Matt Harrison

Christopher Gomez

Agriculture Irrigation in the Canterbury Plains -New Zealand: Assessment from Landsat Imagery Remote Sensing

The Canterbury Plains have gone through significant agricultural changes since the 1970"s. Being situated along the drought prone east coast of the South Island of New Zealand and over permeable postglacial washover deposits and braided river coarse gravels, freshwater management is of prime importance. Agricultural changes have resulted in substantial increases in the amount of irrigated land across the Canterbury Plains, which have in turn led to significant management issues in relation to the availability, distribution and monitoring of freshwater resources. Therefore, it appears essential to develop an understanding of the water usage and resource at the plain-scale. The most appropriate approach at this scale is certainly satellite remote sensing. The availability of Landsat data dating back to 1973 has provided an opportunity to assess the capability of using the normalised difference vegetation index to identify irrigation areas. Through identifying the key long term changes and short term changes in rainfall and groundwater, an understanding of the variations that occur in NDVI was established. The initial assessment of the capability of using NDVI to map irrigation provided positive results for mapping the entire Canterbury Plains. The three tested dates found irrigation estimates for the Canterbury Plains to have results that fit in with the growth of irrigation in the Canterbury Region. February 5 th , 2004 recorded 199,682 hectares, February 16 th , 2008 recorded 263,697 hectares and December 26 th , 2010 recorded 297,251 hectares. However upon closer investigation, it was found that errors were likely occurring on a local scale. In order to improve the accuracy of using NDVI to map irrigation, field investigations at the incorrectly identified sites and fine tuning the defined threshold of NDVI values are required.

Introduction

The Canterbury Plains are one of the most important agricultural areas of New Zealand. The aquifer system of the Canterbury Plains is essential to maintaining the agricultural productivity of the land (Environment Canterbury [ECan], 2011a). The past 40 years have seen the Canterbury Plains go through a phase of change from mostly extensive sheep farming to intensive dairy farming [START_REF] Smith | Revolution or evolution? New Zealand agriculture since 1984[END_REF]. This change has led to increased pressure on the freshwater resources of Canterbury due to the higher water demand associated with dairy farming. The successful management of the freshwater resources of Canterbury is paramount to the future success of Canterbury as a leading agricultural producer in New Zealand. Remote sensing techniques provide very useful tools for rural management. This report will assess the potential of the normalised difference vegetation index (NDVI) to map irrigation. Remote sensing can play an integral role in understanding how agriculture has changed over the years and help to provide guidance for future agricultural development.

Canterbury Plains

Canterbury is home to the largest area of plains in New Zealand being around 180km long with varying widths stretching from the foothills of the Southern Alps to the coast. The Canterbury Plains have very little topographical variation with a gradual increase in elevation from the coast up to the foothills as well as slight depressions along the path of the rivers as shown in figure 1B. This extensive area of relatively flat land was formed from the deposition of the many glacially fed river fans that emerge from the Southern Alps. Geologically, the Canterbury Plains are comprised from primarily gravel dominated alluvial deposits along with many additional deposits of loess as shown in figure 1A (LRIS Portal, n.d.). Over time varying stages of glaciation and sedimentation have created many different layers of geological formations, some of which are more permeable than others. The more permeable layers hold the various aquifers of the Canterbury Plains. The depths required for a well to reach these aquifers vary from a few metres at the coast, to up to 150 metres near some areas at the foothills of the Southern Alps [START_REF] Lough | Vertical flow in Canterbury groundwater systems and its significance for groundwater management[END_REF]. While relatively dry and prone to droughts, the Canterbury Plains are well known for its agricultural production [START_REF] Wilson | Canterbury region -Landscapes. Te Ara -the Encyclopedia of New Zealand[END_REF]. This is largely due to irrigation from river uptakes and diversions, and groundwater extractions which boost agricultural capacity during the hotter, drier periods of the year.

¯ Study Area

The study area has been limited to the Ashley River to the north, the Waitaki River to the south, the foothills of the Southern Alps to the west and the pacific coast to the east. In addition, the area of Christchurch and Banks Peninsula were excluded from the study area, as they both present a very different physionomy that does not interest this study. The borders of the foothills and Banks Peninsula were defined using Landcare Research"s 25m digital elevation slope model (LRIS Portal, n.d.). The area of Christchurch was also excluded to the extent of Halswell, Hornby, Christchurch Airport, Belfast and Kaiapoi. Christchurch is a large urban area with a population of nearly 400,000 people. The focus of this study is towards the rural environment; therefore Christchurch was removed from study. Within the study area, seven target areas were located specifically to build a representative example of the Canterbury Plains. The overall extent of the study area along with the seven target areas can be seen in figure 2.

Climate

The Canterbury Plains are relatively dry and susceptible to prolonged periods of drought. Typical summers have low rainfall coinciding with increased sunshine and temperature. Winter conditions lead to increased rainfall and decreased temperatures and sunshine as shown in figure 3 over the page. The increased temperatures and sunshine hours in summer can lead to increased water stress through evapotranspiration. The climate of the Canterbury Plains area is largely determined by the surrounding topography. Being in the rain shadow of the Southern Alps, rainfall from the west falls before reaching the plains due to the topography of the Southern Alps through orographic rainfall. Expected climate change scenarios are likely to bring about increased severity, length and number of droughts (Ministry for the Environment [MfE], n.d.; [START_REF] Parkyn | Impacts of Agricultural Land Use[END_REF]. The change in climate will impact Canterbury water supply through decreased rainfall, increased evapotranspiration and decreased natural water storage due to glacial retreat and higher snow lines [START_REF] Srinivasan | Irrigation reliability under climate change scenarios: A modeling investigation in a river-based irrigation scheme in New Zealand[END_REF]. Srinivasan, Schmidt, Poyck and Hreinsson suggest that by 2040, there could be a 5% increase in the average number of days each year where water supply falls short of demand and by 2090 this could reach up to 17%. In order to better comprehend the situation for Canterbury agriculture, a stronger understanding of agricultural water use over the past four decades will be very useful. Sufficient management processes and policies need to be properly implemented to ensure sustainable and proficient use of Canterbury"s water sources. Exploring the potential of remote sensing can aid in building management techniques through a better understanding of the changes occurring over time and by providing a tool that can quickly analyse current conditions. While surface water extractions from rivers, lakes and irrigation channels are very important for irrigation in Canterbury, there is an increasing reliance on groundwater sources for irrigation. Recently annual groundwater use began exceeding annual surface water uptakes (ECan, 2011a). Groundwater is often the primary source for public, industry and agricultural use in the Canterbury area. It is used to help supplement agricultural productivity when rainwater is not sufficient and surface water is inaccessible. Historically Cantabrians have taken advantage of the complex aquifer systems of Canterbury since the mid 1800"s [START_REF] Brown | Groundwaters of the Canterbury Region[END_REF]. However, many areas of Canterbury are already over allocated for groundwater use, with some areas such as the Rakaia-Selwyn zone at 145% of the allocation limit. These allocation limits are set using a combination of techniques that relate to average rainfalls, land-surface recharge and area specific hydrological knowledge in order to maintain sustainable groundwater levels (ECAN, 2011c). While these allocations are not always used to the maximum allowable uptake, there is an alarming potential for groundwater to be overexploited in Canterbury which suggests a need to further management techniques.

Agriculture

Agricultural production in Canterbury provides a significant input to the national economy and will gain increasing importance as dairy numbers continue to grow. The spatial extension of agriculture in Canterbury (table 1) covers an area of 2,519,110 hectares, 444,777 hectares of this is equipped for irrigation [START_REF] Bascand | Agricultural Production Statistics[END_REF]. Due to a focus towards livestock farming, agricultural land in Canterbury is concentrated towards grazing and grasslands which take up over 80 per cent of the total land. Traditionally stock type in Canterbury has been dominated by sheep; however, recent trends show Canterbury is undertaking the fastest change nationally towards dairy [START_REF] Bascand | Agricultural Production Statistics[END_REF]. In 1999, the number of sheep in Canterbury were just below 10 million, while dairy cattle numbered as little as 275,000 [START_REF] Tinkler | Agricultural production: national and regional changes[END_REF], since then, sheep numbers have nearly halved to 5,348,010 and dairy cattle have increased nearly fivefold to 1,200,293 (Statistics New Zealand, 2012). This follows similar national trends where the number of Sheep dropped from a peak of just over 70 million in the early 1980"s to being as low as 32 million by 2010 (FAOSTAT, 2012), while dairy farming over this same period has seen numbers double from 3 million to 6 million in 2011.

Tab. 1 Canterbury agricultural land use (hectares). (Statistics New Zealand, 2012).

Agriculture in New Zealand has been largely influenced by changes in governmental policy towards subsidies during the 1980"s. In November 1984, changes in government budget, led to nearly 30 agricultural production subsidies being removed. This was a huge change as previously up to 40% of beef and sheep farm income was provided by the government through various subsidies [START_REF] Smith | Revolution or evolution? New Zealand agriculture since 1984[END_REF]. This removed the governmental influence and provided incentive for farmers to choose the type of farming which they believed would bring in the best returns. This led to large changes in the New Zealand farming industry; particularly important was the switch from largely extensive sheep and beef based farming to more profitable and intensive dairy farming.

