E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
Predicting floodplain inundation and vegetation dynamics in arid wetlands
Steven G. Sandi1,*,Patricia M. Saco1, George Kuczera1, Li Wen2, Neil Saintilan3, and Jose F. Rodriguez1 1School of Engineering, University of Newcastle, Newcastle, NSW, Australia 2Science Division, NSW Office of Environment and Heritage, Sydney, NSW, Australia 3Department of Environmental Sciences, Macquarie University, North Ryde, NSW, Australia
Abstract. The Macquarie Marshes is a freshwater wetland system located in semiarid Australia. The ecological importance of this site has been recognized under the Ramsar convention. Plant associations in the marshes has shown a complex dynamic where some wetland vegetation patches have transitioned to terrestrial vegetation during severe drought, but also quickly responded to increased inflows due to record and near record rainfall accompanied by water releases from an upstream reservoir. Management decisions regarding the environmental flows require the use of predictive tools in order to assess the response of the vegetation. We have developed a vegetation response model that couples hydrodynamic modelling of the northern Macquarie Marshes with watering requirements of different plant associations and vegetation succession rules. The model simulates floods in the wetland during a series of years, after which patches of vegetation are analysed according to water depth, percent exceedance time and frequencies of inundation. During the simulated period, the patch can have adequate watering conditions, or it can have critical conditions that would lead to a succession to another type of vegetation. The predicted vegetation is reintroduced in the model, providing feedbacks for the next simulation period. In this contribution, we implemented the model to simulate changes of wetland understory during the period 1991 to 2014.
1. Introduction Floodplains and wetlands of the Murray Darling basin (Fig. 1c), one of the most productive basins in Australia, have been affected by reduced flows due to dams, earthworks and other river management structures that disconnect floodplains from the main rivers [1-3]. These effects include the reduction of water volumes delivered to wetland systems, water quality, deterioration of vegetation conditions, and reductions of breeding populations of waterbirds and fisheries [4 and references therein]. However, the effects of water diversions on wetland systems of the Murray Darling Basin have not been completely quantified and some of the impacts are undoubtedly related to the changing climate [5]. This fact is of major concern because further wetland deterioration is expected to occur under current climate change projections [6]. This contribution focusses on the development of a dynamic vegetation
* Corresponding author: [email protected]
© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
model in order to analyze the evolution of plant communities of the Macquarie Marshes, one of the most recognized environmental assets of the Murray Darling basin. Although recent investigations have greatly improved the understanding of the wetland ecosystem dynamics and addressed the necessity of predictive models to assist regulatory authorities on informed decision making [7], quantification and prediction of vegetation changes in the short and midterm under current water sharing plans and climate change projections are necessary. Our approach predicts changes in a series of patches that have been recognized to shift in vegetation state during an extended drought period and subsequent recovery after a few years of inundation. A hydrodynamic model is implemented to calculate variables of the water regime which can predict shifts in the vegetation based on minimal water requirements for various plant associations. The model was implemented to simulate changes in the vegetation extent observed during the millennium drought period that affected Australia in the 2000’s. Results show that our framework is capable of reproducing most of the changes observed in the understory vegetation of the Macquarie Marshes and it can be used to analyse future scenarios.
