Plotting more than one regression line in ggplot

I am trying to plot, using ggplot, a series of scatter plots with regression lines for several datasets. I started with the following dataset, "onepectCO2MEDIAN". The data for this dataset is as follows:
??? onepctCO2MEDIAN
??????????????????? x????????? y
??? layer.1?? 0.000000000? 0.0000000
??? layer.2?? 0.006794447? 4.9002490
??? layer.3?? 0.014288058? 0.1608000
??? layer.4?? 0.022087920? 6.6349133
??? layer.5?? 0.030797357 -1.2429506
??? layer.6?? 0.038451072? 1.5643374
??? layer.7?? 0.048087904 -2.2659035
??? layer.8?? 0.058677729? 2.2070045
??? layer.9?? 0.069261406 -2.3677001
??? layer.10? 0.080524530 -1.0913506
??? layer.11? 0.092760246? 0.4099940
??? layer.12? 0.103789609 -0.1259727
??? layer.13? 0.116953168 -2.4138253
??? layer.14? 0.129253298? 7.0890257
??? layer.15? 0.141710050 -0.7593539
??? layer.16? 0.156002052? 0.0454416
??? layer.17? 0.170648172 -1.5349683
??? layer.18? 0.185318425? 6.5524201
??? layer.19? 0.199463055 -0.8312563
??? layer.20? 0.213513337 -2.5099183
??? layer.21? 0.228839271? 0.1365968
??? layer.22? 0.246981293 -1.3719845
??? layer.23? 0.263012767 -0.8712988
??? layer.24? 0.278505564? 0.6632584
??? layer.25? 0.293658361? 0.7938036
??? layer.26? 0.310747266? 3.4880637
??? layer.27? 0.325990349 -4.4612208
??? layer.28? 0.342517540? 0.0871734
??? layer.29? 0.362751633 -1.4171578
??? layer.30? 0.380199537 -0.9956508
??? layer.31? 0.394992948? 0.3215526
??? layer.32? 0.414373398? 3.1403866
??? layer.33? 0.430690214 -0.7376099
??? layer.34? 0.449738145 -2.4860541
??? layer.35? 0.470167458 -3.4235858
??? layer.36? 0.489019871? 0.4824748
??? layer.37? 0.507242471 -0.9785386
??? layer.38? 0.524314284? 8.5359684
??? layer.39? 0.543750525? 5.4844742
??? layer.40? 0.564234197? 3.2149367
??? layer.41? 0.583679616? 3.9168916 
??? layer.42? 0.601459444? 4.4907020
??? layer.43? 0.619924664? 6.5410410
??? layer.44? 0.639932007? 4.8068650
??? layer.45? 0.661347181? 8.1510170
??? layer.46? 0.684117317? 0.2697413
??? layer.47? 0.704829752 -0.1807501
??? layer.48? 0.725045770? 9.7181249
??? layer.49? 0.745165825? 1.5406466
??? layer.50? 0.765016139 -1.6476041
??? layer.51? 0.783461511? 4.8024603
??? layer.52? 0.806382924? 4.0421516
??? layer.53? 0.829241335? 9.3756512
??? layer.54? 0.849924415? 5.3305050
??? layer.55? 0.871352434? 7.5445803
??? layer.56? 0.893632233? 6.4679547
??? layer.57? 0.916052133? 2.8096065
??? layer.58? 0.938579470? 5.3921661
??? layer.59? 0.959907651? 7.2043689
??? layer.60? 0.981643587? 3.3350806
??? layer.61? 1.004116774? 8.8690707
??? layer.62? 1.028363466? 1.7861299
??? layer.63? 1.054009140? 6.2555038
??? layer.64? 1.072440803? 7.6079236
??? layer.65? 1.094457805? 7.6871483
??? layer.66? 1.123176277? 4.7787764
??? layer.67? 1.149430871 12.7110502
??? layer.68? 1.170912921 -0.7156284
??? layer.69? 1.196743071? 1.6490899
??? layer.70? 1.218625903? 3.0363024
??? layer.71? 1.241868377? 4.2974769
??? layer.72? 1.267941594? 1.9543778
??? layer.73? 1.290708780? 3.9986964
??? layer.74? 1.313222289? 4.5179472
??? layer.75? 1.339045882? 0.9337905
??? layer.76? 1.362803459? 3.3050770
??? layer.77? 1.384450197? 3.5422970
??? layer.78? 1.409720302? 5.9973660
??? layer.79? 1.435851157? 0.5081869
??? layer.80? 1.455592215? 7.9661630
??? layer.81? 1.479495347? 9.9460496
??? layer.82? 1.506051958? 3.7908372
