of pH measurements depend on what solution is used when measuring and also during

what season it is performed. During the vegetative season pH decreases due to the acidifying

effect of plant uptake of cations and also the carbonic acid that is produced in soil water by

the production of carbon dioxide from soil respiration. Uptake of cations is usually higher

than anion uptake and therefore the plant uptake has a net acidifying effect on soil. In a long

term perspective this only leads to acidification if biomass is removed from the ground or

forest is felled. If the biomass is not removed then the acidity will be used when litter is

decomposed. Among other things processes like nitrification also can contribute to decreasing

pH. Mineralization and weathering neutralizes the hydrogen ions. pH measured in CaCl2 is

normally 0.5 pH units lower than when measured in de-ionized water. If soils contain high

levels of iron or aluminum oxides measured pH is higher in salt solution than in water

because the oxides have more positive than negative charges. The later is the case in many

tropical soils (e.g. oxisols) (Eriksson et. al.; 2005). When pH is high there is a decreasing

availability of P and B to deficiencies at higher values. When pH is above 7.0 there is an

1 Stevenson; 1986.

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increasing liability of deficiency of Co, Cu, Fe, Mn and Zn. pH 5.5-7.0 is the preferred level

for most crops but for some crops and plants the lower end of this range is too acidic. Low

pH, below 5.5, signifies acid soils with problems such as possible Al toxicity, excess of Co,

Cu, Fe, Mn and Zn, and deficiency of Ca, K, N, Mg, Mo, P and S (and B below pH 5). The

availability of micronutrients is reduced with increasing pH, except for Mo. (Landon; 1991 p.

113-118)

CEC

CEC (cation exchange capacity) is the capacity of the soil to bind exchangeable cations. It is

equal to the amount of negative charges on the mineral surface. CEC depends on pH since the

number of variable negative charges increases with pH. In a soil with low pH CEC is limited

by the fact that some sites are not dissociated. The actual CEC in that type of soil is called

effective CEC (Eriksson et. al.; 2005). The contribution to CEC is especially important in

strongly weathered soils, as many of the tropic soils are. CEC depends on percentage organic

matter and clay in the soil. More important than amount of clay is the type of clay, since

weathered clays will not contribute to the CEC. In warm and humid areas the weathered clays

are common and therefore CEC is often found to be low in such areas. CEC varies a lot with

soil order and is often one factor used when determining soil order (Brady; 2002 p.20-21

p.345, 350, 360).

BS

BS (base saturation) shows the proportion of base cations in relation to the total CEC. A low

BS indicates an acid soil (Eriksson et. al.; 2005). Some tropical soils have a high BS at pH 5.0

which can explain why some acid-sensitive crops can be grown on acid tropical soils and why

liming does not increase their yield. Soils with high BS are considered fertile soils (eutric) and

those with low BS as less fertile soils (dystric) (Landon; 1991 p. 113-123).

OM

OM (organic matter) is an important source when it comes to organic nitrogen, phosphorus

and sulphur that become available when the organic matter is decomposed. Organic humified

matter contains approximately 58% carbon, 5-6% nitrogen and 0.04-0.20% phosphorus.

Humus binds cations and is also an important source of cations in plant available form. The

contribution from humus to CEC is especially important in coarse soils or highly weathered

soils with iron and aluminum oxides. Since the humus components have a low solubility they

also have an immobilizing effect on micronutrient and heavy metals. As mentioned in the pH

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section the organic matter also contributes to the acidifying effect in the soil with hydrogen

ions (Eriksson et. al.; 2005). Approximate guide lines for organic matter content are found in

table 1, but the interpretation of OM measurements depends on soil type and location

(Landon.; 1991 p.113-140).

EC

An EC (electrical conductivity) of 0-2 dS/m does not lead to any salinity effects and the soil

can be regarded as insaline (Landon; 1991 p. 157-158).

Texture

The greater the specific surface of a material the greater is its possibilities to release soluble

nutrients. The specific surface area increases with decreasing soil particle size, clay mineral

content and humus level. It is a very important property of a soil. Most clay minerals has a

great specific surface, the reactivity increases rapidly with size fractions <2 µm. Besides clay

minerals humus is an important factor for the chemical reactivity of the soil since humus also

has a big specific surface. Small particles are many times built in a similar way that gives a

high CEC. That is why the CEC is associated with the specific surface area. Buffering of

acidification is higher in clay soils than in coarse soils (Eriksson et. al.; 2005 p. 18 (25)-26).

Table 2. Particle sizes and their names in different languages.

Swedish Spanish English

<0.002 mm Ler Arcilla Clay

0.002-0.06 mm Mjäla-finmo Limo Silt

0.06-2 mm Grovmo-Sand Arena Sand

Loam and silt loam soils are best for most crops since they have enough clay to store water

and nutrients for good crop growth but not too much clay that would cause poor aeration and

the soils to be very hard to work. A soil containing 7-27% of clay and equal amount of silt

and sand has a loamy texture. If the soil also has high organic matter content it is very well

suited for plant production (Troeh & Thompson; 2005 p.41-42).

Exchangeable acidity (Al3+/H+)

The closer the exchangeable acidity is to the CEC (in number) the more acid soil it is

(Clemson University Extension Servixe (1); 2008). At pH levels below 5.5 the Al-ion is

released from clay lattices and soils with low pH run risk of Al toxicity (Landon; 1991 p.115).

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The aluminum as exchangeable cation is not usually compared to recommendation values.

Since the Al3+

and H+ are the acid ions it is more useful to evaluate pH and base saturation.

(Berggren; 2008).

1.4.2 Macronutrients

Macronutrients are essential for plant growth and development and are required in relatively

large amounts.

Phosphorus

In the top soil 30-60% of the total phosphorus content can be organically bound and is thereby

an important source of phosphorus for the plants. It becomes available for plants through

mineralization. The amount of plant available phosphorus is strongly correlated to soil pH.

The maximum solubility of phosphorus is within pH 5.5-8.0, at lower pH levels it forms low

solubility compounds with iron and aluminum. At high pH it can precipitate with calcium.