1.1. Study site The research focuses on the study of the vegetation of the northern Macquarie Marshes (Fig. 1). The area was chosen because it includes most of the unique vegetation communities of the marshes and because it includes the Ramsar gazetted Macquarie Marshes Nature Reserve. The water balance of the Macquarie Marshes presents a typical deficit of semiarid climates where mean rainfall values range from 400 to 500 mm annually, while evapotranspiration can reach values between 1500 and 2000 mm per year [8]. Discharge entering the system is regulated by water releases from an upstream dam. Most of the discharge that reaches the northern Macquarie Marshes is recorded at a gauging station located at Pillicawarrina (station No.421147) (Fig. 1b) with a mean annual discharge of 6m3/s, and a mean annual runoff volume of 192x106 m3 . Flows in the Macquarie River are not only irregular on a monthly scale (seasonal), but also on an interannual and interdecadal scales due to El Niño Southern Oscillation (ENSO) [8]. Additionally, in the reach from the Burrendong dam to the marshes, flows are diverted for agricultural and domestic purposes by a series of control structures such as weirs, regulators, bypass canals, earthen embankments, irrigation channels and siphons [3, 8] which contribute to the irregularity of the flows reaching the marshes. There is also a significant reduction in the discharge downstream within the Macquarie Marshes system; consequently, the northern Macquarie Marshes is the last asset within the wetland system to receive environmental flows [9]. The Macquarie Marshes are a constantly evolving wetland system that have lasted for thousands of years [10]. The site was an important settlement for the Wailwan people before European colonization, after which cattle stations and agriculture were established in the region since 1830’s and large scale irrigated agriculture started after the construction of the Burrrengdon dam in 1967 [11 and references therein]. Concerns of the effects of human intervention on the site predate the construction of the dam. As early as 1900’s, areas of the Macquarie Marshes have been protected to be used as a sanctuary for native fauna [12 and references therein]. Wetland systems located in dryland environments receive periodical floods that are key for ecological persistence [13]. After floods, wetlands show increases in productivity [14] because the flood delivers sediment and nutrients to the floodplain, it allows aquatic species to reach floodplain environments or distant waterholes, and it triggers different processes in the lifespan of some species such as waterbirds breeding cycles [13 and references therein]. After extended drought conditions in the 2000’s, deterioration of the vegetation condition of the marshes was reported [15] which lead to many patches of wetland understory vegetation
2
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018 model in order to analyze the evolution of plant communities of the Macquarie Marshes, one to undergo succession to terrestrial vegetation. Although many atches recovered after the of the most recognized environmental assets of the Murray Darling basin. Although recent rea ing of the drought in 2009 due to environmental ater delivery and record and near investigations have greatly improved the understanding of the wetland ecosystem dynamics record rainfall, the resilience of the vegetation as directly affected y the reduced and addressed the necessity of predictive models to assist regulatory authorities on informed inundation fre uency during the drought 1 , 1 . urther changes in vegetation are ex ected decision making [7], quantification and prediction of vegetation changes in the short and under current ro ections of climate change 18 , ut current studies have not een a le to midterm under current water sharing plans and climate change projections are necessary. uantify these changes. Our approach predicts changes in a series of patches that have been recognized to shift in vegetation state during an extended drought period and subsequent recovery after a few years of inundation. A hydrodynamic model is implemented to calculate variables of the water regime which can predict shifts in the vegetation based on minimal water requirements for various plant associations. The model was implemented to simulate changes in the vegetation extent observed during the millennium drought period that affected Australia in the 2000’s. Results show that our framework is capable of reproducing most of the changes observed in the understory vegetation of the Macquarie Marshes and it can be used to analyse future scenarios.
1.1. Study site The research focuses on the study of the vegetation of the northern Macquarie Marshes (Fig. 1). The area was chosen because it includes most of the unique vegetation communities of the marshes and because it includes the Ramsar gazetted Macquarie Marshes Nature Reserve. The water balance of the Macquarie Marshes presents a typical deficit of semiarid climates where mean rainfall values range from 400 to 500 mm annually, while evapotranspiration can reach values between 1500 and 2000 mm per year [8]. Discharge entering the system is regulated by water releases from an upstream dam. Most of the discharge that reaches the northern Macquarie Marshes is recorded at a gauging station located at Pillicawarrina (station No.421147) (Fig. 1b) with a mean annual discharge of 6m3/s, and a mean annual runoff volume of 192x106 m3 . Flows in the Macquarie River are not only irregular on a monthly scale (seasonal), but also on an interannual and interdecadal scales due to El Niño Southern Oscillation (ENSO) [8]. Additionally, in the reach from the Burrendong dam to the marshes, flows are diverted for agricultural and domestic purposes by a series of control structures such as weirs, regulators, bypass canals, earthen Fig. 1. a ocation of the northern ac uarie arshes in the lo er flood lain of the ac uarie iver. embankments, irrigation channels and siphons [3, 8] which contribute to the irregularity of etails of the simulated domain of the northern ac uarie arshes. c ocation of the ac uarie arshes in relation to the ac uarie iver asin and the urray arling asin. the flows reaching the marshes. There is also a significant reduction in the discharge downstream within the Macquarie Marshes system; consequently, the northern Macquarie Marshes is the last asset within the wetland system to receive environmental flows [9]. 