??? layer.83? 1.525728464? 2.5735847
??? layer.84? 1.549362063 10.1404974
??? layer.85? 1.573440671 13.7408304
??? layer.86? 1.600278735? 0.9335771
??? layer.87? 1.623879492? 9.7588742
??? layer.88? 1.650029302? 1.2769395
??? layer.89? 1.672362328 13.4970906
??? layer.90? 1.700221121 10.2087502
??? layer.91? 1.724793375? 1.6811275
??? layer.92? 1.751070559? 6.1178992
??? layer.93? 1.778022110 -0.1567626
??? layer.94? 1.803022087? 3.8237479
??? layer.95? 1.830668867? 4.4331468
??? layer.96? 1.855736911? 5.9790707
??? layer.97? 1.882615030 11.3104333
??? layer.98? 1.909218490? 8.2142607
??? layer.99? 1.938130021 15.3209674
??? layer.100 1.963727593? 5.8178217
??? layer.101 1.993271947? 9.6004907
??? layer.102 2.022548139? 3.4063646
??? layer.103 2.050679922? 4.7375010
??? layer.104 2.078064442? 3.0133019
??? layer.105 2.104113460? 5.5659522
??? layer.106 2.133597612 12.0346333
??? layer.107 2.164026260 -0.4028320
??? layer.108 2.194852829 10.5996780
??? layer.109 2.224257946? 5.4479584
??? layer.110 2.252194643? 4.7052374
??? layer.111 2.277335048 14.0962019
??? layer.112 2.304058313? 5.7149016
??? layer.113 2.330930233? 3.7780072
??? layer.114 2.357022762? 4.4120620
??? layer.115 2.386489272? 4.1866085
??? layer.116 2.417503953? 6.9078802
??? layer.117 2.448524356? 2.7825739
??? layer.118 2.478698969? 7.6171786
??? layer.119 2.510175705 10.2410603
??? layer.120 2.539697886? 8.1820711
??? layer.121 2.567915559? 4.8275494
??? layer.122 2.597463250 19.1624883
??? layer.123 2.627518773 16.0677109
??? layer.124 2.658759236 12.5897081
??? layer.125 2.692401528? 9.2907988
??? layer.126 2.721903205? 7.4262502
??? layer.127 2.753021359? 9.3902518
??? layer.128 2.786313415 12.6193550
??? layer.129 2.819564104 11.1121040
??? layer.130 2.850823164 15.7907100
??? layer.131 2.880394101 10.7425287
??? layer.132 2.911391258? 7.7971430
??? layer.133 2.942965150? 8.8060858
??? layer.134 2.974468350 17.5606266
??? layer.135 3.008983612 17.3088605
??? layer.136 3.040015221 13.4500543
??? layer.137 3.072668672 14.6377884
??? layer.138 3.105982423? 8.0798552dput(onepctCO2MEDIAN)??? dput(onepctCO2MEDIAN)
??? structure(list(x = c(0, 0.00679444684647024, 0.014288058038801, 
??? 0.0220879195258021, 0.0307973567396402,0.0384510718286037,0.0480879042297602, 
??? 0.0586777292191982, 0.0692614056169987, 0.080524530261755,0.0927602462470531, 
??? 0.103789608925581, 0.116953168064356, 0.129253298044205, 0.141710050404072, 
??? 0.156002052128315, 0.170648172497749, 0.185318425297737, 0.199463054537773, 
??? 0.21351333707571, 0.22883927077055, 0.246981292963028, 0.263012766838074, 
??? 0.278505563735962, 0.29365836083889, 0.310747265815735, 0.325990349054337, 
??? 0.342517539858818, 0.362751632928848, 0.380199536681175, 0.39499294757843, 
??? 0.414373397827148, 0.430690214037895, 0.449738144874573, 0.470167458057404, 
??? 0.489019870758057, 0.507242470979691, 0.524314284324646, 0.543750524520874, 
??? 0.56423419713974, 0.583679616451263, 0.601459443569183, 0.619924664497375, 
??? 0.639932006597519, 0.661347180604935, 0.684117317199707, 0.704829752445221, 
??? 0.725045770406723, 0.745165824890137, 0.765016138553619, 0.783461511135101, 
??? 0.806382924318314, 0.829241335391998, 0.84992441534996, 0.871352434158325, 
??? 0.893632233142853, 0.916052132844925, 0.938579469919205, 0.959907650947571, 