Dairy farming requires much higher levels of water input when compared to other farming types. [START_REF] Stewart | Reasonable Stock Water Requirements, Guidelines for Resource Consent Applications[END_REF] recommend a range of 95 -140 litres of water per day for drinking water and dairy shed operations. This water requirement excludes the additional water required to maintain pasture growth to meet feed requirements. Comparatively, according to ECan (2011b) recommendations, sheep farming only requires three litres per head per day. This highlights the increased stress Canterbury"s water resources are going through. Canterbury accounted for nearly 60% of the national increase in irrigable land from the year 2007 -2012 and this has been largely attributed to the increase in dairy farming [START_REF] Bascand | Agricultural Production Statistics[END_REF]. The changes in agriculture in Canterbury are and will continue to cause strain on freshwater resources. There is a long history of surface water diversions across the Canterbury Plains. As early as 1896, the Waimakariri was diverted for irrigation purposes (Waimakariri Irrigation Limited, n.d.). The Rangitata Diversion race, the Lower Waitaki Scheme and the Greenstreet (Mid Canterbury) surface water diversions were all created between the 1940s and 1970s. In 1987 the Eiffelton Community Irrigation scheme was completed in the Mid Canterbury area. In addition to this, there is currently many new surface water diversions being proposed or under construction across the Canterbury Plains (Irrigation New Zealand, n.d.). Surface water diversions are important to take note of as they will impact the natural seasonal variations of vegetative health. Monitoring the changes in irrigation across the Canterbury Plains is very important in managing Canterbury freshwater resources. Differences in irrigated and nonirrigated agriculture are likely to be evident in satellite imagery, making it a useful management tool.

Management -Environment Canterbury and the Resource Management Act

The allocation of water for irrigation purposes in Canterbury is primarily the responsibility of Environment Canterbury, however is largely influenced by the Resource Management Act (RMA). ECan"s "Canterbury Water Management Strategy", states that "Environment Canterbury is responsible for managing the region"s water resource, including the flows and levels in any water body; control of taking, use, damming and diversion of water; the allocation of water and the control of discharges" (ECan, 2009). While maintaining this responsibility, ECan also has to uphold its role as a part of the RMA to monitor, report on and provide research in regards to the state of its freshwater resources. ECan is responsible for the allocation of freshwater resources for agricultural irrigation purposes across Canterbury. However, a large portion of the Canterbury Plains is already over allocated for groundwater take consents as shown in figure 4. This shows that many areas require strong monitoring to understand exactly how much of the allocation is being used. Currently there is a variety of methods used to measure how much of an allocation will be used. One method commonly used is the 150 day method (Aitchison-Earl, Scott & Sanders, 2004). This method is based on the assumption that irrigation users will use up 60% of their allocation over a 150 day period. As this is an assumption, there is a high potential for actual use to be greatly underestimated.

The Selwyn River is in an over allocated area and is particularly vulnerable due to its heavy reliance on groundwater recharge to maintain its flow. In particularly dry periods, well over half the length of the river can remain completely dry [START_REF] Kelly | Freshwater Ecosystems, 'Like a fish out of water': life in a disappearing river[END_REF]. The purpose of the RMA is "to promote the sustainable management of natural and physical resources" (New Zealand Government, 1991). Appropriate management of the groundwater resources in Canterbury is therefore very important in order to meet the requirements of the RMA. Steps are currently underway to improve the monitoring of groundwater uptakes through a compulsory program to install meters on all groundwater wells with an uptake of more than five litres per second before November 2016 (ECan, n.d.2). Remote sensing can easily be implemented as monitoring tool, and the Landsat program can help to provide an understanding of how agriculture and water use has changed over the last 40 years. Total amount of groundwater currently allocated exceeds the ECan maximum allocation limit.

Total amount of groundwater currently allocated is more than 80% of the ECan allocation limit.

Total amount of groundwater currently allocated is less than 80% of the ECan allocation limit.

Remote Sensing and Landsat

Remote sensing is the process of obtaining information about an object from a distance. This can be obtained from any distance whether it is just a few metres or from an orbiting platform such as a satellite [START_REF] Jensen | Introductory Digital Image Processing[END_REF]. The ability to obtain data from an aerial or orbiting platform allows for quick analysis of very large areas which would otherwise be very time ¯ consuming. Remote sensing techniques can obtain information on many physical attributes such as location, elevation, depth, biomass, temperature and moisture content of a particular target. In order to obtain this information, remote sensing takes advantage of the different levels of radiation reflected from the target at varying spectral wavelengths. Vegetation in particular, stands out well when compared with other surfaces across the red and near infrared spectral wavelengths. In addition to this, the accuracy and resolution of remote sensing equipment is constantly improving, allowing for increased capability of remotely sensed data.

The Landsat program began in the early 1970"s and is the longest running continuous series of remote sensing data capture [START_REF] Cohen | Landsat's role in ecological applications of remote sensing[END_REF]. Landsat has been used extensively across many disciplines since its existence. A simple search for "Landsat" through the Scopus database returns over 20,000 results. Landsat 1 began with only four spectral bands with a 60 metre pixel size, while Landsat 8, the most recently launched Landsat Satellite collects eleven spectral bands, across a range of pixel sizes from 15m to 100m. This spatial resolution is sufficient enough differentiate the boundaries between different farms. Landsat 1 -5 covers a range dating from as early as 1973 through to 2013. Landsat has a very consistent supply of data through these years for the United States. However, due to issues and costs with the privatisation of the Landsat program in 1985, New Zealand is missing many years of Landsat data [START_REF] Leimgruber | The impact of landsat satellite monitoring on conservation biology[END_REF]. One of the most important advantages of Landsat imagery is that it is free for download (Landsat Missions, 2013). Landsat has been chosen for this study due to having the appropriate attributes required for the study and being easily accessible for download through the USGS website.

Remote sensing has a proven track record in monitoring changes in vegetation and more recently the ability to detect moisture content is becoming more and more important. One of the most simple but well proven techniques for measuring changes in vegetation is the normalised difference vegetation index. The NDVI takes advantage of the specific reflectance levels across the red and near infra-red (NIR) bands of the electromagnetic spectrum. Bands 2 and 4 of the Multi Spectral Scanner (MSS) on board Landsat 1 -5 and bands 3 and 4 of the Thematic Mapper (TM) on board Landsat 4 and 5 capture the red and near infra-red spectrums. Following a simple calculation (shown over the page), the NDVI can help to identify vegetative masses that are under stress [START_REF] Rouse | Monitoring vegetation systems in the Great Plains with ERTS[END_REF]. The NDVI creates an index with a range between -1 and 1. The healthier the vegetation, the closer it will be to reaching 1. In a natural environment, the highest level vegetation can reach is between 0.8 and 0.9, while the unhealthy vegetation will be around 0.2 [START_REF] Weier | Measuring Vegetation. NASA Earth Observatory[END_REF].

NDVI = (NIR-Red) / (NIR+Red)
Having the ability to measure vegetative health without having to make physical contact is a valuable tool, particularly for those involved in water allocation planning. During drier periods, agricultural areas that are being irrigated are more likely to retain high NDVI levels compared to non-irrigated areas which are likely to show weakened NDVI values. The NDVI is advantageous because of its simplicity which allows it to be applied to all Landsat satellite products from the 1970"s through to now, unlike some of the more complex moisture and vegetation detecting indexes.

Important NDVI studies

The ability to measure the health of vegetation on a regional scale is very useful, particularly for management purposes. The NDVI is a very useful tool that has been used in many scientific studies. Particularly useful is its ability to detect levels of stress which are often caused by a lack of water. [START_REF] Sönmez | Relationship between spectral reflectance and water stress conditions of Bermuda grass (Cynodon dactylon L.)[END_REF] undertook a study using remote sensing to investigate the relationship between Bermuda grass and water stress conditions using varied levels of irrigation. Through the use of hand held spectroradiometers set two metres above sample plots they were able to measure changes in spectral reflectance.

It was found to exhibit a significant relationship between NDVI and water stress. The relationship showed that water stress led to decreased NDVI values, while irrigation which decreases water stress would increase NDVI values. Further analysis found it possible to extend the findings to satellite or aerial derived data. A study of Sahelian vegetation dynamics by [START_REF] Anyamba | Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981-2003[END_REF] used NOAA-AVHRR NDVI data to observe relationships between moisture and NDVI from 1982 to 2003. The NOAA-AVHRR is a satellite series which has been running since 1978 however with a spatial resolution of over 1km; the NOAA-AVHRR is more suited for larger scale projects (National Oceanic and Atmospheric Administration Satellite Information System [NOAA SIS], 2013). The main findings saw a significant period of drought from 1982 -1983 which co-existed with weakened NDVI values, the period 1994 -2003 marked a wetter period that co-existed with healthier NDVI values. The relationship between moisture and NDVI is further backed up by [START_REF] Ji | Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices[END_REF] who found strong relationships between NDVI and the Standardized Precipitation Index (SPI) in a study based on the northern Great Plains of the United States.

The SPI is an index based solely on precipitation. One of the important aspects noted in this study is the corresponding lag from rainfall to NDVI change. This study is particularly useful as the study area represents an area from which similar types of farmland to that of the Canterbury Plains. [START_REF] Ji | Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices[END_REF] also mention previous studies in the Great Plains which show varying response times from precipitation event to corresponding NDVI peak ranging from 14 to 61 days [START_REF] Yang | An assessment of AVHRR/NDVIecoclimatological relations in Nebraska[END_REF][START_REF] Liping | Modelling relationships between NDVI and precipitation during vegetative growth cycles[END_REF][START_REF] Rundquist | Mesoscale satellite bioclimatology[END_REF][START_REF] Wang | Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA[END_REF].

Understanding that there can be a significant delay in NDVI response to precipitation is important in analysing changes in NDVI over time.

Key Objectives

This study aims to assess the capability of NDVI in mapping irrigation on the Canterbury Plains. In reaching this goal, the report can be broken down to two key sections; first, the analysis of the historical trends in groundwater, precipitation and irrigation, and second, the implementation of an NDVI irrigation map based on the findings of the previous section.

The first section involved building an understanding of how the changes in precipitation, groundwater and irrigation affect NDVI. This helped in establishing an accurate NDVI range to represent irrigation and in choosing images with the right preconditions for building an irrigation map. The second section used the acquired information to build and test the accuracy of an NDVI irrigation map. Accuracy testing helped to identify the strengths and weaknesses of the irrigation map created as well as identifying key areas which need further investigation.

Methods

Three key datasets were analysed: remote sensing data, rainfall data, and groundwater data. Once processed, these were then compared to help understand the relationships they had between each other. The key steps followed in order to achieve the desired objectives are set out in a flow chart as shown in figure 5.