2. Methods The Macquarie Marshes are a constantly evolving wetland system that have lasted for thousands of years [10]. The site was an important settlement for the Wailwan people before he frame or uses a hydrodynamic model to calculate daily inundation atterns of the European colonization, after which cattle stations and agriculture were established in the northern ac uarie arshes y using discharge records from gauging station o. 211 region since 1830’s and large scale irrigated agriculture started after the construction of the ig 1 . he hydrodynamic model used is a uasi t o dimensional model 19 uilt over a Burrrengdon dam in 1967 [11 and references therein]. Concerns of the effects of human s uared domain grid ith a resolution of 90x90m. erformance and cali ration of the model intervention on the site predate the construction of the dam. As early as 1900’s, areas of the as carried similarly to 20 . An im ortant limitation of the model is that is does not have Macquarie Marshes have been protected to be used as a sanctuary for native fauna [12 and infiltration or eva otrans iration modules. Additionally, during high flo s the ater enters references therein]. the domain along the flood lain so the discharge measured at station o. 211 is an Wetland systems located in dryland environments receive periodical floods that are key underestimation of the total inflo . o some extent, this fact com ensates for infiltration and for ecological persistence [13]. After floods, wetlands show increases in productivity [14] eva otrans iration. because the flood delivers sediment and nutrients to the floodplain, it allows aquatic species imulations are carried out annually as the model is mainly intended to assist on the to reach floodplain environments or distant waterholes, and it triggers different processes in current management of the site. he short term scale analysis allo s the introduction of the lifespan of some species such as waterbirds breeding cycles [13 and references therein]. feed ac from vegetation changes into the hydrodynamic model in small time ste s, After extended drought conditions in the 2000’s, deterioration of the vegetation condition of consistent ith re orted changes of understory vegetation in the site. dates are introduced the marshes was reported [15] which lead to many patches of wetland understory vegetation in the hydrodynamic model y u dating the hydraulic resistance every five years according
3
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
to vegetation changes. his consideration assumes some lag time et een the redicted change of the vegetation and the direct effects on hydraulic flo . his assum tion allo s the model to reach a certain e uili rium efore u dating all hydrodynamic resistance arameters. he vegetation model is set u on the same cell grid domain of the t o dimensional hydrodynamic model and annual simulations are carried out using hydrologic years une to ay instead of calendar years anuary to ecem er ecause ay and une re resent months of lo flo s. egetation evolution of understory s ecies is com uted from an initial o served state of the vegetation re resented as a num er of atches ith homogeneous cover of the vegetation. n this contri ution e focus on four different understory s ecies errestrial vegetation, ater couch, ommon reed, and ixed marsh. ater re uirements of these lant associations have een descri ed in terms of four varia les fre uency of inundation, timing, duration of the flood, and inundation de th 21, 22 . e th and duration of inundation are com ined as ercent exceedance curves calculated annually for every cell of the grid. he ercentage area of the atch ith ade uate atering conditions is o tained from exceedance curves calculated at every cell in the atch. he fre uency of inundation is assessed y considering thresholds of areas in the atch that resent ade uate inundation over time. he use of area thresholds as transition rules has already een discussed in revious u lications 23 2 and they are the result of com ining theoretical ater re uirements for different lant associations 21, 22 , hydrodynamic simulation of the flooding atterns in the marshes and vegetation seasonal fractional cover ma s 2 . hresholds for vegetation succession have een esta lished in terms of areas of the atch ith ade uate theoretical atering conditions and areas ith minimum inundation for maintenance three months , as suggested y the etland site management 28 . A counter is used in each atch of vegetation to trac the years in hich the hydraulic regime as elo the threshold, therefore not eing ade uate for the vegetation of the atch. f the counter reaches a critical fre uency value, a succession of understory etland vegetation to terrestrial vegetation occurs in the atch. n the other hand, etland understory vegetation can coloni e a atch of terrestrial vegetation after a se uence consecutive years ith ade uate ater conditions a ove the threshold. n this contri ution, the critical fre uency for etland vegetation succession as considered to e three years elo or a ove the threshold, ased on the availa le o served data. revious vegetation cover of the atch is given riority if recoloni ation is eing considered. he analysis of different vegetation atches sho ed consistent results ith ersistence ro a ility estimated for iver red gum and understory s ecies . hanges in the extent of the vegetation are calculated for a series of 23 years of consecutive flo s 1991 2013 . he model as tested y com aring simulated vegetation extent ith vegetation ma s of the ac uarie arshes o tained y the ffice of nvironment and eritage for the years 2008 and 2013. hanges in the s atial distri ution of overstory vegetation atches of iver red gum association and lood lain vegetation ere small in the eriod of analysis 1991 2008 and are not included in the analysis carried on this u lication.
