Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon

Journal of Environmental Management 167 (2016) 175e184

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Journal of Environmental Management journal homepage: www.elsevier.com/locate/jenvman

Research article

Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon Pedro Walfir M. Souza-Filho a, b, *, Everaldo B. de Souza a, b, Renato O. Silva Júnior a, b,
Tasso F. Guimara ~es a, b, Wilson R. Nascimento Jr. b Breno R. Versiani de Mendonça c, Jose a, b a
Oswaldo Siqueira , Jose Roberto Dall’Agnol a b c

Vale Institute of Technology (ITV), Rua Boaventura da Silva, 955, Bel
em 66055-090, PA, Brazil
(UFPA), Geoscience Institute, Av. Augusto Correa 1, Bel
Universidade Federal do Para em 66075-110, PA, Brazil ~o, 3580, Nova Lima 34000-000, MG, Brazil Vale S.A., Planning, Intelligence and Environment, Av. de Ligaça

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 September 2015 Received in revised form 13 November 2015 Accepted 19 November 2015

Long-term human-induced impacts have significantly changed the Amazonian landscape. The most dramatic land cover and land use (LCLU) changes began in the early 1970s with the establishment of the Trans-Amazon Highway and large government projects associated with the expansion of agricultural settlement and cattle ranching, which cleared significant tropical forest cover in the areas of new and accelerated human development. Taking the changes in the LCLU over the past four decades as a basis, this study aims to determine the consequences of land cover (forest and savanna) and land use (pasturelands, mining and urban) changes on the hydroclimatology of the Itacaiúnas River watershed area of the located in the southeastern Amazon region. We analyzed a multi-decadal Landsat dataset from 1973, 1984, 1994, 2004 and 2013 and a 40-yr time series of water discharge from the Itacaiúnas River, as well as air temperature and relative humidity data over this drainage area for the same period. We employed standard Landsat image processing techniques in conjunction with a geographic object-based image analysis and multi-resolution classification approach. With the goal of detecting possible long-term trends, non-parametric ManneKendall test was applied, based on a Sen slope estimator on a 40-yr annual PREC, TMED and RH time series, considering the spatial average of the entire watershed. In the 1970s, the region was entirely covered by forest (99%) and savanna (~0.3%). Four decades later, only ~48% of the tropical forest remains, while pasturelands occupy approximately 50% of the watershed area. Moreover, in protected areas, nearly 97% of the tropical forest remains conserved, while the forest cover of non-protected areas is quite fragmented and, consequently, unevenly distributed, covering an area of only 30%. Based on observational data analysis, there is evidence that the conversion of forest cover to extensive and homogeneous pasturelands was accompanied by systematic modifications to the hydroclimatology cycle of the Itacaiúnas watershed, thus highlighting drier environmental conditions due to a rise in the region's air temperature, a decrease in the relative humidity, and an increase in river discharge. © 2015 Elsevier Ltd. All rights reserved.

Keywords: Change detection Deforestation impacts Water discharge Hydro-climate change Brazil

1. Introduction In the Amazon region, the conversion of forest to pasturelands in the modern era began in the early 1970s with the construction of the Trans-Amazon Highway (Fearnside, 2005), which resulted in opening up the forested tropical region to human settlement and

* Corresponding author. E-mail address: [email protected] (P.W.M. Souza-Filho). http://dx.doi.org/10.1016/j.jenvman.2015.11.039 0301-4797/© 2015 Elsevier Ltd. All rights reserved.

natural resource exploitation (Laurance et al., 2009). By 2006, almost 95% of all deforestation in the Brazilian Amazon occurred within 5.5 km of roadways or less than 1 km from navigable rivers (Barber et al., 2014). Hence, areas under pressure from human settlement were found primarily along official roads in the socalled “arc of deforestation”, which intersects agricultural, ecological and cultural areas along the eastern and southeastern of the Amazonian frontier. The forest-clearing process is driven by a combination of factors, primarily infrastructure, financial incentives, and immigration