Due to the precipitation with Fe, Al and Ca, which immobilizes the phosphorous, the effects

of P-fertilizers can be absent. Organic matter can increase the solubility when the negatively

charged humic acids force the phosphate ions away from the colloid surfaces. In agriculture

soils the distribution of phosphorus is often uneven in the soil profile. Because of the low

mobility it predominantly remains in the top soil. Plants also take up phosphorus from the sub

soil and in combination with the low mobility the values of phosphorus can be found very low

in the sub soil (Eriksson et. al.; 2005). Fertilizer response is unlikely when levels are high,

probable when they are medium and most likely when they are low (see table 1). Maize has a

low P demand and deficiency for maize is <4 ppm while an adequate level is >8 ppm

(Landon; 1991. p. 113-137).

Nitrogen

Inorganic N is present in soil solution both as nitrate ions (NO3-) and ammonia ions (NH4

+).

Leaching of NH4+ is limited in clay soils since it fixates quite strongly to the negative charges

of the clays while NO3- is much more mobile and the risk for leaching is high (Eriksson et. al.;

2005). Nitrate leaching though has been found to not leach out to the groundwater but bound

to clays very deep in e.g. Ultisol profiles. This is positive since trees with deep root system

can be grown and thereby be integrated in a crop rotation and facilitate availability of nitrogen

for crops (Brady; 2005 p.558). The ammonia ion is adsorbed in exchangeable form and fixed

in clay minerals in similar way as the potassium ion. Nitrogen is also present in NH2 groups

and similar nitrogen compounds in the humus substances. Humus contains 5-6% of nitrogen

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and thereby represents the actual content of nitrogen in the soil. It becomes available for the

plants through microbial processes and mineralization. In the tropics many bush and tree

species have symbiotic nitrogen fixation by bacteria and root nodules. Leguminous plants can

fixate nitrogen by bacteria forming root nodules on the plants (Eriksson et. al.; 2005). When

analyzing with Kjeldahl method the levels of Ntot is classified as in table X (Landon; 1991. p.

138).

Calcium

Ca2+

is important to the chemical and physical properties of the soil (Eriksson et. al.; 2005).

Ca2+

is the dominating form of calcium both in soil solution and in the exchangeable fraction.

In agricultural soils exchangeable calcium can account for 50-90% of the total base cation

content. Timber harvest methods that leave the soil open to erosion and nutrient leaching lead

to rapid losses of calcium and magnesium from forest ecosystems. The release of Ca from

mineral weathering will not be able to keep up with the losses. Acid rain combined with

intensive timber harvesting may be depleting the Ca reserves in the more poorly buffered

watersheds. Forest growth has rarely showed a positive response to applied calcium (Brady;

2002). Ca deficiency only occurs in soils of low CEC at pH values of 5.5 or less. High K

levels may however inhibit plant uptake of Ca in soils having a more neutral reaction

(Landon; 1991. p. 113-124).

Magnesium

Minerals generally contain more Mg than Ca but usually more Caex than Mg. Mg2+

is

normally 10-30% of base cations and the percentage increases with the clay content and is

often higher in subsoil than in topsoil. Plant uptake of Mg is most of all affected by the

proportion of K+ and Mg

2+ but also by soil pH (Eriksson et. al.; 2005). When Ca levels are

high, Mg is less plant available. Mg deficiency is more likely on coarse, acidic soils. In

tropical soils Mg values >4.0 meq/100g is considered high and <0.5 meq/100g it is considered

low (Landon; 1991. p. 113-125).

Potassium

K is available for plants when it is present in the soil solution and adsorbed to soil particles.

Besides this it is also present in exchangeable form in organic matter but the amounts are low

since K+ has a weak binding capacity. The K unavailable to plants is bound to K minerals or

fixed to clay minerals (Eriksson et. al.; 2005). Response to K fertilizer is unlikely when levels

are considered high (see table 1) but likely when levels are below 0.2 meq/100g. Minimum

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absolute level of K is between 0.07 and 0.20 meq/100g. Minimum relative level is at least 2%

of the sum of all exchangeable bases (Landon; 1991. p.113-127).

1.4.3 Micronutrients

Plant micronutrients are elements that are essential for plant growth and development but that

are present and required in small amounts.

Aluminum

Al is a main limiting factor for growth in acid soils where it often is present at toxic levels. It

is difficult to find reference values for Al toxicity since it cannot be directly related to

exchangeable, available or total aluminum. Al toxicity varies with the environment at a

specific place and with the different plant species (Álvarez et.al.; 2005).

Copper

Cu is released from mineral rocks through weathering and is adsorbed by cation exchange.

Since the copper comes from weathering of minerals deficiency is more common in organic

soils than mineral soils. Deficiency can cause problems for plant growth in alkaline soils and

at very low pH levels since its solubility decreases with rising pH (Troeh & Thompson; 2005.

p. 147, 156-157, 291). A common range for copper is 2-250 ppm and an approximate mean

value is 30 ppm (Landon; 1991 p. 145, 151-152). The common range for agricultural soils is

5-60 ppm (Stevenson; 1986. p. 327). Cereals (e.g. maize) and vegetables are especially

sensitive to deficiency in copper. High levels of copper can be considered those above 100

ppm, but toxic levels are rare (Landon; 1991 p. 145, 151-152). Copper deficiency can be

expected when copper content is less than 4 ppm in mineral soils and 20-30 ppm in organic

soil (Stevenson; 1986. p. 327).

Iron

Iron is the micronutrient that is needed in largest amounts. Even when it is present in large

amounts in the soil deficiency can occur since iron often is present in insoluble forms (Troeh

& Thompson; 2005. p. 147, 156, 292-293). Of the micronutrients, iron is the element that is

most commonly deficient in soil (Stevenson; 1986. p.323). At high pH iron ions often

precipitate in compounds with low solubility, thus iron is more available at low pH. Iron can

become toxic at pH levels below 4-5. In Louisiana, U.S.A., iron toxicity is thought to be the

major constraint for growing rice. Phosphorus and iron levels affect each other. In soils with

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higher pH high phosphorus levels can contribute to iron deficiency. Soils that have a red color

due to iron oxide are often deficient in iron since these soils consist of compounds with ferric

iron which is a very insoluble iron compound, unavailable to plants (Troeh & Thompson;

2005 p. 147, 156, 292-293).