3. Results and discussion Availa le vegetation ma s derived from aerial hotogra hy for the years 1991, 2008 1 and 2013 ere resam led to the resolution of the simulated domain 90x90 m grid and a total of 119 vegetation atches ere selected for the final setu of the vegetation model ig. 2 . egetation atches located est of the orthern y ass channel ig. 1 ere not included ecause of their relative isolation and com lex hydrodynamics, hich contri uted to underestimation of simulated floods in this articular areas of the domain. ig. 3 sho s the variation of simulated extent for four vegetation associations errestrial vegetation, ommon reed, ixed marsh and ater couch. lood lain vegetation and iver red gum
4
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018 to vegetation changes. his consideration assumes some lag time et een the redicted associations sho n in ig. 2 ere considered unchanged during this eriod, as only 1 area change of the vegetation and the direct effects on hydraulic flo . his assum tion allo s the of these associations transitioned to other s ecies. he condition of overstory s ecies is not model to reach a certain e uili rium efore u dating all hydrodynamic resistance arameters. assessed in this contri ution. he vegetation model is set u on the same cell grid domain of the t o dimensional hydrodynamic model and annual simulations are carried out using hydrologic years une to ay instead of calendar years anuary to ecem er ecause ay and une re resent months of lo flo s. egetation evolution of understory s ecies is com uted from an initial o served state of the vegetation re resented as a num er of atches ith homogeneous cover of the vegetation. n this contri ution e focus on four different understory s ecies errestrial vegetation, ater couch, ommon reed, and ixed marsh. ater re uirements of these lant associations have een descri ed in terms of four varia les fre uency of inundation, timing, duration of the flood, and inundation de th 21, 22 . e th and duration of inundation are com ined as ercent exceedance curves calculated annually for every cell of the grid. he ercentage area of the atch ith ade uate atering conditions is o tained from exceedance curves calculated at every cell in the atch. he fre uency of inundation is assessed y considering thresholds of areas in the atch that resent ade uate inundation over time. he use of area thresholds as transition rules has already een discussed in revious u lications 23 2 and they are the result of com ining theoretical ater re uirements for different lant associations 21, 22 , hydrodynamic simulation of the flooding atterns in the marshes and vegetation seasonal fractional cover ma s 2 . hresholds for vegetation succession have een esta lished in terms of areas of the atch ith ade uate theoretical atering conditions and areas ith minimum inundation for maintenance three months , as suggested y the etland site management 28 . A counter is used in each atch of vegetation to trac the years in hich the hydraulic regime as elo the threshold, therefore not eing ade uate for the vegetation of the atch. f the counter reaches a critical fre uency value, a succession of understory etland vegetation to terrestrial vegetation occurs in the atch. n the other hand, etland understory vegetation can coloni e a atch of terrestrial vegetation after a se uence consecutive years ith ade uate ater conditions a ove the threshold. n this contri ution, the critical fre uency for etland vegetation succession as considered to e three years elo or a ove the threshold, ased on the availa le o served data. revious vegetation cover of the atch is given riority if recoloni ation is eing considered. he analysis of different vegetation atches sho ed consistent results ith ersistence ro a ility estimated for iver red gum and understory s ecies . hanges in the extent of the vegetation are calculated for a series of 23 years of consecutive flo s 1991 2013 . he model as tested y com aring simulated vegetation extent ith vegetation ma s of the ac uarie arshes o tained y the ffice of nvironment and eritage for the years 2008 and 2013. hanges in the s atial distri ution of overstory vegetation atches of iver red gum association and lood lain vegetation ere small in the eriod of analysis 1991 2008 and are not included in the analysis carried on this u lication.
3. Results and discussion Availa le vegetation ma s derived from aerial hotogra hy for the years 1991, 2008 1 and 2013 ere resam led to the resolution of the simulated domain 90x90 m grid and a total of 119 vegetation atches ere selected for the final setu of the vegetation model ig. 2 . egetation atches located est of the orthern y ass channel ig. 1 ere not included ecause of their relative isolation and com lex hydrodynamics, hich contri uted Fig. 2. a, served vegetation in 2008 and 2013 res ectively. c,d imulated vegetation in 2008 and to underestimation of simulated floods in this articular areas of the domain. ig. 3 sho s 2013 res ectively. the variation of simulated extent for four vegetation associations errestrial vegetation, ommon reed, ixed marsh and ater couch. lood lain vegetation and iver red gum
5
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
An im ortant consideration in regards to the simulation of understory etland vegetation is that they corres ond to hydrologic years, hich start on une eginning of inter and end in ay end of autumn of the next year. his is ecause ay and une often have lo flo s, thus allo ing for faster s in u of the hydrodynamic model. ore im ortantly, the theoretical re uirement for inundation timing in all the vegetation associations is from s ring to summer e tem er to e ruary 21 . y considering hydrologic years, the model im licitly ca tures the influence of inundation timing and the o tained vegetation distri utions are an estimate of the vegetation at the end of the hydrologic year.