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(Aldrich et al., 2012). Deforestation is also influenced by the geographical position of the arc in relation to a climatological (moist tropical to tropical wet and dry climate) and ecological (tropical rainforest to Brazilian savannah) transition zone (Coe et al., 2013). Although cattle ranching remains the dominant form of land use in the Amazon Region, large-scale commercial agriculture, such as soy bean croplands, have fundamentally changed the landscape in the southeastern Amazon (Martinelli et al., 2010; Morton et al., 2006). These LCLU changes can have a number of consequences for freshwater ecosystems, including changes in the runoff characteristics (Sajikumar and Remya, 2015), changes in river discharge (Lima et al., 2014), changes in headwater stream temperatures (Macedo et al., 2013), degrading riparian areas (Deegan et al., 2011), and changes in the hydrological cycle as a whole (D'Almeida et al., 2007; Wohl et al., 2012). These alteration processes have been responsible for dramatic changes in the Amazon rivers watersheds over the last 40 years, causing among other things greater discharge and increased sediment flux in the channels of the main rivers (Coe et al., 2011; Costa et al., 2003; Latrubesse et al., 2009). Mapping and monitoring the long-term and large-scale remote land cover and land use (LCLU) changes in the moist tropical regions has only been possible since the early 1970s with the launch of the first satellite of the Landsat series in 1972, known as the Earth Resource Technology Satellite - ERTS-1. This event began an era of Earth's surface monitoring by the “work horses” of space-borne optical data generation. Over the following decades, the moderate spatial resolution and global coverage images of the Landsat has allowed for the mapping, monitoring and assessment of LCLU changes at the local (Sonter et al., 2014), regional (Souza et al., 2013), and global scales (Hansen et al., 2013). To understand the land cover (e.g., tropical forest) and land use (e.g., pastureland) conversion processes and their impacts on regional hydroclimatology1, a detailed spatial and multi-temporal scale analysis is required. Hence, we decided to investigate these processes in the Itacaiúnas River watershed, a basin within the
s context of the Amazon catchments, which encompasses the Caraja Mineral Province, one of the largest mining provinces worldwide. We also extended our investigation to several and geographically indigenous lands and environmental protected areas (ILPAs), which are characterized as being sheltered from deforestation activities (Fig. 1). This study aims to i) assess the LCLU change using the multi-decadal Landsat dataset from 1973 to 2013, associated with increasing deforestation and pastureland activities and ii) evaluate the long-term impacts of LCLU changes on the hydroclimatology of the Itacaiúnas River watershed. The outcomes of this study will be useful to inform better management of forest and savanna ecosystems either through the creation of new protected areas, reforestation of degraded areas or increasing awareness of politicians of changes in climate in response to human activities.

2. Study area, geospatial data, remote sensing images and hydroclimate data series 2.1. Study area The present study was carried out in the Itacaiúnas River watershed that drains an area of approximately 41,300 km2 and is

1 The term “hydroclimatology” is used in the present study to express the integrated behavior of the variables of the physical environment: river water level and discharge (representing the hydrology), precipitation and air temperature and relative humidity (representing the surface climate conditions), whose observational analysis is based on historical data of 40 years.

located approximately 600 km southward of the Equator line (Fig. 1). The area, confined by the geographical coordinates are 05
100 to 07
150 S latitude and 48
370 to 51
250 W longitude, was originally covered by the Amazon rainforest and experiences a typical monsoon climate (Alvares et al., 2013). It experiences well defined rainy (November to May) and dry (June to October) seasons, with total annual precipitation range of 1800e2300 mm and averages of approximately 1550 mm during the rainy season and 350 mm during the dry season (Moraes et al., 2005).
s Mountain, The study site is marked by the Serra dos Caraja which has an altitude range of 400e900 m, in contrasts with the adjacent lands, which have altitudes ranging from 80 to 300 m. The area exposes a limited range of land covers and land uses; tropical rainforest and montane savannah initially dominated the pristine landscape, whereas pasturelands currently occupy a large part of the landscape. Moreover, in the Itacaiúnas River watershed there is a mosaic of ILPAs, which stretches across 11,700 km2, or approximately one-quarter of the total watershed area (Fig. 2).

