Articles from Computational CultureSensing an Experimental Forest: ProcessingEnvironments and Distributing Relations2012-09-11 11:09:41 matthew

AbstractThe use of wireless sensor networks to study environmental phenomena is anincreasingly prevalent pract ice, and ecological applicat ions of sensors havebeen cent ral to the development of wireless sensor networks that now extendto numerous part icipatory applicat ions. How might environmental sensingprojects be understood as giving rise to new pract ices for sensingenvironmental processes, and what are the implicat ions of these newmodalit ies of sense? Working through posthuman media theory, as well asengaging with Alf red North Whiteheads approach to experience assomething that is embodied across human and more-than-human subjects,the paper considers how dist ributed sensor technologies cont ribute to newsensory processes by shif t ing the relat ions, ent it ies, occasions, andinterpret ive registers of sensing. Focusing specif ically on one environmentalsensor test site, the James Reserve in California, the paper suggests thatthese experimental environmental sensor arrangements mobilize dist inctsensing pract ices that are generat ive of new environmental abst ract ions andent it ies. How do the interpretat ive pract ices that develop throughexperimental environmental sensing then inform environmental mat ters ofconcern? What are the implicat ions of these experimental environmentalsensing arrangements as they migrate into policy, and as they informpart icipatory sensing processes?

Environmental Sensing Surrounded by the San Bernardino Nat ional Forest and situated within the SanJacinto Mountain Range in California, there is one part icular patch of woodsthat is dist inct in it s ecological processes. This forest is equipped withembedded network sensing that digitally detects and processesenvironmental phenomena, f rom microclimates to light pat terns, moisturelevels and CO2 respirat ion in soils, as well as the phenology, or seasonalt imings, of bluebirds and auditory signatures of woodpeckers. These mult iplemodes of experimental forest observat ion are part of a test site for studyingsensors in situ. A remote sensing lab, the Universit y of California JamesReserve is an ecological study area that has hosted f ield experiments since1966. The use of this ecological study area to test elect ronic sensorsdeveloped through the Center for Embedded Networked Sensing (CENS)research project is at once a cont inuat ion of experimental ecologicalpract ices that have sought to understand the mult iple environmentalprocesses in this area, as well as a shif t in the technologies and pract ices forstudying environments. The quest ion that emerges here is: when the