Fig. 3. imulated extent of four different vegetation associations in the ac uarie arshes and o served extents in the years 2008 and 2013 a ommon reed, ater couch, c errestrial vegetation and d ixed marsh. igs. 2 and 3 sho s atially distri uted and integrated com arisons et een modelled and o served etland vegetation distri utions. or 2008, the model redicts a good a roximation of the s atial extent of the four vegetation associations hen com ared to o served vegetation ig. 2a,c . ig. 3, sho s ho etland understory deterioration started in the northern ac uarie arshes y early 1990’s, ut the orst conditions for the vegetation ere reached during the ea of the drought 2001 2009 . imulation of ommon reed and ixed marsh extension for 2008 are consistent ith the extension re orted for that same year ig. 2a,c . or ater couch, even though the total extent as correctly simulated ig. 3 , the simulated distri ution sho some inconsistencies. he simulation incorrectly redicts a loss of the large ater couch atch located in the southern art of the domain ig. 2a,c , hile it also fails to redict the survival of small atches in the mid section. n 2013 the model redicts a higher recovery of ommon reed and ater couch atches than the o served distri ution ig 2 ,d , ith some ater couch coloni ing atches located in the northern areas of the domain and significant recoveries of ommon reed in the midsection. verall, the model as a le to re resent the deterioration of the vegetation during the drought
6
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
An im ortant consideration in regards to the simulation of understory etland vegetation er e 2000’s, eres a es la er re ery s e e a es 01 is that they corres ond to hydrologic years, hich start on une eginning of inter and a y ase e re s er e e a e e are re ar a ly a ra e end in ay end of autumn of the next year. his is ecause ay and une often have lo a r er r e e e res l s a e a e e a s e e r al flo s, thus allo ing for faster s in u of the hydrodynamic model. ore im ortantly, the re e es res l theoretical re uirement for inundation timing in all the vegetation associations is from s ring to summer e tem er to e ruary 21 . y considering hydrologic years, the model im licitly ca tures the influence of inundation timing and the o tained vegetation 4. Conclusion distri utions are an estimate of the vegetation at the end of the hydrologic year. s r a ell ra e r as e el e r e a alys s e e a a es e r er a ar e ars es e el as se s la e e e e a y a s e r er ars es during the millennium drought in the 2000’s. e el as a le a y e e a a es a e e a e e s res a er e la a y ere e e a ass a s e e s e el e s r a e e ra la e er res a er e la s e rray arl as a y a es r e e a s er re a er s ar s e ar s e ra e r e er as r a l a s r e er re l a e a e a s as ese y e a alyses e re re a e ra e assess e a ere s ales s a e a e e a as s ale y r l al el a s ales l a e a e r a a re rea es l s rea e e la s r el a e e a l e a y e e a a es
References 1 s r Ecological impacts of dams, water diversions and river management on floodplain wetlands in Australia. s ral l y 000 25 109 1 e el a s r Floodplain development & vegetation health on the Macquarie River floodplain of the Murray-Darling Basin 00 ers y e ales e el a s r Disconnecting the Floodplain: Earthworks and Their Ecological Effect on a Dryland Floodplain in the Murray-Darling Basin, Australia. er esear a l a s 01 29 0 1 a lays Australia’s Murray–Darling Basin: freshwater ecosystem conservation options in an era of climate change. ar e a res a er esear 011 62 Fig. 3. imulated extent of four different vegetation associations in the ac uarie arshes and o served extents in the years 2008 and 2013 a ommon reed, ater couch, c errestrial vegetation lays e al The status of wetlands and the predicted effects of global and d ixed marsh. climate change: the situation in Australia. a e es 01 75 1 9 Water availability in the Murray-Darling Basin. A report to the Australian igs. 2 and 3 sho s atially distri uted and integrated com arisons et een modelled Government from the CSIRO Murray-Darling Basin Sustainable