2.2. Geospatial data, remote sensing images and field data collection To support the spatial analysis of LCLUC in the study area, GIS data layering of the Itacaiúnas River watershed was derived from the Shuttle Radar Topography Mission digital elevation model (SRTM DEM) at the Global Land Cover Facility project website (http://glcfapp.glcf.umd.edu:8080/esdi/index.jsp, accessed on 03 March 2014). Data layers on protected areas were extracted from the Chico Mendes Institute for Conservation of Biodiversity (ICMBio http://www.icmbio.gov.br/portal/biodiversidade/unidades-deconservacao/biomas-brasileiros.html, accessed on 04 April 2014). We also acquired geospatial data of indigenous land from the Brazilian Indian Foundation (FUNAI - http://www.funai.gov.br/ index.php/shape, accessed on 05 May 2014). Fig. 2 illustrates the location of ILPAs within the study site. Five mosaics of Landsat images (1973 Landsat-1 MSS, 1984 Landsat-5 TM, 1994e1995 Landsat-5 TM, 2004e2005 Landsat-5 TM, and 2013 Landsat-8 OLI) were generated and analyzed to detect LCLU changes. The mosaics were 30 m in pixel size to UTM 22S zone projection and datum WGS84. The Landsat images were obtained from the Landsat Data Continuity Mission - LDCM (http:// earthexplorer.usgs.gov; accessed on 13 May 2014) and the Catalog of image of the National Institute for Space Research - Brazil INPE (http://www.dgi.inpe.br/CDSR; accessed on16 May 2014). All 2013 Landsat-8 OLI images were converted to the Top of Atmosphere (TOA) reflectance, while the 2004, 1994 and 1984 Landsat-5 TM images were converted to ground reflectance. The 1973 Landsat MSS images were just linear enhanced. For each Landsat mosaic date, we derived the normalized difference vegetation index - NDVI to distinguish vegetated areas and bare soils (Tarpley et al., 1984; Townshend et al., 1985). Fieldwork was carried out through April and May 2014, to recognize LCLU classes using panoramic digital photographs and ground control points (GCPs), which were acquired using a differential global position system (DGPS), with reliable real-time positioning through the OmniSTAR mode for decimeter level accuracy. We collected 1060 GCPs along approximately 2400 km of local roads (Fig. 2) to validate the 2013 Landsat-8 OLI mosaic image classification. We identified three land covers classes (forest, savanna and water bodies) and three land use classes (pasturelands, mining and urban), according to the Land Cover Classification System (Di Gregorio and Jansen, 2005).

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Fig. 1. Total deforestation in Brazilian Amazonia from PRODES data (http://www.dpi.inpe.br/prodesdigital/dadosn/2014/). Most of the forest clearing has ocurred in the “arc of deforestation” in the south-southeastern Amazon region. Observe the location of the Itacaiúnas River watershed boundary in bold blue line. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

2.3. Hydroclimate data series For hydroclimatic analysis from 1973 to 2013, we used monthly mean water level (WLEV) and discharge (DISC) data recorded by the hydrological station located at Fazenda Alegria (triangle in Fig. 2) provided by the Brazilian Waters National Agency (ANA, http:// hidroweb.ana.gov.br). Hydrological measures in the Fazenda Alegria station cover an area of 38.982 km2, which represents 94.2% of the total area of the Itacaiúnas River watershed (Fig. 2). The monthly precipitation data (CPC PREC) consist of gaugebased 0.5
gridded data, which were generated through the observational data analysis system from the Climate Prediction Center (CPC), National Centers for Environmental Prediction (NCEP), USA. Further details on quality control, objective analysis and interpolation techniques used in the CPC data can be found in the work of Silva et al. (2007) and Chen et al. (2008). We also used monthly mean precipitation (PREC), air temperature (TMED) and relative humidity (RH) measured at 2 m in height, whose data collection was compiled by De Souza et al. (2009) and Lopes et al. (2013) through a consistent integration of data derived from the hydro-meteorological network of the Brazilian Institute of Meteorology (INMET), ANA and Par
a State Meteorological Center. A quality control procedure was used to check erroneous or missing data, and only those stations that had less than 5% data missing were selected for the 1973 to 2013 period. To obtain a regional climate dataset, the stations data were spatially interpolated, using the method of the inverse of the quadratic distances, into a regular grid with a 0.5
resolution covering the eastern Amazon.