Remote Sensing

The following steps outline the key steps involved in the analysis of the available Landsat data:

An initial assessment was made through Earth Explorer to filter out the images which were not useable due to excessive cloud cover. Of those chosen, around half were available for instant download, while the rest were ordered and available for download within a week. Downloaded files were unpacked and loaded individually into the software package ENVI 5.0.

Following Rouse, Haas, Schell and Deering"s (2001) dark object subtraction method, atmospheric processing was used to ensure greater accuracy when comparing images from multiple dates. This required finding the darkest pixel with over 1000 pixels at that value from each band. In order to do this, a histogram output was created for every band of every image in order to establish the "darkest pixel" value. Using this information, ENVI was then able to calculate the dark subtraction.

The images were then joined and cropped in order to focus on the Canterbury Plains. This required creating a mosaic of the two images from each date using ENVI"s "Georeferenced Mosaicking" tool.

To set a border for the Canterbury Plains, a shapefile was created using ArcGIS. The northern limit was set to the Ashley River and the southern limit was set to the Waitaki River. The Eastern limit follows the coast from the south before going around Te Waihora Lake Ellesmere, Banks Peninsula and Christchurch. The suburbs of Halswell, Hornby, Belfast and Kaiapoi were included as part of Christchurch. The western extent of the plains and edge of Banks Peninsula were set using Landcare Research"s 25m digital elevation slope model. This shapefile was then used to crop the mosaic image in order to focus on the Canterbury Plains.

An NDVI calculation was applied to the cropped images through the use of ENVI using band math to following the NDVI equation NDVI = (NIR-Red) / (NIR+Red). As NDVI is a commonly used vegetation index, ENVI has an automated NDVI function which just requires the user to select if the Landsat data is from the Multi Spectral Scanner (MSS) or Thematic Mapper (TM) sensors.

Seven target areas were created within the Canterbury Plains with areas of 18.1km 2 that were spread out across the plains to act as representative samples of the varying regions. These target areas were located at varying elevations and distances to surface water. Where possible, the targets were located away from image gaps. The seven areas were named: Oxford, Cust, Hororata, Dunsandel, Ashburton, Orari and Glenavy. The seven NDVI target areas can be seen in figure 2 on page 13. These target areas were classified for their individual cloud cover for every image.

NDVI histograms were created for each of the target areas through the use of ENVI. This data was then transferred into excel where the histograms were visualised through five period moving averages derived from scatter graphs. Visualising the NDVI data this way creates distinct NDVI signatures for each date and location that can easily be compared with both rainfall and groundwater data.

For the final step in the image analysis, rainfall data was taken into account to choose the images most likely to be experiencing water stress. Using these images, a simple threshold was applied to highlight the pixels most likely to be irrigated.

Area Descriptions

Visual investigations were undertaken through the use of satellite imagery to identify key features currently evident in the landscape of each target area. Due to a scale limitation, Landsat images were not high enough to identify features smaller than the average paddock; therefore this step was completed using Google Earth images acquired between 2011 and 2013.

Rainfall

In order to better analyse the variances in NDVI, rainfall data was required to help gauge natural variances in NDVI against irrigation induced changes. Rainfall data was obtained from NIWA using their online national climate database "Cliflo". Seven climate monitoring sites were chosen across the Canterbury Plains which have been recording rainfall data across the entire study period. The seven sites are shown in figure 2 on page 6.

From these seven sites, a Canterbury Plains average was created and then compiled into line graphs for three separate time periods in order to easily visualise and compare the amount of rainfall that had fallen in the months prior to a satellite image being taken. In addition to this, a ten year annual moving average of rainfall was created in order to help understand possible long term changes to rainfall on the Canterbury Plains.

As mentioned earlier, there are significant relationships between precipitation and NDVI, however with varying ranges in lag time for peak NDVI values. It is expected that similar relationships may be found however the lag may not be as noticeable due to the use of monthly rainfall data.

Groundwater

To obtain a better understanding of the possible impacts of irrigation towards NDVI, groundwater information was used to look for relationships with NDVI and rainfall. Water is often sourced from the complex Canterbury aquifer system to meet the heavy requirements of irrigated agriculture. Large areas of the Canterbury Plains are already over allocated for groundwater irrigation (Environment Canterbury, 2012), which suggests a link could be found between NDVI and groundwater data.

Historical groundwater data was obtained through Environment Canterbury. The data for this was limited and many wells are missing significant blocks of data at different periods of the study. The data obtained, included the GW recordings for 8 different wells with data collections beginning before 1980 and continuing until at least 2012. The locations of the varying wells are shown in figure 3 on the following page. This data was organised into individual monthly line graphs through the use of both Microsoft Access and Excel. Ten year averages were produced for all wells to gain a better understanding of the long term changes. This data was then compared with the NDVI and rainfall data to establish any relationships.

A low groundwater level would naturally coincide with low rainfall; however irrigation uptake from groundwater can interfere with this. If rainfall is following a natural pattern and groundwater levels are unnaturally low with strong NDVI values, groundwater extractions for irrigation would likely be the cause.

Comparison of NDVI with Rainfall and Groundwater data

As shown in figure 5, this step involves a combination of the processed NDVI, rainfall and groundwater data. Once the analysis of the three different data sets has been completed, an investigation to specifically identify if a high NDVI value has occurred due to natural processes or irrigation. This involved identifying the unnaturally high range of NDVI values and highlighting them in the Landsat images as irrigated.

The results of this study are set out in four main stages. The initial stage is the analysis of the NDVI, rainfall and groundwater results. Following on from this is to identify the key links and trends within and between each data set. Images were then identified that were likely to have high levels of irrigation currently occurring. These images were then used to identify an NDVI value that could be linked with irrigation.

Creation of NDVI Derived Irrigation Maps

Using the results recorded, images with a high likelihood of containing irrigation were chosen and specific values were set for irrigation. Image thresholds were created and applied to these images to establish the feasibility of NDVI to identify specific irrigation targets or to calculate the total area of irrigation across the Canterbury Plains. Once created, the new maps will be compared with the available information on irrigation in Canterbury and as well as being visually investigated to identify potential errors.

Results

Target Site Analysis

Site analysis was undertaken to ascertain the current land features through Google Earth which provided high resolution imagery of the individual target locations. All sites are made up of primarily agricultural land, with variations stated in the individual descriptions depending on their location (Fig. 2). The seven sites were selected for their representativity of the diversity of the Canterbury plains.

The Oxford area is situated over the View Hill Stream between the Eyre River and the Waimakariri River at an elevation of 260 -310m above sea level (asl). Small pockets of forestry make up less than 5% of the area. It was evident that irrigators were installed in the area. The Hill View Stream appeared relatively dry.

The Cust area is located east of the small rural community West Eyreton at an elevation of 80 -120m asl. The Eyre River and riparian zone create a corridor through the site which makes up less than 5% of the area. There were two streams that appear to have no flowing water within the target area. Large irrigator systems were easily identified on majority of the land.

The Hororata area is located approximately nine kilometres south west of Hororata and five kilometres north of the Rakaia River at an elevation of 225 -250m asl. Irrigation practices were clearly evident in imagery.

The Dunsandel target area is located approximately six kilometres south east of Dunsandel with elevations between 40 and 60m asl. Large irrigators were less evident in the area.

The Ashburton target area is located approximately 15 km west of Ashburton next to the Hinds River at an elevation of 135 -175m asl. A small artificial lake was apparent which is connected to an extensive cannel network. Irrigation practices were clearly evident in the area.

The Orari target area is located approximately five kilometres south east of Orari at an elevation of 30 -65m asl. The Orari river flows directly through this area, with the river and riparian zone covering approximately 10% of the area. Large irrigators are noticeable on both sides of the river, however the northern side appears much dryer in colour in comparison to the southern side.

The Glenavy target area is located just north of Glenavy at an elevation of 20 -35m asl. An extensive channel irrigation network appears evident in imagery; however it is difficult to identify any large irrigators. 2 shows the basic individual NDVI statistics of each location for every image.

Across all target sites, standard deviations show that variance is lower in winter and spring than summer and autumn. The same difference in standard deviation can be seen between the summer 1973-1981 and the summer 2003-2011 targets with the latter having higher standard deviations. This helps establish that significant changes have taken place between the two time periods. To help understand if the rainfall prior to image capture was above or below average, a monthly mean (40 year average) was added to these figures. In addition to this, a ten year moving average of rainfall was created to identify the long term trends as shown in figure 42.

Using a moving 10 year average of rainfall data, long term changes in precipitation were also observed. Early in the study period, significantly higher annual rainfall was recorded across the Canterbury Plains. This is important as it suggests that the increases in healthy vegetation during summers after 2003 are less likely to be a result of increased rainfall. However, standard deviation is still high which means that an individual year could still have much higher rainfall. As shown in figure 43, the December 1973 image was taken after a significant dry period of three to four months at between 25 -50mm of rain per month. This supports the weakened NDVI values found at this date. While the February 1978 image had more rainfall in the previous few months when compared to the 1973 image. This is a likely explanation for why the late summer 1978 image had higher NDVI values when compared with the early summer 1973 image. The 1981 images were taken following three to five months of consistent rainfall at around 80 -100 mm per month with the exception of September. This relates well to the high NDVI values recorded in the two 1981 spring images.

The spring NDVI results for 2003 fit well with the rainfall received prior to image capture. Rainfall prior to the December image was lower than average and suggests that the NDVI values should have decreased more than what actually occurred. The February 5th image was showed concentrations of significantly weakened NDVI as well as concentrations of healthy NDVI. The rainfall prior to this date was well below average in October (41.5mm), November (43.0mm) and December (4.6mm), while January (58.8mm) recorded average rainfall. The low rainfall in the months prior to January would likely have had a significant impact on NDVI values. As January was recorded average rainfall it is expected that it would have had little impact on NDVI. This suggests that the areas of healthy NDVI for the February image are not rainfall related. The July image in the winter following this received lower than average rainfall, however being in winter, lower temperatures and sunshine hours result in less evapotranspiration allowing for better use of the available water which explains the large increase in NDVI. Groundwater dating back as far as 1970 was acquired across the study region from ECAN.