ecological experiment changes, how then do experiences also change?This not ion of experiment ing and experiencing as springing f rom the samemodalit y is put forward by Isabelle Stengers in her discussion of Alf red NorthWhitehead, where she coins a (French-inspired) neologism that does notdraw a clear dist inct ion between the terms experience and experiment asthere is in English. This merging of terms is also a crit ical way for describingthe approach of Whitehead, which is characterized by a crossing-over ofexperience and experiment , where experimenter and experiment are part of aunif ied and concrete occasion.1 This point of ent ry is important for thisdiscussion of sensors, as it immediately points toward a considerat ion ofsensors not as inst ruments sensing something out there, but rather asdevices for making present and interpretable dist inct t ypes of ecologicalprocesses. These processes are rendered computat ionally, and they drawtogether a wide range of experiencing ent it ies that begin to inform newarrangements of environmental sensing.The use of wireless sensor networks to study environmental phenomena is anincreasingly prevalent pract ice. Sensing projects encompass studies ofseismic act ivit y, the health of forests, maps of contaminant f low, as well asthe t racking of organisms f rom dragonf lies and turt les to seals and elephants,which provide indicat ive sensor data of environmental processes. At a t imewhen ubiquitous comput ing is extending to all aspects of everyday lif e, wherethe Internet of Things promises to have your ref rigerator communicat ing withsupermarkets, and smart cit y designs propose to harvest your locat ion datato ensure your roast -chicken dinner is prepared on t ime, sensing environmentsfor ecological study is just one set of pract ices within a larger project ofprogramming environments through dist ributed modes of computat ion. 2Sensor networks arranged over stat ic and mobile plat forms and widelydist ributed throughout environments are the common thread throughoutthese projects, but the deployment of sensors within ecological study siteshas been one of the key areas for sensor research and development .Although a range of research has been conducted on ubiquitous comput ingand the Internet of Things,3 less has been writ ten in the context of digitalmedia theory or science and technology studies about the ways in whichunderstandings and pract ices of environmental science have shif ted throughsensor systems, and how these shif t s have also had recursive ef fects onmore part icipatory sensor projects. While sensors and sensor systems wereinit ially developed for use in milit ary contexts, wireless and embedded sensorsystems have further developed through ecological study, which has in turnprovided an addit ional basis for deploying sensor systems within social mediaand cit izen-sensing contexts. 4 This paper focuses on the use of sensors forstudy in environmental science in order to begin to consider how thesesensing pract ices might inform parallel sensing pract ices.Situated within the context of these ubiquitous comput ing developments, thispaper specif ically focuses on the dist inct forms of sensing that emerge inrelat ion to monitoring environmental phenomena. One key advantage thatsensor systems are meant to provide is the abilit y to understand the complexinteract ions and relat ions within ecosystems in greater detail. Ecologicalrelat ions emerge in higher resolut ion because sensors monitor and makeavailable aspects of environmental processes as they unfold over t ime ratherthan as more discrete moments; and because more data are available forgenerat ing models of complex interact ions. But this study asks how theecologies that emerge for study through more cont inual sensor observat ionare not simply the result of increased data output and processing, but mightalso be understood as emergent sensory relat ions art iculated across humans,more-than-humans, environments and devices. In what ways do dist ributedsensor technologies cont ribute to new sensory processes by shif t ing therelat ions, ent it ies, occasions, and interpret ive registers of sensing? How dothe interpretat ive pract ices that emerge in experimental environmentalsensing then inform environmental mat ters of concern? And what are theimplicat ions of these experimental environmental sensing arrangements asthey migrate into policy, and as they inform part icipatory sensing processes?In order to consider these quest ions, I f irst give an overview of the increasinguse of sensors for monitoring environments and studying environmentalchange. The generat ion of more and higher-qualit y data is seen as crit ical todeveloping more advanced insights into how environments are t ransforming,and so the sense data produced through these projects are of ten gatheredfor the purposes of informing science and policy, in addit ion to test ingprototype computat ional technologies in the f ield. Environmental monitoringcan bring with it a sense of increased responsibilit y, and the commonly usedphrase, all eyes on earth, is a way of art iculat ing the watchful concern thatsensors are seen to embody and operat ionalize through the cont inualobservat ion of environmental processes.But sensors connect up more than just a network of human eyes or theircorrelat ive. This paper then draws on posthuman media theory to movebeyond human-cent ric interpretat ions of (computat ional) technology; andengages with Alf red North Whiteheads approach to experience as somethingthat emerges across human and more-than-human subjects. As Whiteheadsuggests, perceiving subjects are neither exclusively human nor pre-given, butcombine as feeling ent it ies through actual occasions.5 In this way, sensorsmight also be understood not as detect ing essent ial external phenomena, butas part of generat ive processes for making interpret ive acts of sensat ionpossibleand for art iculat ing emerging environments as mat ters of concern.

This is a way of saying that interpretat ion mat ters, that experience to beinterpreted emerges across mult iple registers and ent it ies; and also thatinterpretat ion is part of a processes whereby things come to mat ter asobjects of importance or relevance.6

Based on a considerat ion of the dist inct art iculat ions of sense across more-than-human and environmental processes, this paper moves to focusspecif ically on the use of embedded networked sensors at the JamesReserve ecological study site. Drawing on f ieldwork carried out at this testsite for studying sensors in situ, as well as an analysis of online records ofsensor data, I discuss new format ions of dist ributed sense that emergethrough these experimental forms of environmental sensing. Part of the wayin which sensors might be understood as operat ive within dist inct registers ofexperience is as dist ributed computat ional technologies. Sensors aredist ributed in at least two ways: both in terms of their spat ial dist ribut ion, bymonitoring environments in a widespread and localized way; and in terms ofthe dist ribut ions of experience that generate sense data and interpretat ions.7If we take seriously Whiteheads suggest ion that sensing ent it ies emergethrough experiences and that they are inseparable f rom occasions ofexperience, then how do experimental environmental sensor arrangementsmobilize dist inct sensing pract ices that are generat ive of new environmentalabst ract ions and ent it ies?8