??? 0.981643587350845, 1.00411677360535, 1.02836346626282, 1.05400913953781, 
??? 1.07244080305099, 1.09445780515671, 1.12317627668381, 1.14943087100983, 
??? 1.17091292142868, 1.19674307107925, 1.21862590312958, 1.24186837673187, 
??? 1.26794159412384, 1.2907087802887, 1.31322228908539, 1.33904588222504, 
??? 1.36280345916748, 1.38445019721985, 1.40972030162811, 1.43585115671158, 
??? 1.45559221506119, 1.47949534654617, 1.50605195760727, 1.52572846412659, 
??? 1.5493620634079, 1.5734406709671, 1.60027873516083, 1.62387949228287, 
??? 1.65002930164337, 1.67236232757568, 1.70022112131119, 1.72479337453842, 
??? 1.75107055902481, 1.77802211046219, 1.80302208662033, 1.83066886663437, 
??? 1.85573691129684, 1.88261502981186, 1.90921849012375, 1.93813002109528, 
??? 1.96372759342194, 1.99327194690704, 2.02254813909531, 2.05067992210388, 
??? 2.07806444168091, 2.1041134595871, 2.13359761238098, 2.16402626037598, 
??? 2.19485282897949, 2.2242579460144, 2.25219464302063, 2.27733504772186, 
??? 2.30405831336975, 2.33093023300171, 2.35702276229858, 2.38648927211761, 
??? 2.41750395298004, 2.44852435588837, 2.47869896888733, 2.51017570495605, 
??? 2.53969788551331, 2.567915558815, 2.59746325016022, 2.62751877307892, 
??? 2.65875923633575, 2.69240152835846, 2.72190320491791, 2.75302135944366, 
??? 2.78631341457367, 2.8195641040802, 2.85082316398621, 2.88039410114288, 
??? 2.91139125823975, 2.94296514987946, 2.97446835041046, 3.00898361206055, 
??? 3.04001522064209, 3.07266867160797, 3.10598242282867), y = c(0, 
??? 4.90024901723162, 0.160799993152722, 6.63491326258641, -1.24295055804536, 
??? 1.56433744259162, -2.26590352245208, 2.20700446463354, -2.36770012911069, 
??? -1.09135061899174, 0.409993989292701, -0.125972681525582, -2.41382533818026, 
??? 7.08902570153028, -0.759353880417294, 0.0454415959640926, -1.53496826259972, 
??? 6.55242014096194, -0.831256280861552, -2.50991825629084, 0.136596820654013, 
??? -1.37198445498419, -0.871298832596736, 0.663258363762466, 0.793803634291308, 
??? 3.48806373666998, -4.46122081238949, 0.0871733966938564, -1.41715777257774, 
??? -0.995650815648318, 0.32155262317503, 3.14038657369241, -0.737609879885404, 
??? -2.48605406511292, -3.423585843908, 0.482474753780281, -0.978538630093809, 
??? 8.53596837794201, 5.48447420320695, 3.21493665820644, 3.91689160157513, 
??? 4.49070195980797, 6.54104103157039, 4.80686500146557, 8.15101701282067, 
??? 0.26974132191657, -0.180750068063062, 9.71812491230244, 1.54064657400204, 
??? -1.64760408795688, 4.80246028991894, 4.04215159914344, 9.37565121768513, 
??? 5.33050496938428, 7.54458026088508, 6.46795470819342, 2.80960651433971, 
??? 5.39216613235986, 7.20436888038562, 3.3350806460997, 8.86907069895943, 
??? 1.78612988613659, 6.25550382050395, 7.60792364896564, 7.68714830528144, 
??? 4.77877638957615, 12.7110501777314, -0.715628443181046, 1.64908991824022, 
??? 3.03630240714679, 4.29747688442346, 1.95437780501881, 3.99869636910933, 
??? 4.51794724689848, 0.933790484492299, 3.30507700050003, 3.5422970157433, 
??? 5.99736597322524, 0.508186860060022, 7.96616300581067, 9.94604963036295, 
??? 3.79083717222623, 2.57358468532258, 10.1404974171776, 13.7408303595752, 
??? 0.933577123801399, 9.75887417074129, 1.27693947132921, 13.4970905965787, 
??? 10.2087501765735, 1.68112753028756, 6.1178991508927, -0.156762622680077, 