The consistency of data recordings prior to the year 2000 was very limited particularly in the southern half of the study area. However, from 2002 -2012, groundwater data collection was much more reliable providing a near full record for all wells as shown in figures 45 and 46 below. In addition to this, ten year averages were created from the monthly data and combined with a ten year average of rainfall in a time series graph in figure 44 below.

The ten year averages provided useful guidance in how both precipitation and groundwater levels have changed over the past 40 years. The well K37/0335 was removed from the 10 year analysis due to having only one recording prior to 2000. Wells with greater depths to water generally showed greater variation over time, while those with shallower depth to water showed the less variation. While the well recordings prior to 1985 were less consistent, the recorded higher depth to water levels fit well with the increased rainfall also recorded at that time. Most wells recorded a higher 10 year average groundwater level during the 1970-1980to 1979-1989period compared to the 1993-2003period. However, the 1970-1980to 1979-1989 period recorded significantly higher rainfall when compared to all other time periods, which lead to a period of increased groundwater levels. The 1980The -1990The to 1989[START_REF] Tinkler | Agricultural production: national and regional changes[END_REF] period saw an initial drop in rainfall but gradually increasing back to an average around 700mm per year. Groundwater levels in wells M35/1080, L36/0142 and K37/0215 during this same period followed a similar pattern with an initial decrease followed by an increase. After this period, rainfall remained relatively constant around 700mm annually for each 10 year average until the 2002 -2012 period with a slight drop around the 1997 -2007 period. However, from the 1992 -2002 period onwards, noticeable drops in groundwater can be seen in all Groundwater wells except for M35/0058 and J40/0045. Significant drops of 2 and 3 metres can be observed in the L36/0142 and K37/0215 wells which happen to be located within the Rakaia-Selwyn and Valetta ECan groundwater allocation zones. The Rakaia-Selwyn zone is currently at 145% of its allocation limit and the Valetta zone at 138%. This helps to explain the significant drop at this location. All other locations that saw minor drops in GW were also located in over allocated GW areas. The two locations that showed a minor increase were located in zones at less than 100% of allocation.

Due to the limited Groundwater data before 2000, monthly data was only analysed from this year onwards. Groundwater wells L37/0451, K37/1792 and J40/0045 which were located closer to the coast tended to have less monthly variation and were less affected by rainfall events. The wells located further from the coast show easily identifiable links to rainfall events where significant rain generally leads to an increase in groundwater level. In addition to this, there is a slight lag that can be noticed when a rainfall event causes groundwater increases. Mapping irrigation using NDVI Through the use of the key identified characteristics of both seasonal and long term changes to NDVI in relation to rainfall and groundwater, three images summer images with high areas of suspected irrigation were chosen. A threshold between 0.55 and 1.0 was applied to each image to highlight the potential irrigation areas.

The total areas identified as being irrigated (see table 3) fits well with the available data on total irrigable land in Canterbury. The total area of irrigable land in Canterbury at June, 2012 was 444,777 hectares [START_REF] Bascand | Agricultural Production Statistics[END_REF]. This covers the entire area of Canterbury which includes the major areas of the Culverden Basin, Waipara, and the Waitaki River catchment area. The study area does not include these areas and the December 2010 estimation allows for this as well as expected growth. Canterbury had an increase of 60,000 hectares in irrigable land between 2007 and 2012 [START_REF] Bascand | Agricultural Production Statistics[END_REF]. The estimated area of irrigation follows this trend of increasing irrigation that Canterbury has followed during this same time period.

In order to test the ability of NDVI to identify specific targets, the irrigation threshold images were explored to identify if obvious errors were occurring. To do this, circular irrigators were searched for as they provide an easy to identify circular shape on the landscape. This search however resulted in finding many circular paddocks which were either not identified at all or only partially identified as being irrigated. Examples of these areas are highlighted in figure 48 over the page. Further investigation is required to identify the potential reasons for not showing higher NDVI levels.

Discussion

Canterbury is one of the driest and drought prone regions of New Zealand, yet it is one of the most agriculturally productive regions. Due to its drought prone nature, managing the freshwater resources of Canterbury sufficiently is paramount to maintaining this agricultural productivity for the long term. The normalised difference vegetation index is a very useful tool to assist in rural management. It can provide a very quick analysis of vegetation health across very large areas. This vegetation health can then potentially be used to identify areas under irrigation. A remote sensing tool which can quickly create an irrigated area map is particularly useful in times of heavy drought. Accurate irrigation maps would benefit regional council in monitoring irrigation use, particularly when water restrictions are in place.

Improving the ability to quickly and efficiently monitor irrigation will be very useful for the management of freshwater resources. The decreases to groundwater in the past decade have been occurring largely as a consequence of poor management in the over allocation of groundwater resources.

Groundwater is becoming an increasingly important issue for ECan and the groundwater trends found in this report support this. Most of the Canterbury Plains are already over allocated for groundwater irrigation use and currently have little in the way of monitoring actual usage. Groundwater levels, particularly in the last decade have seen significant declines. Two of the groundwater wells that had the biggest drop in groundwater level are also in two of the highest over allocated zones. This highlights the importance of managing and monitoring irrigation efficiently. Due to the inconsistency of groundwater data before 1981, it was difficult to establish a base of non-irrigated groundwater trends to work from in identifying NDVI to groundwater relationships. While 2002 -2012 saw some short term links between groundwater and rainfall, significant links between increased summer NDVI values and groundwater could not be identified. While no obvious links were found, Statistics New Zealand reports show that Canterbury has gone through significant increases in dairy farming and irrigable land in the past ten years [START_REF] Bascand | Agricultural Production Statistics[END_REF][START_REF] Tinkler | Agricultural production: national and regional changes[END_REF]. This when coupled with the fact that most of the Canterbury Plains are over-allocated for groundwater use (figure 4) helps to explain the decreased groundwater levels. While no links were specifically found within the short term groundwater and NDVI data, the long term trends do suggest a possible connection with the increased summer irrigation NDVI concentrations.

The information gathered in regards to Canterbury agriculture prior to 1984 suggests that highly extensive agriculture was predominant across the Canterbury Plains. While after this date, due to a reduction in the government subsidies available to farmers, agriculture began to change towards intensive agriculture [START_REF] Smith | Revolution or evolution? New Zealand agriculture since 1984[END_REF]. The last decade has seen particularly high levels of intensification, notably in the increase in irrigable land largely as a result of increased dairy farming [START_REF] Bascand | Agricultural Production Statistics[END_REF]. Extensive agriculture requires much less human input and therefore less irrigation when compared intensive agriculture. Using the four images created before 1984 as a base for natural vegetative growth, it can be seen that a natural agriculture system is more likely to have NDVI values concentrated towards a specific value. When compared with the 2003-2011 images, the spring values match, while the summer values of the latter dates show concentrations at both unhealthy and healthy NDVI values. The dates which have concentrations of both healthy and unhealthy vegetation are likely to be a result of irrigation. In order to map irrigation areas using NDVI, it was required to limit the potential of rainfall to impact the NDVI values.

Through the analysis of ten year moving averages of rainfall, it was identified that the 2003 -2011 period recorded less rainfall than the 1973 -1981 period. As [START_REF] Anyamba | Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981-2003[END_REF] suggest, long term rainfall patterns can have long term impacts on NDVI levels. This supports the idea that the increased NDVI values found in the 2003 -2011 images are less likely to be rainfall related and are likely the cause of human induced changes. However the examination of rainfall in the months prior to each image provided a better opportunity to investigate the capability of using NDVI to identify irrigated land.

The normalised difference vegetation index was found to be significantly affected by the amount of rainfall in the months prior to image capture. Many studies highlight this link and particularly the fact that there can be varying amounts of lag time between a rainfall event and the corresponding change in NDVI levels [START_REF] Yang | An assessment of AVHRR/NDVIecoclimatological relations in Nebraska[END_REF][START_REF] Liping | Modelling relationships between NDVI and precipitation during vegetative growth cycles[END_REF][START_REF] Rundquist | Mesoscale satellite bioclimatology[END_REF][START_REF] Wang | Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA[END_REF]. The results found are backed up by these studies; however a specific lag time was not identifiable due to the use of monthly rainfall data and the inconsistent time frames between images. Further investigation through the use of daily imagery and rainfall would be required to establish set NDVI lag times for the Canterbury Plains.

The results for short term rainfall helped to further establish the link with NDVI. Importantly, these results aided in identifying specific dates which show concentrations of high NDVI values that are not likely to be a result of rainfall. These dates were identified based on a combination of the rain/NDVI lag information obtained from [START_REF] Ji | Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices[END_REF] and the rainfall that occurred in the two to three months prior. The selection of specific dates was important because if too much rainfall had occurred in the months prior, it would be difficult to differentiate between the effects of irrigation and rainfall. Also the need to monitor irrigation during wetter months is not as important as monitoring during the drier months when groundwater and surface water levels are at higher risk of overuse. The three dates chosen for irrigation mapping are useful in that there is significant information in regards to the changes in irrigation and farm types that closely match the timeframe [START_REF] Bascand | Agricultural Production Statistics (Final)[END_REF][START_REF] Bascand | Agricultural Production Statistics[END_REF][START_REF] Tinkler | Agricultural production: national and regional changes[END_REF]. The information in regards to the changes that Canterbury went through during this time is valuable as it provides a rough guide of what changes to expect in irrigation for the smaller area of the Canterbury Plains.