Manganese

Mn in soil ranges from 20 to 3000 ppm and can be toxic at high levels. Low pH increases the

solubility and probability for leaching. When Mn is dissolved it moves from acid areas to

alkaline areas in the soil and nodules form by precipitation. In acid conditions and in soils that

are not well drained, there is a risk for Mn toxicity (Troeh & Thompson; 2005. p. 295-296).

Levels above 2000 ppm in soils can be regarded as high (Landon; 1991. p. 153).

Molybdenum

Mo is the micronutrient that is required in smallest amounts. Sometimes the plant uptake is so

low that the levels in plants are not detectable. Mo is mostly bound in organic matter and

therefore the amount of Mo increases with the percentage of organic matter. Deficiencies are

mostly found in acid soils since the solubility increases with pH. In plants, levels above 10

and 20 ppm can be toxic to ruminant animals. It is probable that one kg/ha in the soil is

enough for plant growth. When applying P fertilizers the availability of Mo is likely to rise

since it is present in many P compounds (Troeh & Thompson; 2005 p. 148, 297, 312). A

normal level of Mo in soils is 0.2-5 ppm. Recommended levels have to be considered very

lightly since there is still much that is unknown about the behavior of Mo in soil. One

approximate level for tropical soils is 0.1-1.0 ppm, with deficiency below 0.01 ppm (Landon;

1991 p. 153-154).

Zinc

Zinc deficiency can be found in soils that are highly weathered, but it is not common.

Solubility of zinc increases with lower pH and in mineral soils it is common to have a zinc

content of 10-300 ppm but there is only a small amount in solution. One reason to this is that

the zinc ion is adsorbed strongly to clays, carbonates and other soil minerals (Troeh &

Thompson; 2005 p. 148, 299). According to Stevenson (1986 p.326) normal zinc levels in soil

ranges from 2 to 50 µg/g. Further, low levels of zinc are found in sandy soils, eroded soils and

peat and muck soils. Zinc deficiency is also many times increasing when phosphate levels are

high (Stevenson; 1986. p.326-327). Since the zinc availability increases when pH increases it

is not common with zinc deficiencies in acid soils (Landon; 1991 p. 151).

16

Major soil constraints

An overview of the major soil constraints in Central and South America gives an indication of

the conditions for agriculture activities in the area. 10% of the land surface in Central and

South America has poor soil drainage. CEC is low in 5% of the area, 39% of the land is

suffering from aluminum toxicity and 15% has high phosphorus fixation. In Peru 25-30% of

the land is dominated by very steep (>30%) slopes. But Peru is not among the top 12 in world

ranking of countries with most soil constraints (FAO Country rank; 2008 p. 4-5)

1.5 Plant requirements

1.5.1 Perennial crops

High yielding coffee take up at least 135 kg/ha of N, 35 kg/ha of P2O5 and 145 kg/ha of K2O,

the N requirements are lower for shaded coffee. Coffee also requires quite high amounts of Ca

and if there is a deficiency of Mg the quality of the coffee will be lower (Landon; 1991. p.

296). Originally coffee was grown with little input to the soil but now it is common with

fertilized, unshaded, small-sized bushes (Webster & Wilson; 1998). According to the variety

best yields are obtained at different altitudes, e.g. Arabica is grown at 1000-2000 masl in

Africa while Robusta is adapted to lower altitudes (Landon; 1991). Coffee generally requires

a pH of 4.5-5.5, but in Brazil the best yields come from soils with pH 6.0-6.5, a CEC at 40-

50% and base saturation of 60% in top soil. Some studies show an increased yield by 500%

after liming (Coffee research; 2008). Nutrient requirements are according to Procafé (2008)

20-45 ppm phosphorus, pH should be from 5.5 to 6.5 and organic matter content between 2

and 6%. Distribution of the different cations in percentage of CEC should be 10-15% K, 40-

60% Ca and 10-15% Mg. Further, aluminum levels should be less than 0.7 meq/100g to avoid

toxic effects. Coffee needs deep, penetrable soils for its tap root and the rest of root system to

develop well. When preparing land for coffee it is important not leaving the soil bare and to

save some trees for shading the plants. Instead of leaving the soil bare, plant residues should

be left on the ground or cover crop should be planted to protect the soil from erosion and to

contribute with organic matter (FAO (1); 2008).

Cacao is also a crop that grows with little input in shaded spots in humid areas but where

more fertilization is needed if it is grown unshaded (Webster & Wilson; 1998). Cacao can

grow in different soil types, with pH from 4.0 to 7.0, but the most limiting factor is the level

of organic matter (InfoAgro (1); 2008). It is also important with a well drained soil with

permeable layers to a depth of at least 80 cm for the roots to develop. Optimum altitude is

17

between 300 and 800 masl, but around the equator it can be grown up to 1300 masl (ICT;

2008).

1.5.2 Annual crops

Maize is tolerable to heat and drought and is important in intercropping as a support plant for

e.g. the beans to climb on (Webster & Wilson; 1998). Preferred pH is between 6.0 and 7.0,

but it can grow in soil with pH 5.0 to 8.0 (Landon; 1991). It can produce in different kinds of

soils, but best in deep soils with adequate levels of organic matter (InfoAgro (2); 2008).

Banana prefers a pH from 5.5 to 7.5 with an optimum at 6.5. Ntot content should be above

0.12% , Pav from 50 to 100 ppm and Kex around 0.4-0.5 meq/100 g (Landon; 1991).

1.5.3 Pasture

EMBRAPA in Brasil has come to the conclusion that phosphorus fertilization is needed in

order to have a continuously productivity of the pasture. It has been found that soils that are

low in phosphorus content limit pasture grass growth (Wood & Porro; 2002. p.306). Pasture

consisting of grass should have a pH above 5.2 and preferably around 6.0 (Clemson

University Extension Service (2); 2008).