(Blaschke, 2010). This approach included multi-date segmentation, a classification process based on segmentation with the extraction of object multi-date spectral signatures, multi-resolution classification using a rule set-based approach, and quantifying classification. Segmentation is the process of partitioning an image into groups of pixels that have similar numerical characteristics and are spatially adjacent, thereby minimizing the variability within the object (Baatz and Schape, 2000). The multi-resolution segmentation process includes three user-defined parameters: spectral parameter wsp to obtain spectrally homogenous objects, compactness parameter wcp that adjusts the object shape between compact objects and smooth boundaries, and scale parameter hsc that controls the object size. Different weights were used to try to enhance objects, which are well discriminated in determined spectral bands.
e The segmentation parameters wsp and wcp were set to 0.5 (Descle et al., 2006), as we are uncertain about the relative patterns between spectral bands versus shape and between compactness versus smoothness. The hsc parameter was set to 50 for Landsat-8 OLI and Landsat-5 TM multispectral bands, while for Landsat-1 MSS, the hsc parameter was set to 100 due to differences in pixel sizes. At least 90 segments were used for each class in order to extract statistical information and develop the most appropriate rule sets for multi-decadal Landsat mosaic classifications. Almost 75% of the total segments were used to define rule sets for each LCLU classes and 25% were used as independent segments to assess the accuracy of the defined rules over the entire classified mosaics (Gilani et al., 2015). A summary of the rule sets used for the LCLU classification of the study area is provided by Souza-Filho et al. (2015).

3. Methodological approach 3.1. Geographic object-based image analysis (GEOBIA) The proposed classification approach is based on GEOBIA

3.2. Classification accuracy assessment of LCLU classes We used 1060 GCPs collected during the fieldwork to run the

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Fig. 2. Landsat remote sensing dataset and ancillary geospatial data illustrated in the 2013 Landsat-8 OLI mosaic images in 6R5G4B color composite. This figure shows the location of ILPAs in the Itacaiúnas River watershed.

classification accuracy assessment of 2013 Landsat-8 OLI image. As we have no data available for old Landsat images, we used selected objects generated from image segmentation to produce thematic class map based on stratified random sampling. These objects were visually interpreted in accordance with the descriptions of LCLU classification system used in this study. Accuracy assessment of 2013 Landsat-8 OLI image classification was undertaken using confusion matrices and Kappa statistics (Congalton, 1991). Producers and Users accuracies (Story and Congalton, 1986), Kappa per class, overall accuracies, Kappa coefficient (Congalton and Green, 2009), and Tau statistics (Ma and Redmond, 1995). The results indicated that the overall accuracy, kappa and Tau index for mapping forest, montane savanna, pastureland, mining, urban and water bodies classification were 0.96, 0.94 and 0.93, respectively, using 2013 Landsat-8 OLI imagery as reference data (Souza-Filho et al., 2015).

3.3. Hydroclimatic data and analysis procedures To analyze the hydro-climate pattern over the period 1973 to 2013, an annual time series was generated for the variables CPC PREC, PREC, TMED and RH considering the spatial average within the Itacaiúnas River watershed (domain between 51W/49W and 7S/5.5S). The annual time series of the WLEV and DISC in hydrological station was also obtained from 1973 to 2013. With the goal of detecting possible long-term trends, the non-parametric

ManneKendall test based on the Sen slope estimator (Goossens and Berger, 1986) was applied to these annual time series through the investigated period. Afterwards, decadal means were calculated for the periods 1973 to 1984, 1985 to 1994, 1995 to 2004 and 2005 to 2013 to investigate the long-term variations associated with the LCLU dynamic in the Itacaiúnas River watershed. Pearson correlations were employed on these decadal time series and the evolution of the changes from forest to pastureland areas to quantify the associated impacts.