There is potential in using NDVI to specifically map irrigation. For this to work, the imagery used must be taken after a period of around 3 months of lower than average rainfall. Using NDVI across the entire Canterbury Plains produced results that fit well with the total area and growth rate of irrigable land in the entire Canterbury region. However, at a smaller local scale, the accuracy is questionable and requires further investigation. The NDVI maps created suggest that many irrigated areas were not recorded as being irrigated. However, this is based on the idea that the circular shapes evident in paddocks are from circular irrigators currently in use. Further field studies to investigate some of the unmapped circular irrigation fields could help in understanding why these fields did not show as being irrigated. A comparison of vegetation and soil types as well as surveying the farm"s irrigation use could explain as to why the NDVI did not raise to a high enough level. In addition to this, work is needed to fine tune the chosen irrigation NDVI range of 0.55 -1.0. This value was chosen based on the NDVI signatures created, however an investigation to identify the best possible range of NDVI for the Canterbury Plains would improve irrigation identification.

Limitations

There were some important limitations in this project, particularly in the availability of consistent groundwater and Landsat data. The lack of good quality Landsat imagery made analysing a consistent flow of images from the 1970"s until now difficult. From 1981 until 2003, no images were found to be of use, which removed the possibility of seeing the growth of irrigation during the 80s and 90s. Similar issues were found in the groundwater which had large gaps in data recordings prior to 2000. This limited the capability of comparing the 1973 -1981 images with the 2003 -2011 images in relation to groundwater fluctuations. If a complete track of monthly groundwater recordings had been available for analysis, relationships between NDVI, irrigation use and groundwater may have been easier to identify.

Conclusion

The Canterbury Plains is an area which is under significant pressure for freshwater resources. Groundwater trends identified in this report show significant decreases, particularly in the last decade. This is due to the significant agricultural changes the Canterbury Plains have gone through since the 1970"s. These changes were a result of changes in governmental policy towards agricultural subsidies in 1984. This produced significant differences between the agriculture of the last decade compared to that prior to 1984. Importantly, this created significant difference in the amount of irrigation used. This provided an opportunity to compare non-irrigated land and irrigated lands through Landsat imagery using the normalised difference vegetation index. Using this comparison, in combination with groundwater and rainfall data, NDVI was tested in its ability to map irrigation. Across the entire plains, it performed well, however at the local scale issues were evident. While the performance of NDVI in mapping irrigation did not reach expectations, the potential for using NDVI to map irrigation is still evident. Additional fine tuning and field work to improve accuracy are required to meet its full potential.

Bibliography:

Aitchison-Earl, P., Scott, D., Sanders, R. (2004). Groundwater Allocation Limits: Guidelines for the Canterbury Region. Environment Canterbury Report No. U04/02. Retrieved from http://ecan.govt.nz/publications/Reports/U0402.pdf

Figure

  Figure 1A and 1B: Geological map and topographical map of the Canterbury Plains (data obtained from LRIS Portal)

Figure 3 .

 3 Figure 3. Canterbury Plains monthly average in precipitation, temperature and sunshine 1972 -2012 (Adapted from Cliflo Database, n.d.)

Fig. 4 .

 4 Fig. 4. ECAN groundwater allocation zones and allocation amount(ECan, n.d.1. Reprinted with permission)

Figure 5 .

 5 Figure 5. Key steps to method process.

Figure 6 .

 6 Figure 6. December 7 th 1973 NDVI ¯Fi gure 7. February 5 th 1978 NDVI ¯Fi gure 8. September 3 rd 1981 NDVI image ¯Fi gure 9. October 27 th 1981 NDVI image

  The pre 1984 summer images tended to have NDVI values concentrated towards unhealthy vegetation values between 0.2 and 0.4, while spring values were all showing very healthy NDVI values closer to 0.8. Notably many target locations show December 1973 as having weaker NDVI values than February 1978. Orari showed the most significant difference to the other target areas in summer with a higher standard deviation due to a large spread of both healthy and unhealthy vegetation. The Orari River runs directly through this area, and the highest NDVI values were located closer to the river as shown in figure20. This suggests that the river could be having a positive effect on NDVI values possibly through surface water uptakes for irrigation. However, Cust also has a river flowing through the target area but only shows a slightly larger spread of NDVI and the difference is not evident in the imagery.The 2003-2004 period has provided a very useful analysis of a year-long NDVI cycle. Most areas show an easy to identify NDVI transition throughout the year. Orari and Glenavy are difficult to follow in their cycle due to the impact of excessive cloud cover impacting some NDVI data as signified in their respective figures. The general trend shows the NDVI values building a peak towards 0.8 through the spring months of September and October, before beginning to spread back towards 0.2 in December. February then shows a very strong spread of NDVI values from very unhealthy to very healthy. July then shows NDVI values beginning to increase back towards a healthy state. Standard deviation follows a similar pattern throughout the year being lower in winter and spring with NDVI concentrated towards the healthy vegetation value of 0.8. When summer begins, standard deviation increases as the NDVI begins to spread back towards the unhealthy vegetation value of 0.2 while some areas maintain their healthy NDVI values.

Figure 20 .

 20 Figure 20. Orari target area (red circle) December 7 th , 1973 with NDVI values between 0.55 and 1.0 highlighted. Orari River flows from top left to bottom centre of image.

Figure 21 .

 21 Figure 21. Orari target location NDVI signatures 1973 -1981

Figure 41 .

 41 Figure 41. Glenavy target location NDVI signatures 2003 -2004

Figure 42 .

 42 Figure 42. Ten year moving average of rainfall across the Canterbury Plains.

Figure 43 .

 43 Figure 43. Canterbury Plains monthly rainfall from 1973 to 1983. Satellite image capture dates highlighted with green arrow. The monthly mean for the entire study period is shown in red.

Figure 44 .

 44 Figure 44. Canterbury Plains monthly rainfall from 2002 -2012. Satellite image capture dates highlighted with green arrow. The monthly mean for the entire study period is shown in red.

Figure 45 .

 45 Figure 45. 10 year moving averages of groundwater and rainfall data across the Canterbury Plains.

Figure 46 .

 46 Figure 46. Northern groundwater well depths to water and rainfall 2002 -2012

  of the image to not be recorded in the images. The February 5 th , 1978 image is actually a mosaic of two images from February the 5 th and February 6 th , 1978.The four NDVI images from before 1984 provide the closest replication to a non-irrigated agriculture system. However, there are some early surface water irrigation schemes in place which possibly impact this. Both summer images show weakened NDVI across the plains with small areas of strong NDVI values. The December, 1973 image appears to have weaker NDVI in comparison with the February, 1978 image. It would generally be expected that a late summer image should show weaker NDVI due to prolonged hotter and drier weather. The two 1981 spring images show high NDVI results across the entire plains with October showing higher NDVI than September. Both the spring and summer results across the Canterbury Plains follow the expected natural path of NDVI with higher rainfall in the winter causing increased NDVI in winter and spring, and lower rainfall and hotter temperatures drying out vegetation in summer leading to decreased NDVI. The images dated from 2003-2011 tend to show similar results to pre1984 in the spring months with very strong NDVI. The July, 2004 winter result produced mid-range NDVI values, suggesting it is still recovering from the previous summer. Summer results tended to show a mixture of strong and weak NDVI values, with the exception of the December 3 rd , 2003 image which was still showing mainly strong NDVI values. The March 11 th , 2005 image is showing NDVI to be more similar to the summer images, while the March 28 th , 2011 shows stronger NDVI values across most of the plains. The key difference between the pre 1984 and 2003-2011 images is in the summer images which show much larger areas of healthy NDVI values in the 2003 -2011 years.

	Diachronic Analysis of NDVI Across the Entire Canterbury Plains.

NDVI images were created to show the variations in vegetation health across the Canterbury Plains from

1973 -2011 (figures 6 -19)

. The darker areas show weaker NDVI values and the lighter areas strong NDVI values. The darkest areas tend to be either surface water bodies or cloud cover. Three of the earlier images had satellite data collections errors which caused large areas

Table 2 .