2. Material and Methods

2.1 Study areas

The department of San Martín is located in the north of Peru and the landscape can be

described as highland rainforest with altitudes from 190 masl to 3080 masl (Peru Agency;

2008). The dominating geology in San Martín is from the Cenozoic era and the main deposits

are quaternary (Dumont; 1995). The soils are composed by materials of plutonic nature and

volcanic nature, shale, gneiss, limestone and sandstone. The geology differs a lot within San

Martín there are narrow lines going from north to south with different geology. In the area

there is frequently seismic activity at different strengths. In the areas where the study has been

preformed the forests are classified as Bosque intervenido o deforestado, Intervened or

Deforestated Forests (IIAP; 2004). Two areas in this department were chosen for this study.

These areas are the watersheds of Sisa and Saposoa which are located in the western parts of

San Martín. In Sisa the study was performed around a village in the northern parts where

altitudes varied between 1078 and 1333 masl. Approximately 110 families lived in the heart

and on the hillsides of this village. In Saposoa the study was performed in the south west

18

Figura 01: TEMPERATURA MAXIMA PROMEDIO REGIONAL

2006 - 2007

28

29

30

31

32

33

34

MAR ABR MAY JUN JUL AGO SET OCT NOV DIC ENE FEB

TE

MP

ER

AT

UR

A °

C

PROMEDIO 2006-2007 NORMAL REGIONAL

where altitudes varied between 684 and 938 masl. This village was about half the size of the

one in Sisa. In both villages families work on their chacras (agriculture plots) and produce

maize, rice and beans for household consumption and cash crops as coffee and cacao for

selling to the market. There are bodegas in both villages with provisions, basic goods and

satellite telephones. Deliveries from larger villages come in several times a week when the

weather conditions allow cars to travel on the roads. Electricity is only available in a couple of

household in each village.

San Martín has a tropical climate with an annual average temperature of 26.1 °C. Annual

rainfall is 1164 mm (year 1950-1990) (World Climate; 2008). In February 2007, when field

sampling was carried out, the temperature levels were higher than normal and the

precipitation levels were remarkably low. Maximum and minimum temperatures from the

weather stations in the area of Sisa and Saposoa were 2.2 respectively 0.6 °C higher than

normal, see fig.1 and fig.2. Precipitation in the study area was on an average 66% deficient

(SENAMHI; 2007).

Fig.1 Average maximum temperature for the region of San Martín. (SENAMHI; 2007)

19

Figura 07: TEMPERATURA MINIMA PROMEDIO REGIONAL

2006 - 2007

17

18

19

20

21

22

23

24

MAR ABR MAY JUN JUL AGO SET OCT NOV DIC ENE FEB

TE

MP

ER

AT

UR

A °

C

PROMEDIO 2006-2007 NORMAL REGIONAL

Fig 2. Average minimum temperatures for the region of San Martín. (SENAMHI; 2007)

Fig. 3 Map over Sisa and Saposoa

2.2 Land cover classes

Five land cover classes were included in the study. For each class 10 and 6 sites were sampled

in Sisa and Saposoa respectively.

20

2.2.1 Primary forest (class 1)

Primary forest has at no occasion been cut down by man. However, most of these forests

where the study was conducted had been selectively logged (i.e. specific trees have been

removed). The forest consists of a large variety of tree and plant species and is typical for the

sub-andean moist forest.

2.2.2 Secondary forest (class 2)

When an area has been clear cut and sometimes cultivated it is left to regenerate new

vegetation. This vegetation that grows into forest is called secondary forest. Where sampling

was done the secondary forest had not yet grown into a forest with large trees and timber. The

vegetation consists of small trees and bushes. The time passed since there was primary

vegetation on the site varied between 6 and 20 years, but at the majority of the sites

approximately 10 years have passed since there was primary vegetation.

2.2.3 Pasture (class 3)

Pasture for cattle were of the Brachiaria species. Brachiaria species are the most common

pasture in South America though originally from Africa (CIAT; 2008). The pasture could

have two different histories, the grass was either sown directly after clear-cutting or it was

sown after a season or two of maize, bananas and beans. It was not very high pressure on the

pasture, the cattle had relatively large areas to graze. Between 2 and 17 years have passed

since the primary vegetation was cut and burned on these sites, in Sisa the majority of the

sites were cut and burned approximately 3 years ago and in Saposoa approximately 12 years

ago.

2.2.4 Plantations (class 4)

The most common agricultural cash crop in the study areas is coffee. Large trees are usually

planted on a regular distance throughout the field to provide shade for the coffee plants.

Leaves from the surrounding trees and the coffee plants are left fallen on the ground to

contribute to the fertility by organic matter. None of the farmers added chemical fertilizers to

their plantations. The years that had passed since the sites were covered with primary

vegetation varied between 3 and 13 years, but at the majority of the sites 5 to 6 years had

passed.

2.2.5 Burned fields (class 5)

An important part of slash and burn agriculture is, as the name suggests, burning of the forest.

In the majority of the cases the vegetation that had been burnt was primary forest and in a few

21

cases secondary. The vegetation at the sampling sites had been burnt between one and four

months before the sampling occasion. On some plots logs were still laying there while on

others they had recently planted rice or maize. Ashes were also present on the plot in different

amounts according to time past and the wind and weather conditions since the plot had been

cut and burned.

2.3 Field methods

A total of 50 and 30 sites were sampled in Sisa and Saposoa respectively. Approximately one

third of the sites in Saposoa were not possible to sample in February due to heavy and

persistent rainfall. These were sampled by Lina Lindell in October 2007. From each site three

subsites were chosen and sampled. The three subsamples were taken diagonally across the

sampled location to obtain material from different altitudes across the slope. Samples have

been taken by digging a soil profile of 50 cm depth using an iron spit. From the profile,

samples of one kg were extracted from two depths; 0-10 cm (top soil) and 20-30 cm (sub

soil). The material from each subsite was mixed in a bucket and from that soil one kg was put

in a plastic bag for analysis. Density samples were taken from each depth interval by taking a

clot sample and putting it into a separate bag. The inclination was measured at each site with a

level and a folding rule.