As Whitehead suggests, abst ract ions are not separate f rom concrete things,but rather inform the process of concrescence and provide a lure forfeeling.9 The concrescences that emerge here might be understood not justas scient ists-devices-f lora-and-fauna, but also as relat ions that emergethrough data sets and algorithmic processes, across sedimentedenvironmental ef fects, and through responsive modes of ecological act ion.The coming together of an experiment then presents the possibilit y fordist inct experiences and subjects to emerge. Sensing an experimental forestis not about detect ing informat ion out there, but about tuning the subjectsand condit ions of experience to new registers of becoming, as well as newmat ters of concern. Tuning is a way to describe the co-emergence ofagencies within experiments, and the dif f icult process of developing facts ormat ters of concern within such experiments.10 This paper then sets out toprovide an understanding of the dynamic, dist ributed and mult iple modes ofcomputat ionally sensing environments that might provide insights for a morecosmopolit ical part icipat ion in sensing environments, where sensing is aprocess of tuning and experiencing that is mult i-direct ional, and involvesmult iple subjects.11

Instrumenting the EarthThe use of inst rumentat ion, f rom bird ringing to anemometers, withinecological study has a longer history than the more recent use of wirelesssensor systems.12 However, the miniaturizat ion and faster processing speedsof sensors have cont ributed to their increasing use as inst ruments withinecological study.13 Sensor systemscomposed of relat ively small-scale insitu sensors and actuators that are able to collect and t ransmit data throughwireless connect ions, as well as undergo remote reprogramminghave beendescribed as nothing less than another revolut ion on par with the rise of theInternet .14 These imagined and actual t ransformat ions involve extendingcomputat ional capacit ies to environments through sensors, where objectsand phenomena are t ransformed into sensor data and made manageablethrough those same computat ional architectures.In related lit erature, wireless sensor networks have also been described as arevolut ion in scient if ic inst rumentat ion, similar to the telescope andmicroscope, where a new order of insights might be realized. But instead ofprobing outer or inner space, sensor networks are seen to operate asmacroscopes, which enable a new way to perceive complex interact ionsthrough the high densit y and resolut ion of temporal and spat ial monitoringdata.15 While issues related to providing a reliable power source, ensuring therobustness of hardware, and maintaining the validit y and manageabilit y oflarge data sets remain, sensor systems are seen to present the possibilit y forunderstanding environmental processes and relat ions more thoroughly byproviding records and real-t ime data that are more detailed than exist ingmodes of data collect ion, including remotely sensed and manually gathereddata that may be at a much larger scale or more discrete moments in t ime. Abackground of relat ions may then be connected up and made evident throughthese sensing devices.A wide range and number of projects now employ sensors for environmentalmonitoring, f rom bird migrat ion and nest ing to the social lif e of badgers, andf rom water qualit y monitoring to phenological observat ions, as well asacoust ic sampling of volcanic erupt ions and monitoring of microclimates inredwood forests.16 One of the key projects within sensor systemsdevelopmenta 2003 study of Leachs Storm Pet rels at Great Duck Island, awildlif e preserve in Maineestablished that habitat and environmentalmonitoring is a driving applicat ion for wireless sensor networks.17 This sensorproject employed stat ic sensor nodes and patches, with burrow motes andweather motesor sensor nodesto study the underground nest ingpat terns of migrat ing birds. As with many similar and subsequent sensordeployments, this project generated more detailed data on previouslyunobserved ecological phenomena and relat ionships, while also providing atestbed for experiment ing with the system architecture of sensor networks.The ecological relat ionships observedor sensedare in many ways coupled