 2 Individual target location and date NDVI statistics.

		Dec 7th 1973				Feb 5th 1978				Sept 3rd 1983
		Mi n	Ma x	Mea n	Stdev	Mi n	Ma x	Mea n	Stdev	Mi n	Ma x	Mea n	Stdev
	Oxford	-0.128571 0.819549 0.317579 0.156838	-0.15493	0.728 0.317625 0.164674	-1 0.825243 0.512556 0.159444
	Horora ta	-0.088 0.876543 0.249208 0.153853	-0.137931 0.774011 0.357664 0.122474	0.019608		0.9 0.487736 0.137507
	Duns a ndel	-0.130435	0.80117 0.153657 0.175725	-0.209302 0.809524 0.289236 0.155429
	Cus t	-0.138462 0.818182 0.301715 0.176719	-0.302326 0.815789 0.256293	0.17658
	As hburton	-0.127072 0.797468 0.199305 0.186608	-0.081081 0.820513 0.415208 0.163012	0.014493 0.851852 0.581975 0.136437
	Ora ri	-0.209677 0.895954 0.472245 0.235422	-0.219512 0.819355	0.36275 0.207994	-0.142857 0.837838 0.436483 0.177102
	Gl ena vy	-0.307263 0.726708 0.228281 0.219602	-0.875 0.773333 0.265096 0.184386	-0.142857 0.814433 0.524713	0.14795
		Oct 27th 1983				Sept 14th 2003				Oct 16th 2003
	Oxford	-0.012658 0.885057 0.672931 0.155021	0.016393 0.771429 0.515857	0.14584	-0.011765 0.812081 0.567228 0.166377
	Horora ta	-0.037037	0.87013	0.62891 0.164787	-0.027027 0.777778 0.513868 0.157913	0 0.794118 0.602798 0.132818
	Duns a ndel					-0.2 0.773585 0.537341 0.151965	-0.384615	0.81457 0.607278 0.173428
	Cus t					-0.085714 0.790476 0.559964	0.1587	-0.190476 0.824324 0.621264 0.165853
	As hburton	0.046729 0.871921 0.649555 0.154635	-0.021277	0.72093	0.36552 0.154147	0 0.744681 0.485284 0.184747
	Ora ri	-0.036364 0.909677 0.609954 0.197628	-0.170732 0.745098 0.370613 0.174219	0.014085 0.728395 0.434198 0.144967
	Gl ena vy	-0.050505 0.892683 0.668388 0.149425	0.033333 0.791667 0.604373 0.115116	0.1 0.674074 0.529253 0.082261
		Dec 3rd 2003				Feb 5th 2004				Jul 31s t 2004
	Oxford	-0.016393 0.803468 0.564028	0.14424	-0.018182 0.756098 0.430697 0.152187	-0.066667 0.727273 0.429862 0.134164
	Horora ta	-0.006993 0.806061 0.573028 0.132995	-0.092199 0.789474 0.370667 0.214817	-0.125 0.733333 0.470561 0.160068
	Duns a ndel	-0.277778 0.798817 0.534966 0.160212	-0.405405 0.792683	0.40442 0.229979	-0.222222 0.746032 0.486775 0.164438
	Cus t	-0.212121 0.802198 0.550077 0.162901	-0.222222 0.793939 0.453402 0.247817	-0.142857 0.764706 0.475201 0.167908
	As hburton	-0.282051 0.769231 0.413058 0.193362	-0.607843 0.798817 0.377741 0.213828	-0.111111 0.737705 0.395429 0.148682
	Ora ri	-0.046296 0.751196 0.265883 0.208084	-0.016393	0.76 0.404967 0.205066	-0.142857 0.727273 0.380296 0.206247
	Gl ena vy	-0.075594 0.771429 0.435182	0.22847	0.047619 0.676923 0.383179	0.10949	-0.066667 0.724138 0.470259 0.149418
		Ma r 11th 2005				Oct 5th 2005				Feb 16th 2008
	Oxford	0 0.747899 0.340356 0.134305	0 0.811321 0.583248 0.162309	-0.035714 0.761006 0.310642 0.164796
	Horora ta	-0.037594 0.793651 0.541643 0.156144	0 0.809524 0.553732 0.169943	0.009524 0.816092 0.492489 0.168537
	Duns a ndel	-0.304348 0.794872 0.438041 0.200533	-0.37931 0.822222 0.611829	0.1311	-0.307692 0.798561 0.422444 0.232422
	Cus t	-0.068493	0.8 0.471869 0.213983	-0.045455 0.810811 0.556331	0.18606	-0.25 0.801418 0.400539	0.22529
	As hburton	-0.511111 0.791045 0.517894 0.139814	-0.416667 0.812081 0.555635 0.178344	-0.52381 0.808917 0.459603 0.212153
	Ora ri	-0.090909 0.793103 0.451766 0.221278	-0.02439	0.80597 0.587434 0.163808	-0.463415 0.809524 0.451121	0.24203
	Gl ena vy	-0.050847 0.798319 0.576909 0.123168	0.02381 0.814286 0.616073 0.138208	-0.058824 0.801324 0.594118 0.124901
		Dec 26th 2010				Ma r 28th 2011
	Oxford	-0.086957	0.8 0.443548 0.167294	0	0.81982 0.556172 0.160236
	Horora ta	0.020979 0.772727 0.493744 0.179612	0 0.826923 0.642116 0.118565
	Duns a ndel	-0.333333 0.778947 0.439932 0.209715	-0.466667 0.813084 0.580425 0.154579
	Cus t	-0.266667 0.789474 0.462009 0.205824	-0.111111 0.803922 0.527923 0.179865
	As hburton	-0.540984	0.8 0.441225 0.215852	-0.4 0.813084 0.608218 0.163035
	Ora ri	-0.109091 0.787234	0.52458 0.179047	-0.06383 0.826923 0.515355 0.227792
	Gl ena vy	-0.030137 0.783784 0.484806 0.166594	-0.02381 0.793103 0.640181	0.09179

Table 3 .

 3 Total area of land with an NDVI value between 0.55 and 1.0 (hectares)

	Image Date	Total area of estimated irrigation
	February 5 th 2004	199,682
	February 16 th 2008	263,697
	December 26 th 2010	297,251

Figure 48. Predicted Irrigation areas for February 5 th 2004, February 16 th 2008 and December 26 th 2008 highlighting potential errors.


Fara Lala

Razafy Forêt

Fara Lala Razafy

Forêt, lémuriens et communauté locale

Keywords: Midongy Atsimo, transferts de gestion des forêts, impacts

ouverte pluridisciplinaire HAL, est destinée au dépôt

Introduction

Dans sa politique de lutter contre la spirale de dégradation de l'environnement, le Gouvernement Malagasy a encouragé la participation des communautés de base par le biais des transferts de gestion des ressources naturelles. Une des ressources dont la gestion a attiré les communautés de base est la forêt. La forêt de Madagascar en soi, de par sa flore est très riche en espèces endémiques faisant la renommée de Madagascar avec ses 12 000 plantes. Protéger la forêt équivaut ainsi à la préservation de la biodiversité. Et, encore à part les plantes, l'espèce faunistique pour ne parler que des primates constituent un fascinant domaine à explorer démontrant que la découverte des espèces nouvelles est encore à explorer. Dans ce contexte, le WWF Madagascar n'a cessé d'oeuvrer dans le maintien de la représentativité de la biodiversité en travaillant avec les communautés de base. Le défi est élevé d' autant plus que, dans sa mission, le WWF ambitionne à ce que la forêt protégée fournisse des bénéfices économiques et des services écologiques au peuple Malagasy. Toutefois, qui dit bénéfices économiques issus de la forêt pense souvent aux rendements que peuvent apporter les produits forestiers et entrainant ainsi conséquemment une perte en biodiversité.

La localité de Midongy Atsimo abrite une vaste étendue de forêt de basse altitude riche en biodiversité. La population de Midongy est classée au niveau de Madagascar comme une des plus pauvres. Les lémuriens dans cette zone sont encore inconnus et mal explorés. Le WWF s'est intéressé à travailler dans cette zone pour atteindre sa vision de conserver et protéger la forêt dense humide tout en satisfaisant le développement du bien être humain. Qu'est-ce que le WWF a donc développé comme approche pour pallier la conservation de la forêt, la satisfaction des besoins de la population et le maintien de la biodiversité? Cet article en se basant sur les expériences de WWF à Midongy Atsimo analyse la recherche d'équilibre entre la forêt, la communauté et les lémuriens. 2 Méthodologie : analyse des différents contextes de conservation Les forêts de basse altitude de Midongy sont connues comme représentatives de cette catégorie avec ses reliefs constitués de vastes plaines et de collines en demi orange. Classées parmi les forêts à sauvegarder pour la conservation de la biodiversité de cette catégorie en plus de celles du Parc National de Midongy, les forêts environnantes ont été délimitées avec les populations locales pour des transferts de gestion.

Les contextes sociaux-économiques

Etudes bibliographiques et monographiques

Le WWF en s'installant à Midongy en 2003 a fait des études bibliographiques basées sur les littératures publiées pour la mise en place du Parc de Midongy Befotaka d' une part. Et, d'autre part, par des analyses multiples et croisées de la richesse en biodiversité des forêts, de l'importance des différents écosystèmes, ainsi que de leurs valeurs économique et sociale. Des études monographiques ont aussi été conduites pour ressortir les caractéristiques et particularités de chaque localité où des communautés dépendent étroitement de ressources naturelles.

Etudes diagnostiques de la situation agricole

Les communautés vivant aux dépends des ressources naturelles ont souvent tendance à développer des techniques agricoles traditionnelles (cultures de riz sur brûlis, cultures de manioc, de patates douces et quelques cultures de rentes). Des études diagnostiques rapides de la situation agricole ont ainsi été conduites. L'idée est de ressortir les différents types de cultures que la région peut produire (analyse des produits commercialisables) et d'analyser le prix sur le marché. Une stratification des marchés existant a aussi été faite pour une orientation future des produits à cultiver et à vulgariser. Ces études ont aussi pour finalité d'avoir une idée sur les caractéristiques apparentes des propriétés des sols pour diagnostiquer quel autre type de culture non développé par les paysans peuvent y pousser.

Le contexte écologique

Etudes bibliographiques

Sur la base des études bibliographiques, il a été démontré que la zone de Midongy Atsimo présente un intérêt biologique valable pour mériter une conservation. La richesse du Parc Midongy Befotaka d'une superficie de 192 198 ha a servi de base pour assumer que les forêts riveraines sont aussi riches en biodiversité. Et, pour assurer les flux de circulation entre la flore et la faune, la conservation des zones périphériques est aussi indispensable. Sur la base de ces études bibliographiques, des études et/ou des inventaires supplémentaires ont été planifiés dans les zones où des transferts se feront.

Enquêtes informelles

Une des méthodes développée, surtout pour la faune, et plus particulièrement les lémuriens est constituée par les enquêtes informelles. Sur la base des documents existants, une liste des animaux pouvant se trouver dans les forêts à proximité des villages et ou hameaux est dressée. Des discussions informelles sont ainsi engagées avec les paysans pour sonder l'existence ou non de ces animaux. Des descriptions de ces animaux sont aussi demandées aux paysans pour compléter les informations.

Inventaires participatifs : agents du WWF, étudiants et population locale

Pour compléter les études bibliographiques et les enquêtes informelles, des inventaires participatifs ont été effectués. Ils sont appelés participatifs car ils sont conduits par différentes entités dont la population locale. En effet, il est très important d'impliquer les paysans dans les inventaires pour mieux les engager dans la protection de la biodiversité de ces forêts.

Les inventaires ont été effectués par des étudiants dans le cadre de leurs travaux de diplômes (Ingéniorat, Diplôme d' Etudes Approfondies) accompagnés par les agents du WWF et par des consultants spécialisés (primatologues, forestiers, écologistes, environnementaliste). Les méthodologies d'inventaires sont développées par les étudiants et consultants, expliquées aux communautés de bases, et les relevés des données sont effectués ensemble.