2.4 Lab methods

Chemical analyses were performed by the laboratory Instituto de Cultivos Tropicales (ICT) in

Tarapoto and were carried out according to standard methods (Alvarado Valles; 2006) that are

described in short below. Analyses of copper, iron, manganese, molybdenum and zinc were

performed at ACME labs in Canada. Density and water content measurements were

performed by me, Karin Olsson, at ICT.

Measurements of soil pH were carried out in water. The electric conductivity was measured

with a conductivitymeter with 0.01 M KCl. Analyses of carbonates, calcite and dolomite, was

measured through CO2 release using HCl. Determination of the CEC and exchangeable

acidity was done through soil extraction with the reactant 1N KCl and the solutions are

titrated with NaOH. The required amount of NaOH for the titration is what gives the result of

exchangeable acidity. Values for Ca2+

and Mg2+

are given from atomic absorption of the

substances in a La- solution. Pex content is determined with the modified Olsen method and

from reading the absorption in a spectrophotometer and Kex content is determined with the

modified Olsen method and from reading the atomic absorption. Organic matter content is

22

determined with the modified Walkley and Black method. Total N has been determined with

the Kjeldahl method for top soil samples and for the sub soil it has been calculated out of

organic matter values. Nitrate and ammonium was determined with spectrophotometer after

extraction.

To determine the density of the soils a new procedure was invented for the occasion. Plastic

bags were weighed and then the density samples were put into the bags and weighed. The

density samples in their plastic bag was made as airless as possible and then put into a

cylinder filled with 100 ml water. The water volume displaced by the soil was noted and the

procedure was repeated three times. An average volume was calculated and then the volume

was calculated by dividing the weight with the average volume. This method is not a very

accurate method but was the only performable according to the available instruments.

When determining the water content the soil samples were weighed in beaker and dried in

105°C for minimum 24 hours. Subtracting the dry sample from the wet sample the amount of

water was obtained. Water content in percent is calculated by dividing the water amount with

the dry soil weight.

Analyses of the micronutrients were done in Canada where extractions for potentially

available (pot av) content have been made with 1 M sodium-acetate leach for total (tot)

content extractions were made with aqua regia (Acme lab; 2008). Potentially available

nutrients are those that are bound to e.g. carbonates and oxides (Lindell. 2008).

2.5 Statistical methods

The statistical analyses were performed using non parametrical methods with Kruskal-Wallis

and a multiple pair-wise comparison with Dunn-Bonferroni. A non-parametrical method was

chosen since the samples did not have a normal distribution. The method was also used in

Lina Lindell´s research project and therefore it facilitates comparison and discussion between

the works when the same method is used.

23

3. Results and Discussion

3.1 General Soil Fertility

Soil data was compared to a ranking in Landon (1991) which can be found in table 1 and the

soil data in table 2-5.

3.1.1 Sisa and Saposoa versus San Martín

Sampled soils were classified as Entisols and Inceptisols and were compared to previous data

from soils of these soils orders in San Martin. Soil pH in Sisa and the San Martín entisols

were within the range preferable for plants while the other soils were slightly acid. Base

saturation was close to 100% in all soils except the ones in Saposoa, there it was just below

the limit for fertile soils (Landon; 1991 p. 113-123). None of the Subandean soils had levels

of electric conductivity that would indicate salinity problems. The median percentage of

organic matter was low in all soils even though Sisa and Saposoa soils had higher values than

the San Martín soils. For both phosphorus and CEC Sisa and Saposoa soils had higher values

than the IIAP soils.

When comparing median values for the soils with the median for all soil orders in San Martín

top soils it showed that values from Sisa are indicating a higher soil fertility than the other

soils in San Martin.

24

Table 3. Soil properties in different areas.

Location Sisa Saposoa San Martín2 San Martín

San

Martín

z (1=top; 3=sub)/soil

order 1 1 all soils Entisol inceptisol

n 50 32 70 21 47

Value median median median median median

pH 6,0 5,4 5,5 6,1 5,3

EC dS/m 0,16 0,09 0,12 0,15 0,1

CaCO3 (%) - - 7,2 1,5 9,4

OM (%) 4,9 3,2 2,6 2,2 2,7

N (%) 0,3 0,2 0,1 0,1 0,1

P (ppm) 9,8 9,4 7,9 8,3 7,3

TEXTURE

(%)

Sand 32,9 28,8 38,4 33,4 33,5

Silt 25,2 29,6 28,7 24,7 25,7

Clay 35,9 40,6 26,8 35,9 33,8

clay clay loam clay loam loam clay loam

CEC 18,6 10,3 6,5 7,2 5,5

EX-

CHANGEABLE

CATIONS

(meq/100g)

Ca2+3

16,0 5,6 7,1 4,3 5,1

Mg2+

1,63 0,86 - - -

K+ 0,15 0,30 0,20 0,13 0,21

Al3+

+H+ 0,09 1,75 0,06 0,16 0,06

Sum of bases 18,6 6,5 5,4 7,2 4,6

Base saturation (%) 99,5 57,9 99,0 100 97,8

2 IIAP – Analisis fisicoquimico 3 Values from the IIAP analysis are Ca2++Mg2+

25

3.1.2 Sisa

Base saturation for Sisa top soil was very good, considering that median values were above

99%. Values ranged from 15.9% (low) to 100.0% (high). Values above 60% are considered

high and characterize fertile soils (Landon; 1991, p. 113-123). Median soil pH in Sisa was

within the range that most plant prefers, though the highest values were classed as high and

can cause Al-toxicity, low P availability for plants and nutrient deficiencies (e.g. Ca, K, N,

Mg and P) (Landon; 1991 p. 113-118). However, the exchangeable acidity (Al3+

/H+) was very

low in most sites and did not contribute to the acidity of the soil. Median Pex levels were

within the medium range and in top soil above the adequate level (8 ppm) for maize (Landon;

1991 p. 113-137). Even the lowest value in top soil, 4.5 ppm was above the deficiency limit (4

ppm) for maize (Landon; 1991 p. 113-137). Ca2+

values ranged from 0.6 meq/100 g (low) to

23.6 meq/100 g (high) and median Ca (16.0 resp. 14.2 meq/100 g) was classified as high

(Landon; 1991. p. 113-124). Mg2+

varied from 0.1 (low) to 2.1 (medium) and the median (1.6

meq/100 g) was within the medium range. In top soil median K+ was within the medium

range while it in the sub soil was low. In some of the locations K+

was under the detection

limit while the highest value was 1.4 meq/100 g (high). All the values of electric conductivity

were within the range of no salt effect (Landon; 1991, p. 157-158). Organic matter content in

Sisa soils varied from 0.3% (low) to 11.4% (high): the median values were in the lower range

of medium in top soil and low in sub soil (Landon; 1991 p. 113-140). Median total N in top

soil was (0.3%) within the medium range. Median value for CEC was within the medium

range. Values ranged from 5.0 meq/100 g (low-very low) to 26 meq/100 g (high).