4. Results 4.1. LCLU dynamic across the itacaiúnas river watershed Deforestation in the Itacaiúnas River watershed significantly changed the LCLU over the period 1973 to 2013 in the studied area, as shown by Fig. 3. In 1973, a small area of the natural land cover was used for pastureland (32,756 ha), which corresponds to only 0.79% of the total studied watershed. However, in 1984, 1994, 2004 and 2013, pastureland occupied an area of approximately 10%, 28%, 46% and 50%, respectively, of the entire watershed, and currently, pastureland covers approximately 2 millions of hectares. Overall, approximately 2,070,607 ha of forest were cleared between 1973 and 2013, mostly due to the expansion of pastureland. Montane savanna was less affected by the land use dynamic. It occupied an area of almost 13,000 ha in 1973 that was reduced to 10,600 ha in

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Fig. 3. Classified images showing temporal and spatial variation of land cover and land use in the Itacaiúnas River watershed for the years 1973, 1984, 1994, 2004 and 2013. The black line polygon defines indigenous lands and environmental protected areas (ILPAs). ILPAs were established in the following years: SIL ¼ 1983, TANF ¼ 1989, TBR ¼ 1989, EPAIG ¼ 1989, XCIL ¼ 1991, CNF ¼ 1998, INF ¼ 1998, TAIL ¼ 2012.

2013, corresponding to a 17% decrease in area. There was no mining activity in 1973, but by 2013, mining area covered 11,719 ha, mainly,
s mining projects. In parallel, we observed the as a result of Caraja increase of urban area from 573 ha in 1973 to 13,822 ha in 2013, with more accelerated urban expansion in the last decade. Fig. 4 shows graphically the LCLU classes dynamic in the Itacaiúnas River watershed over time. In relation to annual rates of LCLU changes, it is possible to observe that from 1973 to 1984, forest areas decreased by almost 35,000 ha per year and pastureland increased at the same rate. Between the periods 1984 to 1994 and 1994 to 2004, the study site was subjected to higher rates of deforestation, with annual rates of approximately 75,000 ha, while pasturelands increased at the same rate per year. Over the last decade, deforestation rates have significantly decreased reaching ~20,000 ha per year, and this decrease in mostly related to pastureland expansion, which occurred at a rate of approximately 15,000 ha per year. With regard to montane savanna land cover change, we found that in the period 1973 to 1984 the annual loss of savanna area has reached a rate of 121 ha per year. In the following decades, 1984 to 1994 and 1994 to 2004, the annual rates decreased to approximately 20 ha per year, while between 2004 and 2013, the annual rate increased again to approximately 60 ha per year. With respect to mining areas, the annual rates show an increasing tendency of approximately

190e250 ha per year from 1973 to 2004, whereas the last decade is marked by a considerable expansion of the mining areas at a rate of almost 520 ha per year. With respect to urban expansion, the annual rate increased progressively over time, accelerating over the last 10 years (~920 ha per year), at which point the annual rate was three times higher than in the previous decade. Fig. 5 synthesizes the annual rate of land cover and land use changes over time in the study site. The annual deforestation rate within the mosaic of six indigenous land and protected areas (ILPAs) was lower than that along the outside, which exhibited a strong deforestation process in the active pastureland frontier. In general, in the ILPAs, the land cover remains almost stable compared with non-protected areas. The ILPAs encompass almost all of the preserved land cover of the Itacaiúnas River watershed. Between 1973 and 2013, less than 3% of the forest was cleared, with more than 1,126,000 ha remaining conserved (Fig. 3). During this period, the annual deforestation rate was only approximately 793 ha per year. Pastureland has increased from 124 ha in 1973 to 9700 ha in 1994. Since 2004, pastureland has occupied an area of ~26,260 ha, decreasing to ~25,500 ha in 2013, at an annual rate of ~618 ha per year. However, in non-protected areas, more than 2 million hectares of forest were cleared from 1973 to 2013, with an annual deforestation rate of ~50,000 ha per year, and peak deforestation occurred from 1984 to 1994 and 1994

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Fig. 5. Annual rate of land cover and land use changes over time. A) Forest and pastureland. B) Montane savannah, mining and urban.