Analyse spatio-temporelle de la déforestation

Pour caractériser les pertes des forêts, des analyses spatiales et temporelles de la déforestation ont été faites. Ces analyses sont basées sur l'existence des images satellites. Les images utilisées sont des images LANDSAT TM. Les dates disponibles se situaient entre 2005 et 2010.

Les approches de conservation développées

Le WWF en tant qu'organisation mondiale oeuvrant pour la protection de la vie sauvage travaille aussi pour l'amélioration de bien être humain. Ainsi, pour obtenir le maximum d'impact sur la biodiversité, le WWF développe différentes approches de conservation. Il est sans conteste admis que sans ces approches développées, le risque de ne pas obtenir la participation de la population locale vivant à proximité des forêts est élevé.

Les transferts de gestion des ressources

Pour une meilleure implication des communautés dans la gestion des ressources dont la forêt, le WWF a fait la promotion de 12 transferts de gestion. Pour obtenir la signature de ces transferts, les résultats des différentes études citées dans le précédent chapitre sont synthétisées et transcrites dans un document officiel (Plan d' Aménagement et de Gestion Simplifié/PAGS) à signer par le Service de tutelle et par les Communautés de base (COBA).

En termes de biodiversité, les inventaires floristiques ont montré une richesse remarquable de la flore avec 291 espèces réparties dans 149 genres et 58 familles (MARLINE, 2009).

Lors des inventaires forestiers, il a été reconnu que les potentiels des forêts ne sont pas assez élevés : en moyenne une rangée de 100 à nombre de tiges par hectare pour un diamètre supérieur ou égal à 30 cm [START_REF] Wwf | Rapports lors de l'élaboration des différents PAGS de 10 COBA[END_REF][START_REF] Wwf | Rapports lors de l'élaboration des différents PAGS de 10 COBA[END_REF][START_REF] Wwf | Rapports lors de l'élaboration des différents PAGS de 10 COBA[END_REF]MARLINE, 2009). La surface terrière des forêts à Midongy (25,20 m2/ha) est inférieure à celles trouvées dans des forêts de même type à Ranomafana (34,96 m2/ha, Schatz & Malcomber. 1993) et Masoala (34,10m2/ha, Rabenatoandro, 2001).

Les espèces les plus utilisées dans la construction des maisons et la fabrication des meubles sont :Ocotea cymosa (Varongy) Dalbergia baroni (Voamboana) ,Tambourissa religiosa (Ambora), Ravensara flouribinda (Ravintsara) (MARLINE, 2009) ; Mimus opssalicifolia (Tendrikazo),Streblus dimepate, (Andrimena) ;Symphonia tanalensis (Nato), Leptolaena multiflora (Foto) D'un commun accord avec les gestionnaires, les exploitations forestières à but commercial ont été écartées. Par contre, pour satisfaire les besoins des communautés en bois, une partie des superficies des lots à gérer par les COBA est destinée à la satisfaction de leurs besoins en bois (construction des maisons, des écoles, des bureaux etc…) dont les quantités à prélever annuellement sont définies dans les PAGS. En cas d'exception, des accords au préalable par le comité de gestion et du Service Forestier sont nécessaires.

Pour les inventaires des lémuriens

Les sensibilisations et informations

Pour de meilleurs impacts dans la conservation de la biodiversité, des sensibilisations et informations périodiques ont été données aux membres des communautés de base. Ces approches ont pour objectifs de faire connaître à la population vivant à proximité des forêts l'interdépendance de la flore et de la faune dans la fourniture des biens et services divers à l'environnement en général, et aux êtres humains en particuliers.

En combinaison avec des connaissances générales sur l'importance de la biodiversité, des sensibilisations et des informations sur les intérêts d'utiliser des techniques adéquates pour une gestion durable des sols et une exploitation soutenue de différents types d'espaces ont aussi été données. Les membres des communautés ont ainsi pu prendre connaissance des avantages directes et des effets indésirables des exploitations non soutenues de ces espaces dans la durabilité de leur mode de vie.

Les formations techniques diverses

Pour un meilleur accompagnement de la population locale dans l'application des différentes connaissances « quasi nouvelle » pour elle, des formations techniques diverses ont aussi été données. La diffusion de ces formations se fait sous forme pratique et sous forme de documents enregistrés dans des supports audibles. Les paysans sont encouragés ensuite à se réunir périodiquement (hebdomadairement ou mensuellement selon leur organisation) et à écouter et commenter ensemble ces formations et témoignages.

Pour les gestions diverses et les activités de développements

Pour la gestion en soi des associations, les COBA ont reçu diverses formations dont : La gestion des associations, la gestion des réunions, la gestion des caisses (pour les entrées et sorties d'argent) ; la gestion des forêts (pour les satisfactions des besoins en bois). Ces formations ont pour but de rendre fluide la vie associative et pour faciliter les suivis et contrôles divers.

Les COBA élisent des comités pour chaque section (vie associative, caisse, technique et…). Les membres des comités élus font des rapports périodiques (au moins annuel) pour partager les informations et pour améliorer la gestion de leur vie associative. Les agents du WWF avec les appuis des agents de l'Etat (Service Forestier, Service Agricole et du Développement Rural) encadrent périodiquement les membres du comité dans leur fonction.

Pour les suivis de la biodiversité

Comme les membres des communautés sont formés pour la protection de la biodiversité, des techniques simplifiées pour le suivi des impacts de la conservation sont aussi diffusées. Il s'agit de la mise en place des transects d'observation des animaux et des pressions (pièges pour les animaux, coupe illicites de bois, cultures sur brûlis, …). Différents pistes / transects sont mis en place en forêt. Précédant la mise en place de ces transects, des formations sur les techniques d'observation et de remplissages des cahiers de suivi et contrôle ont été organisées. Les membres des communautés élisent des représentants pour faire des patrouilles en forêt en suivant des pistes / transects. Des rapports sont ensuite effectués pour faciliter les suivis.

Etant donné que dans certaines localités (Midongy et Ivohibe), les membres élus sont illettrés et se font toujours aider par d'autres personnes dans le rapportage, il a été constaté qu'il y avait eu beaucoup de perdition des informations. Le WWF a ainsi simplifié le cahier de suivis par des grilles (avec des gammes de chiffres) à colorer, suivis de narratifs ou non selon le niveau d'instruction des contrôleurs locaux 4 Les impacts des approches développées Il est à noter que les sensibilisations pour les transferts de gestion ont commencé en 2003 dans la localité de Midongy. Les délimitations des forêts ont débuté en 2004, et les premiers transferts de gestion de forêt ont été faits en 2007. Sur les neuf COBA étudiées, six (soit 67%) ont enregistré une diminution de la déforestation ; et trois (soit 33%) ont présenté une augmentation de taux de déforestation.

Evolution des sources de revenus des communautés de base

Les résultats des enquêtes effectuées auprès de 75 ménages dans quatre COBA ont montré une grande variation des sources de revenus des paysans. Les enquêtes ont porté sur la traduction en valeur monétaire des productions des paysans sur cinq spéculations (riz pluvial, riz irrigué, arachide, haricot, café) effectuées avant l'application des techniques agricoles diffusées par le WWF en 2006 et après la mise en pratique des spéculations. Les résultats des enquêtes avec l'application des techniques améliorées enseignées par des consultants spécialisés et les agents du WWF ont été issus des données de 2010. Le tableau suivant illustre les résultats. Les chiffres montrent dans l' ensemble une augmentation des revenus avec des grandes variations par localité. Les explications sont nombreuses mais celles constatées le plus souvent sont : les ménages appliquant dans sa totalité les pratiques améliorées enregistrent des augmentations nette de revenus ; la plupart des paysans encadrés ne veulent pas tout de suite changer leurs pratiques culturales et continuent à les appliquer avec une légère modification pour les adapter aux techniques améliorées enseignées.

Observation de nouvelles espèces craintives et augmentation du nombre de lémuriens

Pour les inventaires des lémuriens : Le WWF a commencé à travailler dans la zone en 2003. L'augmentation du nombre des espèces des lémuriens inventoriées de six à 12, montre déjà que les espèces de lémuriens sont moins craintives. Elles deviennent faciles à observer et à inventorier. A titre d'exemple, en 2003, sur les chemins forestiers empruntés par les agents du WWF pour rejoindre deux communautés voisines, s'ils n'ont pu rencontrer aucun lémurien, à partir 2008, sur ces mêmes chemins, sept à douze groupe de lémuriens sont maintenant facilement observables à une position de 2 m de et à une hauteur de 2 m du sol et plus. Les positions de ces lémuriens montrent d'après les scientifiques, une marge de confiance aux hommes (qui ne vont pas les chasser ou les tuer).

Un extrait des rapports de suivi des membres de deux COBA a aussi montré une variation moyenne des comptages lors des suivis mensuels de 16 individus de Varibolo (Hapalemurgriseus) en

Les exigences des approches et revers

Depuis l'installation de WWF à Midongy, dix ans sont déjà passés. Au cours de ces dix années, les leçons apprises sont aussi nombreuses que variées. Il y a eu des revers et, crise politique aidant, ces leçons ont permis de faire les constats suivants ayant aidé aussi le WWF à trouver des stratégies de pérennisation des actions entreprises :

Trouver des sources de financement pour des activités connexes : Conserver la biodiversité signifie également trouver des alternatives pour réduire les pressions sur elle. Dans la localité de Midongy, avant les transferts de gestion des forêts et, donc aussi la responsabilisation des COBA, les pressions et menaces sur la biodiversité étaient nombreuses. Sont cités à titre d'exemple, à part les cultures sur brûlis, le braconnage des lémuriens, la consommation des poissons et crustacés en toute saison, la croyance de tuer le Aye aye chaque qu'on le rencontre. Pour réussir à freiner ces pressions et menaces, des mobilisations de financement sont à faire. Il est en effet connu qu'une simple interdiction de chasser les lémuriens est inefficace sans que d'autres solutions pour suppléer la viande des lémuriens ne soient offertes.