Medium zinc levels are between 2 and 50 ppm and values in Sisa top soils were within this

range while slightly lower in sub soils. Manganese levels were within the lower medium

range. Sisa median Fe values did not reach normal levels. Most iron in the soils were probably

strongly bound in complexes and not extractable with sodium-acetate. There could be Mo

deficiency in Sisa soils, with values below 0.01 ppm, but information on Mo in soils is scarce.

According to Stevenson (1989) Cu levels lower than 4 ppm in mineral soils can lead to

deficiency, which was the case in Sisa soils.

The median distribution of particle sizes in surface soil was 40.6% clay, 29.6% silt and 28.8%

sand and 51% clay, 25.6% silt and 23.1% sand in sub soil. This distribution classifies them as

clay soils. The high clay content can lead to insufficient aeration and difficulties to cultivate

the soil. An optimal clay content for the crop is 7-27% (Troeh and Thompson; 2005 p.41-42).

26

3.1.3 Saposoa

Base saturation for Saposoa soils was not very high, although the top soils median was close

to levels that are considered high the sub soils median was only in the lower range of medium

classification (Landon; 1991, p. 113-123). Median pH value in Saposoa soils was classified as

low (<5.5 for both top and sub soil). This can possibly lead to Al-toxicity and deficiency in

Ca, K, N, Mg and P (Landon; 1991 p. 113-118). pH varied from 4.1 (low) to 7.0 (limit

good/high). The exchangeable acidity was almost 20% of CEC in the top soils and near to 50

% in the sub soils thus it contributed to even more acid soils than would it be with only the

low pH. A satisfactory P-level for maize is above 8 ppm (medium level) and the top soil

median value in Saposoa came above this (9.4 ppm). For the sub soils the median value was

quite lower with its 3.8 ppm (low). The P levels varied from 0.4 ppm (low) to 29.3 ppm (high)

(Landon; 1991 p. 113-137). Median Ca2+

values in Saposoa soils were low, though in top soil

just above medium level. Values went from not detected at all in the sub soils to 39.2

meq/100g (high) in the top soils (Landon; 1991. p. 113-124). Mg2+

values were classified as

medium in the top soils, but low in the sub soils. In all Saposoa soils the Mg2+

values ranged

from 0.06 (low) to 3.26 (high). K+ median values were low for both top and sub soils, but

almost three times lower in the sub soils than in the top soils. K+ levels were found from 0.03

(low) to 1.23 (high). All values of electric conductivity were within the range of no salt effect

(Landon; 1991, p. 157-158). OM content ranged from 0.6% (low) to 6.0% (medium) in the

Saposoa soils. Median values for as well top soils as sub soils were classified as low levels,

with slightly higher values in the top soils (Landon; 1991 p. 113-140). In Saposoa top soils

the median Ntot value was just between low and medium classification (0.2%). Median value

for CEC in Saposoa soils was classified as low and the overall values ranges from 3.3 me/100

(very low) to 43.8 me/100 (very high) (Landon; 1991 p. 113-122). Manganese levels can be

considered in the lower range of normal. Cu2+

levels in Saposoa were at such low levels that

they can cause Cu-deficiency. The normal range of iron levels is very wide but the Saposoa

soils did not enter in this range. There could be Mo deficiency in Saposoa soils, with values

below 0.01 ppm, but as mentioned in 3.1.1 information on Mo in soils is scarce. Zinc levels

were below normal levels in Saposoa soils.

The distribution of particle sizes was for the median value of Saposoa top soils 36% clay,

25% silt and 33% sand and of Saposoa sub soil 40% clay, 21% silt and 44% sand. The clay

content of sub soils was higher than in the top soils and at approximately the same level as

Sisa top soils and classification of the sub soil is just on the limit between clay loam and clay.

27

Saposoa top soil classifies as clay loam. This percentage of clay can lead to insufficient

aeration and difficulties to cultivate the soil. Clay content should be approximately 7-27% to

be optimal for the crop (Troeh and Thompson; 2005 p.39, 41-42).

Table 4. Results for all land cover classes in Sisa.

Location Sisa Sisa

z (1=top; 3=sub) 1 3

Value min max median min max median

pH 4,1 7,4 6,0 4,2 7,7 5,6

EC dS/m 0,07 0,45 0,16 0,02 0,24 0,07

CaCO3 (%) - - - - - -

OM (%) 1,1 11,4 4,9 0,3 5,4 1,4

N (%)4 0,19 0,69 0,32 0,01 0,24 0,06

P (ppm) 4,5 57,5 9,8 2,9 24,5 7,0

TEXTURE

(%)

Sand 9,2 58,9 28,8 8,6 57,0 23,1

Silt 16,0 41,8 29,6 10,6 35,6 25,6

Clay 20,8 53,3 40,6 29,0 65,2 51,0 TEXTURAL

CLASS Clay clay

CEC 6,2 26,0 18,6 5,0 24,6 16,6

EX-

CHANGEABLE

CATIONS

(meq/100g)

Ca2+

2,5 23,6 16,0 0,6 22,8 14,2

Mg2+

0,37 2,03 1,63 0,12 2,07 1,55

K+ 0,00 1,44 0,30 0,00 0,51 0,05

Al3+

+H+ 0,045 4,57 0,09 0,045 9,33 0,09

Sum of bases 3,3 26,0 18,6 0,8 24,5 15,9

Base Saturation (%) 48,1 100,0 99,5 15,9 100,0 99,2

Cupot av (ppm) 0,27 0,03 0,09 0,02 1,50 0,11

Fepot av (ppm) 9,0 85,0 20,0 10,0 107,0 31,0

Mnpot av (ppm) 6,0 175,0 48,0 2,0 236,0 27,0

Motot (ppb) <10 <10 <10 <10 13,0 <10

Znpot av (ppm) 0,5 10,0 2,1 0,1 4,5 0,5

4 Sub soil values are N calculated from OM content.

28

Table 5. Results for all land cover classes in Saposoa.