75,000 ha per year (Fig. 5A e 5B). An exceptional increase in pastureland areas was observed from 1973 (~33,000 ha) to 2013 (~2 million ha). 4.2. The effects of the LCLU changes on the regional hydroclimatology

Fig. 4. Major trends of land cover and land use dynamic change from 1973 to 2013.

to 2004, when the annual deforestation rates reached almost

Pronounced interannual variability of precipitation (PREC and CPC PREC) and hydrological regime (DISC and WLEV) are observed (Fig. 6). A decrease in the relative humidity (RH) and an increase in air temperature (TMED) are observed. Positive trends (positive sign of Kendall's tau and Sen's slope) that are statistically significant at the 90% level (p-value less than 0.010) for the discharge (DISC) and river water level (WLEV) are evidenced (Table 1). A positive trend for TMED and negative trend for RH are also observed, with very high Kendall's tau that is significant at the 99% level (p-value less than 0.001). The two rainfall time series showed weak negative trend with statistical significance at the 77% level. Thus, analyzing the observational behavior of the time series (Fig. 6) and the results of the statistical test (Table 1), The changes to the hydro-climatic variables in the study watershed were clearly evident, with a notable increase in river discharge and air temperature and a reduction of atmospheric moisture. The overall effects of the four decades of changes in forest cover to pastureland on the regional hydroclimatology of the watershed as a whole are summarized in Fig. 6D, 6E and 6F. The decrease in forest cover and the increase in pastureland in the Itacaiúnas watershed can be clearly observed in Fig. 4, and the current proportion is approximately 50% for each surface coverage. Associated with the LULC dynamic for each decadal average (1973/1984, 1985/ 1994, 1995/2004 and 2005/2013), there is evidence (cf. Fig. 6D) of a systematic increase in the air temperature (TMED) from 25.5
C to 27.2
C, representing an increase in the surface air temperature of approximately 1.7
C and, in parallel, a systematic reduction in RH from 85.2 to 75.7%, corresponding to a drying of the atmosphere

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Fig. 6. A) Annual means values of Air temperature (TMED) and relative humidity (RH) from 1973 to 2013; B) forest and pastureland area in 1973, 1984, 1994, 2004 and 2013 and annual mean values of CPC precipitation (CPC PREC) and precipitation (PREC); C) annual mean values of water discharge (DISC) and water level (WLEV) from 1973 to 2013. Decadal data analysis based on the average for the periods 1973 to 1984, 1985 to 1994, 1995 to 2004 and 2005 to 2013; D) mean air temperature (TMED) and relative humidity (RH); E) CPC precipitation data (CPC PREC) and station precipitation data (PREC); and F) water discharge (DISC) and water level (WLEV). Units for each variable are shown on the y-axis. Dotted lines show linear trends.

Table 1 ManneKendall test applied on hydroclimate variables of the Itacaiúnas watershed for 1973 to 2013 annual time series. Variables