??? 3.82374791691426, 4.43314678736265, 5.97907067167507, 11.3104332518482, 
??? 8.21426074201525, 15.320967360602, 5.81782169471483, 9.6004907412354, 
??? 3.40636455909704, 4.73750103921864, 3.0133019468806, 5.56595224859066, 
??? 12.0346332527215, -0.40283199827104, 10.5996779538754, 5.44795836991128, 
??? 4.70523736412729, 14.096201892183, 5.71490161813391, 3.77800720810782, 
??? 4.41206200639436, 4.18660847858423, 6.90788020044911, 2.78257393345915, 
??? 7.61717857379431, 10.2410602647684, 8.18207106836167, 4.82754943871433, 
??? 19.1624882857155, 16.0677109398509, 12.589708067017, 9.29079879799404, 
??? 7.42625019725314, 9.39025179806185, 12.6193550331438, 11.1121039747257, 
??? 15.7907099734986, 10.7425286789233, 7.79714300307344, 8.80608578166101, 
??? 17.5606266346039, 17.3088604929222, 13.4500543478523, 14.6377884248645, 
??? 8.07985518296064)), class = "data.frame", row.names = c("layer.1", 
??? "layer.2", "layer.3", "layer.4", "layer.5", "layer.6", "layer.7", 
??? "layer.8", "layer.9", "layer.10", "layer.11", "layer.12", "layer.13", 
??? "layer.14", "layer.15", "layer.16", "layer.17", "layer.18", "layer.19", 
??? "layer.20", "layer.21", "layer.22", "layer.23", "layer.24", "layer.25", 
??? "layer.26", "layer.27", "layer.28", "layer.29", "layer.30", "layer.31", 
??? "layer.32", "layer.33", "layer.34", "layer.35", "layer.36", "layer.37", 
??? "layer.38", "layer.39", "layer.40", "layer.41", "layer.42", "layer.43", 
??? "layer.44", "layer.45", "layer.46", "layer.47", "layer.48", "layer.49", 
??? "layer.50", "layer.51", "layer.52", "layer.53", "layer.54", "layer.55", 
??? "layer.56", "layer.57", "layer.58", "layer.59", "layer.60", "layer.61", 
??? "layer.62", "layer.63", "layer.64", "layer.65", "layer.66", "layer.67", 
??? "layer.68", "layer.69", "layer.70", "layer.71", "layer.72", "layer.73", 
??? "layer.74", "layer.75", "layer.76", "layer.77", "layer.78", "layer.79", 
??? "layer.80", "layer.81", "layer.82", "layer.83", "layer.84", "layer.85", 
??? "layer.86", "layer.87", "layer.88", "layer.89", "layer.90", "layer.91", 
??? "layer.92", "layer.93", "layer.94", "layer.95", "layer.96", "layer.97", 
??? "layer.98", "layer.99", "layer.100", "layer.101", "layer.102", 
??? "layer.103", "layer.104", "layer.105", "layer.106", "layer.107", 
??? "layer.108", "layer.109", "layer.110", "layer.111", "layer.112", 
??? "layer.113", "layer.114", "layer.115", "layer.116", "layer.117", 
??? "layer.118", "layer.119", "layer.120", "layer.121", "layer.122", 
??? "layer.123", "layer.124", "layer.125", "layer.126", "layer.127", 
??? "layer.128", "layer.129", "layer.130", "layer.131", "layer.132", 
??? "layer.133", "layer.134", "layer.135", "layer.136", "layer.137", 
??? "layer.138"))
I started with the following to generate the first regression line and scatter plot:??? lm<-ggplot(onepctCO2MEDIAN) +? 
??? geom_jitter(aes(RCP1pctCO2cumulativeMedian[1:138], departurea),?? 
??? colour="blue") + geom_smooth(aes(RCP1pctCO2cumulativeMedian[1:138], 
??? departurea), method=lm) 
But I receive this error:? ??Warning message:
??? Computation failed in `stat_smooth()`:
??? 'what' must be a function or character string
A blue scatter plot is successfully generated, but the problem is that the regression line does not appear, presumably related to the above warning.
Is there a reason for this? I would appreciate any assistance!