Location Saposoa Saposoa

z (1=top; 3=sub) 1 3

Value min max median min max median

pH 3,8 7,0 5,4 4,1 6,3 5,0

EC dS/m 0,03 0,48 0,09 0,02 0,16 0,04

CaCO3 (%) - - - - - -

OM (%) 1,6 6,0 3,2 0,6 2,0 1,1

N (%)5 0,12 0,34 0,20 0,03 0,09 0,05

P (ppm) 3,3 29,3 9,4 0,4 22,2 3,8

TEXTURE

(%)

Sand 8,8 60,7 32,9 6,7 58,7 40,2

Silt 14,1 43,5 25,2 11,6 40,1 20,6

Clay 18,8 69,1 35,9 25,1 71,2 44,1 TEXTURAL

CLASS Clay loam

Clay loam/Clay

CEC 3,7 42,2 10,3 3,3 43,8 9,9

EX-

CHANGEABLE

CATIONS

(meq/100g)

Ca2+

0,06 39,2 5,6 0,00 38,3 2,5

Mg2+

0,09 3,26 0,86 0,06 2,97 0,34

K+ 0,06 1,23 0,15 0,03 0,64 0,06

Al3+

+H+ 0,045 12,1 1,8 0,045 15,9 4,8

Sum of bases 0,3 41,8 6,5 0,1 41,6 3,0

Base saturation (%) 3,8 100,0 57,9 1,3 100,0 30,4

Cupot av (ppm) 0,03 0,48 0,1 0,02 1,28 0,1

Fepot av (ppm) 12 224 44 15 130 41

Mnpot av (ppm) 15 339 57 8 163 34

Motot (ppb) <10 <10 <10 <10 <10 <10

Znpot av (ppm) 0,2 1,2 0,6 0,1 0,6 0,3

3.1.4 Sisa versus Saposoa

According to the analysis of the median values of soil fertility indicators it is clear that the

soils in Sisa were of an overall higher quality than those in Saposoa. The soils in Sisa had four

chemical parameters (pH, EC, Ca2+

and BS) within the high range; none was classified as low

in surface soil and only one in sub soil (OM). In Saposoa soils only the EC had good values

(insaline) while three properties were low both in top and sub soil (OM, CEC and K+).

Saposoa top soil was also low in Ntot while the sub soil was low in P and Ca2+

. Phosphorus

levels are so low that a response to fertilizer could be expected according to Landon (1991).

In addition, the Sisa soils were higher in pH, BS, Ca2+

and K+ than the Saposoa soils.

5 Sub soil values are N calculated from OM content.

29

3.2 Soil Fertility and Land Covers

A comparison was made to determine similarities or differences between the studied land

cover classes. The median values for the top soils from respectively land cover class were

studied, see table 6. According to statistical analysis (Kruskal-Wallis non-parametric test

including a multiple pair-wise comparison with Dunn’s procedure) there were significant

differences between the classes for some soil properties. The analysis showed a difference in

NO3- between Pasture soils and Burned fields soils in both Sisa and Saposoa. In Sisa there

were a difference between Secondary vegetation and Burned fields regarding K+, also in

Saposoa there were a significant difference of K+ but Dunn’s procedure could not distinguish

between which classes. Furthermore the Sisa soils showed significant differences in Fe3+

which differed between Primary and Secondary vegetation. Regarding other properties there

were no significant differences. Some properties are similar between the classes, i.e. all

classes have the same density.

Figure 4. NO3- levels in Sisa for Primary vegetation (1), Secondary vegetation (2), Pasture (3), Plantation (4) and

Burned fields (5). Showing variation in NO3- and significant differences.

SI1

SI2

SI3

SI4

SI50

5

10

15

20

25

30

35

40

NO3- (ppm)

30

Figure 5. NO3- levels in Saposoa for Primary vegetation (1), Secondary vegetation (2), Pasture (3), Plantation (4)

and Burned fields (5). Showing variation in NO3- and significant differences.

Figure 6. K+ in Sisa for Primary vegetation (1), Secondary vegetation (2), Pasture (3), Plantation (4) and Burned

fields (5). Showing variation in K+ and significant differences.

SA1

SA2

SA3

SA4

SA50

5

10

15

20

25

30

35

40

45

NO3- (ppm)

SI1

SI2

SI3

SI4

SI50

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

K+ (meq/100g)

31

Figure 7. K+ in Saposoa for Primary vegetation (1), Secondary vegetation (2), Pasture (3), Plantation (4) and

Burned fields (5). Showing variation in K+ and significant differences.

After clear cutting of primary vegetation a decline of soil nutrients is expected as there no

longer is any vegetation or insufficient vegetation present to retain the nutrients in the system.

Lower nutrient levels would be expected in the other land cover classes after cutting primary

vegetation. The answer to that no difference could be observed in this study could be found in

the local geological conditions. See table 7 for Primary vegetation minimum and maximum

values related to natural variation. The variation in soils that have been left without impact

from human activity could be a possible explanation to the difficulty to see the expected

variations between the classes. Previous studies have been performed on lowland rainforest

with different and more homogeneous geology.

SA1

SA2

SA3

SA4

SA50

0,2

0,4

0,6

0,8

1

1,2

1,4

K+ (meq/100g)

32

Table 6. Soil properties under different land covers. Median values for top soils from Sisa and Saposoa.