Kendall's tau

p-value

Sen's slope

DISC WLEV CPC PREC PREC TMED RH

0.287 0.287 0.002 0.129 0.717 0.622

0.009 0.009 0.889 0.234 <0.0001 <0.0001

7.039 4.222 0.009 4.760 0.060 0.343

near the surface of 9.5%. Although the decadal means of both PREC and CPC PREC data do not show clear trends (Fig. 6E), the discharge and the river water level (Fig. 6F) increased over the decades, with DISC values varying from 310 to 574 m3/s (an intensification of 264 m3/s that represents an increase of 85%) and WLEV increased from 531.2 to 684.6 cm (the river level increased 153.4 cm, representing a rise in water level approximately 29%). Complementing the analysis, we calculated the correlation between the evolution of the decadal time series of forest and pasture coverage with hydroclimate variables. Table 2 confirms the existence of a strong relationship between the decrease of forest (and increase of pasturelands) and the increase of air temperature with significant negative (positive) correlations on the order of 98% (þ98%). Relatively minor correlations were found for the other

variables, such that the increase in pastureland is associated with decreasing relative humidity (with correlations of approximately 81%) and an increased in discharge and in river water level (correlations between 88% and 85%). The relationship between the coverage and the precipitation is much weaker, with a correlation of approximately 33%. 5. Discussion Our results from GEOBIA showed that approximately 50% of the Itacaiúnas watershed remains covered with forest and a similar area was converted to pastureland. However, remaining area covered by forest, that is, only the area situated in the ILPAs domains, which corresponds to ~33% of the total area should remain effectively unchanged. Similar rates of deforestation have also been observed along the arc of deforestation (Fearnside, 2005), where the opening of major roads in the early 1970s, such as the TransAmazonian (BR-230) and PA-150 roads, and the existence of

Table 2 Correlations calculated for the decadal time series between forest, pastureland and hydroclimate variables.

Forest Pastureland

TMED

RH

WLEV

DISC

CPC PREC

PREC

0.984 0.984

0.817 0.814

0.884 0.884

0.859 0.858

0.329 0.333

0.355 0.353

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navigable rivers allowed for the initial establishment of rural settlements and extraction of timber. The deforestation process that developed along the study area is also associated with the opening of roads in the southeastern Amazon region as noted by Laurance et al. (2009) and Barber et al. (2014). The ecological consequences of this initial exploration can be observed in the 1973 classified image, expanding gradually in the subsequent decades along other roads (PA-150, PA-275, and PA279). Another point worth noting is that the deforestation occurred preferentially in larger properties with >500 ha dominated by large and very large landholders, whose properties are mostly concentrated in older areas that have better infrastructure, allowing for access to roads and markets (Godar et al., 2014). It is worth noting that during the last 40 years, the LCLU dynamic in the studied area was completely different from what occurred within ILPAs. More than 70% of the forest was cleared outside the ILPAs, while within ILPAs, almost 97% of the forest remains conserved. Hence, the Brazilian Amazon ILPAs network has established a conservation paradigm, forming large blocks of forest that act as a “green barrier” to deforestation (Nepstad et al., 2006; Soares-Filho et al., 2010). The analysis of annual and decadal climate and hydrology data of the Itacaiúnas watershed as a whole indicated that conversion of forest to extensive and homogeneous pastureland areas was accompanied by an increase in the air temperature of almost 1.7
C and a decrease in the relative humidity of approximately 9.5% over the last four decades. Although precipitation did not change significantly in the same period, the annual mean water discharge increased by 85% (P < 0.01). These results are consistent with previous studies (Coe et al., 2011; Latrubesse et al., 2009), which reported that deforestation have modified the energy balance in the Araguaia River watershed. Compared with forests, pastureland has a lower leaf canopy area, a shallower rooting zone depth, and a higher surface temperature, which leads to a reduction of evapotranspiration and infiltration, consequently increasing runoff (Costa et al., 2003; Nepstad et al., 1994). As a result, there is an increase in surface flow; thus, river water discharge almost doubled with the intensification of watershed deforestation. Furthermore, the spatial variability of soil water storage in pasturelands and forest is completely different, mainly after rainfall events in the dry season. In pasturelands, the rainfall is redistributed as local surface runoff, while in foreste areas, there was no evidence of this redistribution (Hodnett et al., 1995). Future studies can investigate the role of the LCLU changes on evapotranspiration, one of the most important applications in agricultural and forest meteorological research in arid (Valipour, 2015) and moist regions (Dias et al., 2015). Conversion of tropical forest to pasture generally produces permanent increases in streamflow (Bruijnzeel, 2004). In the southeastern Amazon, an area subject to seasonal rainfall, there will be diminished streamflow, mainly during the dry season after tropical forest clearance. This process is associated with continued exposure of bare soil (Lal, 1996), the compaction of topsoil by overgrazing (Gilmour et al., 1987), and the disappearance of soil faunal activity (Bruijnzeel, 2004) that contribute to reduced rainfall infiltration in more than 50% of the study watershed area. Due to this process, storm runoff occurs during the rainy season, causing an increase in the river water discharge. Another consequence of tropical forest conversion to pasture is related to a reduction of the soil recharging and groundwater reserves, which consequently diminishes dry season flows inevitably despite the fact that the reduced evapotranspiration associated with tropical forest clearance (Bruijnzeel, 2004). Regardless of whether a strategy of forest recover is adopted in the Itacaiúnas River watershed, there will be a negative effect on the water yield (Chappell and Tych, 2012). In other words, the