Travailler en collaboration avec d'autres partenaires pour lever les ancrages profonds des coutumes ancestrales : Les bonnes pratiques en cas d'absence d'encadrement sont rapidement abandonnées annuellement au détriment des pratiques ancestrales par la majorité des membres des COBA. Pour ne citer qu'un exemple, les paysans arrêtent tout leur travail quand il y a un décès dans un village voisin. Pour eux, c'est important de montrer à la famille du défunt qu'ils compatissent avec elle et ils y viennent juste pour discuter, boire et manger pour trois jours à une semaine. Le WWF dans ce contexte a travaillé avec divers partenaires dont : les prêtres des églises pour les sensibiliser sur l'importance de travailler tout en aidant les autres pour que toute une campagne culturale ne soit pas ratée ; les Chefs Districts et maires ainsi que les autres Services étatiques présents à Midongy (Education, Santé etc).

Impliquer toutes les forces vives de la société : Dans la coutume des Antaisaka, les femmes et les enfants sont toujours relégués au second plan. Ils ne participent pas à la prise de décision dans la vie de famille. Toutefois, pour une meilleure conservation de la biodiversité, surtout pour faire démarrer les activités de développement économique, ils sont les plus assidus et fidèles à l'application des techniques améliorées. Des associations féminines sont ainsi créées au sein des communautés ainsi que des clubs informels des enfants acquis à la conservation de la biodiversité. Dans les Collège d'Enseignement Général, des clubs Vintsy formels sont créés pour la sensibilisation de leurs paires et de leurs parents sur l'importance de la biodiversité via la conservation des forêts.

Inculquer la valeur de la biodiversité à la population : La valeur de la biodiversité varie d'un individu à un autre. Il en est de même de sa valeur. Un effort continuel et, pour le long terme, devrait être engagé pour transmettre la valeur de cette biodiversité aux paysans vivant près de la forêt. Les interactions entre leur mode de vie, la durabilité de l'exploitation des ressources (sol, eau, forêt et produits forestiers) sont autant de valeur à enseigner qu'à valoriser. Nécessité d'encadrement serré et continue : Les paysans dans la localité de Midongy sont dominés par l'ethnie Antaisaka. Et, il semblerait que leur devise en dise long sur leur caractère et leur mentalité. La devise : « Antaisaka tsy mahadiny raha ela », traduit littéralement par les Antaisaka ne supportent pas attendre trop longtemps, dénote une impatience dans tout ce que le groupe ethnique entreprend. Toutefois, il est reconnu que les techniques agricoles améliorées requièrent à la fois un investissement physique un temps assez long pour obtenir des productions adéquates. Le fait que la localité de Midongy soit aussi une des plus pauvres à Madagascar, combiné avec le taux d'analphabètes élevé (70% de la population) en plus de l'enclavement de la zone, ont travaillé ensemble pour exiger un encadrement serré et continu. Toutes les valeurs à transmettre et transmises doivent ainsi être rappelées périodiquement aux paysans jusqu'à ce qu'elles soient complètement internalisées. Ceci exige un encadrement à long terme.

Conclusion

La biodiversité n'a pas de valeur que si on ne lui en donne pas. La forêt a des valeurs potentielles mais ne peut offrir plus que ce qu'elle renferme. Les paysans ont des valeurs, qu'ils respectent, parfois en contradiction avec la protection et gestion durable des ressources naturelles. Les transferts de gestion des forêts constituent un outil de sauvegarde de la biodiversité pour limiter les pratiques agricoles traditionnelles des paysans habitant près des forêts. Mais les transferts ne suffisent pas à eux seuls pour sauver la biodiversité dont les lémuriens.

Les TGRN engagés dans le District de Midongy ont eu des impacts positifs dans la conservation de la biodiversité. La forêt de basse altitude est protégée par l'existence des PAG, la communauté locale est bien encadrée depuis dix ans par la présence du WWF et des appuis financiers sous formes d'indemnités de déplacement octroyés aux représentants de l'Etat, et les lémuriens n'ont pas souffert des pressions des hommes qui ont trouvé des suppléments de protéines et alimentaires grâce au développement des techniques agricoles améliorés.

Il est pourtant admis qu'avec la crise qui a perduré depuis quatre ans, les approches développées sont précaires et ne pourront être soutenues par les agents étatiques hypothéqués comme des relèves majeurs des agents des ONG promoteurs. La communauté est dynamique et imprévisible. La présence quasi permanente des agents d'accompagnement et d'appui (soit de l'Etat, soit des ONG) est ainsi indispensable. Ceci est d' autant plus vrai que la biodiversité n'apporte pas de bénéfices directs (surtout monétaires) pouvant profiter aux paysans des COBA de Midongy. Les bénéfices indirects sont nombreux pour ne parler que des biens et services fournis par la forêt dans cette localité. Ces biens et services sont à gérer durablement pour le maintien de la vie et de la biodiversité. Le trio, forêt, communauté et lémurien pourra ainsi vivre en harmonie et durablement avec un suivi et encadrement à long terme.

REMERCIEMENTS

Nos sincères remerciements vont :

1

  Contact correspondance :

  : Le WWF a fait dresser une liste des espèces des lémuriens les plus connues par les COBA et existant dans les forêts gérées. Des primatologues sont ensuite venus plus tard pour conduire des inventaires de lémuriens dans quelques forêts des COBA assumées être les plus riches en lémuriens d'après les enquêtes informelles et la liste obtenues. Si au départ des inventaires de la faune de Midongy pour la mise en place du Parc Midongy Befotaka, en 1997, six espèces ont été répertoriées, à la fin des différents inventaires (2010), les espèces suivantes ont été notées (RAKOTONIRINA, 2006 ; RAKOTONIRINA et RAJONHSON 2010) : Avahi laniger (Fotsife) Cheirogaleus major (Tsitsidy) et/ou Cheiorgaleussp (Antsidy/Tsitsidy) ; Daubentonia madagascariensis (Aye aye) ; Eulemur collaris (Varika) ; Eulemural bocollaris (Varika) ; Hapalemur griseus (Bokombolo), Hapalemur aureus (Varibolo) ; Lepilemur microdon, Microcebus rufus et Microcebus sp ; Prolemur simus (Bokombolobe) ; et, Variecia varegata editorium (Varikandana).

4. 1

 1 Diminution de la déforestation Dans l' ensemble des neuf COBA où des images satellites ont pu être étudiées, la variation des taux de déforestation est surprenante. Les minimum et maximum de taux de déforestation enregistré entre les dates 2000 et 2005 d' une part et 2005 à 2010 d' autre part sont très variés d'une COBA à une autre. Les résultats sont groupés dans le tableau suivant pour neuf COBA.

•

  Au WWF Suède qui a financé le WWF Madagascar :  Dans le cadre de la mise en place des Transferts de Gestion des forêts à Midongy Atsimo via le Projet « Community Forestry » ;  Dans le cadre de la protection des lémuriens via deux projets : « Lemurs'project » et « Counting lemurs » ; • Au SIDA (Swedish International Development Agency) via le WWF Suède pour le projet « Sustaining life » ; • Au Service Forestier dont principalement les agents de la Direction Régionale des Forêts et du Tourisme à Atsimo Atsinanana et les agents Forestiers de Midongy. • Au staff du WWF à Midongy qui a contribué largement à la collecte des données de bases utilisées dans cet article. BIBLIOGRAPHIE Marline L., (2009). Inventaire Biologique et typologie des forêts communautaires de MarovatoMidongy Atsimo en vue d'un transfert de gestion. Mém DEA. Option Ecologie végétale Appliquée. Faculté des Sciences. Département de biologie et Ecologie végétales. Antananarivo. Rabenatoandro, T. J. , (2001). Analyse floristique, structurale et dendrométrique de la forêt dense humide de basse altitude du Parc National Masoala sur le versant occidental selon la méthode de la parcelle permanente. Mem DEA. Option Ecologie végétale. Faculté des sciences. Département de biologie et Ecologie végétales. Antananarivo.

Tableau 1 : Evolution de la déforestation dans neuf COBA à Midongy

  Les explications et les chiffres sont aussi à prendre avec prudence car ils ne représentent qu'une moyenne annuelle au cours de cinq ans.

	Plusieurs	explications	sont
	valables mais celle présentée ici (la plus
	fréquente et flagrante) est le manque
	de suivi effectué par le Service Forestier
	et les agents du WWF pendant les
	périodes cruciales.
	Certes, les membres des COBA ne
	sont pas les auteurs des causes de la
	déforestation (cultures sur brûlis ou les
	feux se propageant dans les forêts
	naturelles) mais des migrations non
	contrôlés ont toujours apparus depuis
	2009.

Tableau 2 : Moyenne des revenus des ménages par COBA Localité Nombre de ménages enquêtés Revenu moyen annuel en Ariary pour cinq spéculations Pratique traditionnelle

				Pratique améliorée
	Ambodisay	20	45,249	65,315
	Fitatsa	20	42,957	57,110
	Menatraka	15	54,926	57,110
	Maliorano	20	93,237	98,728

  une année d'observation), à 23 individus en 2013 (pour six mois d'observation) pour la COBA de Beala. Pour une autre espèce Eulemurcollaris (Varika) il a été enregistré 40 individus en 2012 (pour une année d'observation), contre 47 individus en 2013 (pour six mois d'observation) pour la COBA Vonona. Il est certes admis que des biais peuvent apparaître dans les comptages des lémuriens, car les individus ne sont pas marqués. Toutefois, ces biais sont assumés comme minimum à cause de la dextérité des membres des COBA habitués à suivre les mouvements des animaux.

	2012 (pour
	Localités	Taux de déforestation enregistré
		2000-2005	2005-2010
	Ambodisay	8.85	6.87
	Ampatramary	2.93	3.32
	BevahoAnkalatany	7.52	7.31
	Mahabe	21.94	25.65
	Marovato	4.38	7.65
	Marovovo	44.66	28.79
	Menatraka	2.00	0.97
	Tsararano	20.80	20.20
	Zaraha	18.79	15.76