Land cover Primary

vegetation Secondary vegetation Pasture Plantations

Burned fields

level median median median median median

pH 5,7 5,2 5,8 5,9 6,1

EC dS/m 0,1 0,1 0,1 0,2 0,4

OM (%) 3,3 3,1 4,1 4,5 4,5

N (%) 0,2 0,2 0,2 0,2 0,2

C/N 8,29 9,34 9,46 10,14 8,84

NO3- (ppm) 3,1 2,2 1,2 2,1 17,8

NH4+ (ppm) 14,3 12,2 11,0 11,4 9,8

P (ppm) 9,9 9,2 9,5 10,5 13,6

TEXTURE

(%)

Sand 34,9 39,5 31,3 24,4 24,9

Silt 26,7 28,6 31,2 29,6 29,3

Clay 37,1 27,3 35,1 44,4 44,8

Clay loam Clay loam Clay loam Clay Clay

CEC 16,2 14,9 13,9 19,8 16,5

EX-

CHANGEABLE

CATIONS

(meq/100g)

Ca2+

14,1 12,7 11,6 17,7 14,4

Mg2+

1,2 1,1 1,5 1,6 1,6

K+ 0,2 0,2 0,3 0,1 0,4

Al3+

+H+ 0,1 0,4 0,2 0,1 0,2

Sum of bases 16,1 14,2 13,7 19,2 16,5

% Sat. de bases 99,4 97,2 98,5 99,6 99,3

Cupot av (ppm) 0,1 0,1 0,1 0,1 0,1

Fepot av (ppm) 16,0 29,0 27,0 21,0 40,5

Mnpot av (ppm) 63,0 56,0 47,5 44,5 81,5

Motot (ppb) <10 <10 <10 <10 <10

Znpot av (ppm) 1,5 1,1 1,5 1,2 1,1

Al (ppm) 39,0 98,0 35,0 40,0 45,5

Density (g/cm3) 1,0 1,0 1,0 1,0 1,0

Water content (%) 21,1 16,2 22,4 20,0 27,9

33

Table 7. Variations in primary vegetation

Area Sisa Saposoa

Land cover Primary vegetation Primary vegetation

level min max median min max median

pH 4,9 6,9 6,1 3,8 7,0 5,4

EC dS/m 0,1 0,3 0,1 0,0 0,5 0,1

OM (%) 1,1 8,6 5,6 1,6 6,0 3,2

N (%) 0,1 0,4 0,3 0,1 0,3 0,2

C/N 1,13 13,30 8,29 7,48 10,22 8,59

NO3- (ppm) 1,2 28,9 2,2 6,3 14,8 13,0

NH4+ (ppm) 10,7 39,7 17,2 2,6 12,1 7,9

P (ppm) 4,5 51,7 9,1 3,3 29,3 9,4

TEXTURE

(%)

Sand 9,2 46,9 31,5 8,8 60,7 32,9

Silt 24,7 41,8 30,8 14,1 43,5 25,2

Clay 28,5 49,1 39,0 18,8 69,1 35,9

CEC 8,3 22,7 19,6 3,7 42,2 10,3 EX-

CHANGEABLE

CATIONS

(meq/100g)

Ca2+

6,2 19,6 17,4 0,1 39,2 5,6

Mg2+

0,5 2,0 1,6 0,1 3,3 0,9

K+ 0,1 1,4 0,2 0,1 1,2 0,2

Al3+

+H+

0,05 0,5 0,1 0,2 12,1 1,8

Sum of bases 7,8 23,0 19,6 0,3 41,8 6,5

% Sat. de bases 95 100 99 4 100 58

Cupot av (ppm) 0,03 0,19 0,09 0,03 0,48 0,1

Fepot av (ppm) 9 26 14 12 224 44

Mnpot av (ppm) 27 103 70 15 339 57

Motot (ppb) <10 <10 <10 <10 <10 <10

Znpot av (ppm) 0,7 10,0 2,6 0,2 1,2 0,6

Al (ppm) 10 148 19 631 1449 711,5 Density (g/cm

3) 0,9 1,2 1,0 0,8 0,8 0,8

Water content (%) 10,8 32,3 17,8 22,8 37,5 25,1

4. Conclusions Comparing Sisa and Saposoa with other soils in San Martín proved that the Sisa soils had a

higher fertility level than the San Martín soils. When comparing the median values of the two

study areas it can be noted that soils in Sisa have a better soil quality than soils in Saposoa.

Land cover classes did not show the expected difference with clearly falling nutrient levels

after clear cutting and agricultural use of the land.

34

This ought to be due to the variable geology in the area which is an argument that can find

support looking upon the variation in primary vegetation. It would be interesting to see more

studies of highland rainforest to see how these soils differ from lowland soils and the different

reactions that comes by disturbance and cultivation of the soil.

There are improvements of soil fertility that can be done. Improvement of the OM, being such

an important property affecting several other soil properties (e.g. pH, CEC and soil texture),

could have a positive impact. When clear cutting primary or secondary vegetation it is very

important to establish new vegetation as soon as possible. Leaving plant residues in the time

gap between cutting and planting can have a very positive effect. This will stop the soil from

eroding and thereby the residues help preserving the organic matter present in the top soil. In

the pasture it could be an idea to include some N-fixating plants that is also a good fodder. A

crop rotation with species that contribute to improving the soil and soil structure would be

positive. I got the impression that pastures were not included in the crop rotation/fallowing

cycle. If including N-fixating plants in the pasture and also considering the manure left from

the cattle on site this could be one good period in a crop rotation.

35

5. Acknowledgements I would like to thank the persons and organizations that have helped me and made it possible

to carry out this study. I want to thank the staff at Capirona for facilitating contact with and

transport to the villages in Sisa and Saposoa, the staff at Senamhi, also ICT for letting me

perform my laboratory work at their laboratory in Tarapoto and the Municipalities of Saposoa

and San José de Sisa with their radio stations. A special thank you to the farmers that let me

sample on their land and that facilitated my stay and work in the villages. I am especially

grateful for all the help and the warm hospitality of Sr. Prieto and his family in Saposoa. This

study would never have taken place if it was not for my tutor Lina Lindell, PhD student at the

University of Kalmar. Thank you for all your help and patience! Special loving thanks to

Willy for going and working with me during the sampling and for being by my side during the

long process of finishing this thesis. In addition thanks to my family and all my friends for

cheering me up in the dark moments.

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