temperature and stream flow will diminish and relative humidity will increase. Conversely, a decrease in tropical forest cover will increases runoff and the associated risks of floods and soil erosion (Bruijnzeel, 2004). Over the last 10 years, Brazil has achieved an unprecedented success in reducing deforestation in the Amazon, which can clearly be observed in the study site from 2004 to 2013. It is important to emphasize that approximately 53% of Brazil's native vegetation occurs on private properties, and while the new Brazilian Forest Code grants amnesty to illegal deforesters, it creates new mechanisms for forest conservation (Soares-Filho et al., 2014). However, the agroindustrial frontier landscape in the southeastern Amazon can be considered a threat to forest conservation (Brando et al., 2013). 6. Conclusions We conclude that over the last four decades, the Itacaiúnas River watershed was subject to two different settings of LCLU changes: one marked by a successful model of a public-private partnership between Brazilian environmental agencies and a multinational mining company, leading to forest conservation inside ILPAs, and the other associated with a strong deforestation process and the formation of a new landscape dominated by pastureland. The deforestation reached 52% of the watershed area, and this change in land cover is apparently responsible for a 1.7
C increase in air temperature, a reduction of almost 10% in the air relative humidity and an 85% increase in observed water discharge in 2013 compared with a 1973 baseline. Therefore, over the last four decades, the long-term LCLU changes have significantly modified the hydroclimatology cycle of the Itacaiúnas River watershed. The creation of the mosaic of five protected areas and one indigenous land area in the western sector of the Itacaiúnas River watershed represents one of the largest forest protection achievements in the history of southeastern Amazon rainforest conservation. This is even more pertinent if we consider the location of the study site along the arc of deforestation and the existence of mining projects within the protected areas. As the pressure for changes in land cover was reduced over the last decade, the preserved rainforests inside of ILPAs play an important role in the present and future maintenance of the hydrological regime of the Itacaiúnas River watershed and in the mitigation of the climatic change impacts due to intense deforestation in the basin. The study outcomes are valuable for developing a better understanding of the relationship between LCLU changes and hydroclimatological responses in the Itacaiúnas River watershed. Moreover, this study provides a useful approach for the determination of the LCLU and of climate change from satellite images and hydrometeorological long-term data series, respectively, in regions with similar and different climate conditions. For future research, the effects of LULC changes on evapotranspiration, temperature, precipitation and streamflow should be analyzed from field measurements and model simulations considering seasonal scenarios, in order to determine the effect of LCLU changes on regional water dynamics. Acknowledgments The authors would like to thank the United States Geological Survey, Department of the Interior (USGS), for providing the Landsat-8 OLI and Landsat-5 TM images and the National (Brazilian) Institute for Space Research (INPE) for providing Landsat-1 MSS data. The authors thank the members of DIPF, GELIF, DIST, LISF, LAMSF and GABAN of Vale S.A for the field support. This project was partially carried out in the National Forest of Caraj
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