Yields Project and o served etland vegetation distri utions. or 2008, the model redicts a good 00 s ral a a roximation of the s atial extent of the four vegetation associations hen com ared to e al Developing state and transition models of floodplain vegetation o served vegetation ig. 2a,c . ig. 3, sho s ho etland understory deterioration started dynamics as a tool for conservation decision-making: a case study of the Macquarie in the northern ac uarie arshes y early 1990’s, ut the orst conditions for the Marshes Ramsar wetland. r al l e l y 01 52 vegetation ere reached during the ea of the drought 2001 2009 . imulation of ommon al a esse Downstream hydrogeomorphic changes along the reed and ixed marsh extension for 2008 are consistent ith the extension re orted for that Macquarie River, southeastern Australia, leading to channel breakdown and same year ig. 2a,c . or ater couch, even though the total extent as correctly simulated floodplain wetlands. e r l y 010 118 1 ig. 3 , the simulated distri ution sho some inconsistencies. he simulation incorrectly 9 r er a Macquarie Marshes 2005/06 Environmental Flow. redicts a loss of the large ater couch atch located in the southern art of the domain ig. Responses of groundcover plants to environmental flow. Report to the Macquarie 2a,c , hile it also fails to redict the survival of small atches in the mid section. n 2013 Marshes Environmental Flow Reference Group 00 the model redicts a higher recovery of ommon reed and ater couch atches than the 10 e a esse Geomorphic environments, drainage breakdown, and o served distri ution ig 2 ,d , ith some ater couch coloni ing atches located in the channel and floodplain evolution on the lower Macquarie River, central-western northern areas of the domain and significant recoveries of ommon reed in the midsection. New South Wales. s ral a r al ar e es 009 56 s 1 verall, the model as a le to re resent the deterioration of the vegetation during the drought
7
E3S Web of Conferences 40, 02019 (2018) https://doi.org/10.1051/e3sconf/20184002019 River Flow 2018
. , Ma uari Mars s a i ir a Ma a a y sis i r a i r s a a i s. 20 0, e rtment o n ironment, lim te h nge nd ter dne . 2. erne , . nd . os ing, r u i i s a a s r a r r ar a a a arisi r a r a a r r i Murray– ar i asi a as s u y r Ma uari Mars s i us ra ia u ti onser tion rine nd resh ter os stems, 20 . 26 . 2 2 . . eigh, ., et l., u ia s ri s a a rsis i ry a ri rs a sy sis rine nd resh ter ese r h, 20 0. 61 . 0 . . un , . ., . . le , nd . . r s, u s i ri r ai sys s n di n s e i l u li tion o isheries nd u ti s ien es, . 106 . 0 2 . . o en, . nd . im son, a s i a i i a i u i i s Ma uari Mars s ai i a r r a ry r ra . 20 0, i er nd etl nds nit, e rtment o n ironment, lim te h nge nd ter, dne . . ogers, ., . l h, nd . mgr en, a r r uir s i a r y a i a a i Ma uari Mars s, in sys s s M i i Murray ar i asi u is i M ur , . intil n nd . erton, ditors. 20 0. . 0. . hom s, ., et l., u a i r s s a i u i i s Ma uari Mars s i s i ari us ra ia, in sys r s s i i Murray ar i asi . 20 0, u lishing el ourne. . 0. . , a r a ai a i i y i Ma uari as r a r r us ra ia r r , in Murray ar i asi us ai a i s r . 200 , ustr li . . . . i rdi, ., r y r i a y rau i i ourn l o n ironment l drolog , 2000. 8. 20. ndi o s, . ., et l., Ma uari ri r ai i i a i s r r y, in i r , . . hleiss, et l., ditors. 20 , ress. . 2 2 . 2 . ogers, ., a i , in ai a i a i Murray ar i asi a r a a i a uir s, . . ogers, ., ditor. 20 ustr li . . 2. 22. o erts, . nd . rston, a r r i r a a ai a s a s ur r Murray ar i asi . 20 , n err tion l ter ommission. 2 . ndi, . ., et l. a a i y a i s M r r s a r a ss s i Ma uari Mars s. in y r y a a r s ur s y siu 20 . o rt, sm ni . 2 . ndi, . ., et l., i i y rau i i ara ris i s a i a us i Ma uari Mars s, in r a i a y siu y rau i s. 20 el ourne, ustr li . 2 . ndi, . ., et l., i u a i a i s a a r i i ra i i Ma uari Mars s, in i r . 20 , ress. . 20 20 . 2 . ndi, . ., et l., r i i ri i a a i i i s i Ma uari Mars s si a y rau i r a in r r ss 20 u l um ur, l si . 2 . , as a ra i a r a sa a ri ra i si s ar r . 20 . 2 . os ing, ., r u i a i r . 20 .
8