with the capacit ies of sensor networks, which similarly are adapted to andlearn f rom the processes under study. The tuning of sensor networks maythen take place not just between scient ists and devices, but also betweendevices, code and ecological processes.At the same t ime that sensor observat ions are intended to provide moredetailed renderings of phenomena on the ground, they also cont ribute tomult i-scalar and widely dist ributed approaches to environmental sensing,including remote sensing by satellit es and airborne observat ions. Mult ipleobservatories, together with long-term ecological research sites (LTERs),and the U.S. Nat ional Ecological Observatory Network (NEON), which at temptsto synthesize sensor data across the United States, collect and provideongoing sensing data, of ten across scales and f rom diverse modes of sensorinput for wider and more detailed views on environmental processes and tostudy the ef fects and possible impacts of environmental change.18 While asite-specif ic sensor project may study the detailed relat ionship betweenbirds nest ing behavior in relat ion to microclimate and mult iple otherenvironmental factors, this same study may benef it f rom climate dataresources or may cont ribute to climate monitoring programs. The sense datagathered may have the potent ial to elucidate environmental relat ions within apart icular area of study, as well as across expanded and yet -to-be-gathereddata setsas long as the data to be compared are of compat ible formats.Just as sensing systems are proliferat ing, numerous at tempts are thenunderway to amalgamate and make sense of the many forms of dataa keycyberinf rast ructure tasksince the mult iple formats and provenances ofdata may mean that they are rendered meaningless for ongoing use andstudy if not consistent ly handled.19 Sensor-gathered data sets, which aretypically heterogeneous, are increasingly brought together not just in largerdata networks, but also in mapping plat forms where f ine-grain sensor dataprovides a ground-t ruth to coarser remote-sensing and f ield-gathered data.From Microsof t s SenseWeb to the DIY sensing plat form Cosm (formerlyPachube), such plat forms intend to consolidate environmental sensorinputs.20 The range of possible sensor inputs is illust rated by one Microsof tgraphic, Inst rument ing the Earth, which out lines twenty dif ferent modes ofsensor input , f rom snow hydrology and avalanche probes to cit izen-suppliedobservat ions and weather stat ions.21 Innumerable potent ial points andprocesses in the environment become the basis for sensor input , and it isf rom these delineated sites of input that newly observed relat ions might bestudied, art iculated or managed.While these sensing projects and networks have been under developmentwithin universit ies and public inst itut ions, technology companies workingindividually or of ten in collaborat ion with universit ies are developing a wholerange of sensor network systems. These projects range f rom Nokias SensorPlanet , to IBMs A Smarter Planet , HP Labs Cent ral Nervous System for theEarth (CeNSE), and Ciscos Planetary Skin (in collaborat ion with NASA, theUniversit y of Minnesota, Imperial College, and others).22 Governments andtheir milit aries are also invest ing in the development of sensor networks, withwhitepapers and research issuing f rom the EU, China, and the US DARPA,among others.23 Many of these sensing projects raise ethical issues relatedto surveillance, while st ill other projects are enabling new forms of resourceexploitat ion. The project of monitoring and managing environmentalrelat ionships cont inues to be a way in which the governmentalit yand evenenvironmentalit yof sensor systems unfolds, where sensor capacit ies maypoint toward part icular relat ions to manage or sustain in dist inct ways.24

All together, these environmental sensing systems variously undertake aproject of inst rument ing or programming the Earth.25 Within a sensor-ecologyimaginary, the planet might be understood as an ent it y to be sensed andt ransformed into data. Improved sensing capabilit ies have come to be seenas crit ical to advancing understandings of environmental change, while alsoindicat ing ways of act ing (whether through automated systems orenvironmental policy) in response to that data. With small-scale, dist ributedand pervasive computat ion embedded in environments, new relat ionships notjust to studying, but also to managing environments emerge, since sensorsystems computat ionally describe and capture environmental processes,while also providing the promise to design and cont rol these complexsystems.26 On the one hand the argument here is that increased amounts ofdata about environments allow for the greater management of environments.Data are descript ive measures capturing environmental t ransformat ions outthere. But f rom a Whitehead-inf luenced perspect ive, it could be argued thatsense data are less descript ive of pre-exist ing condit ions, and moreproduct ive of new environments, ent it ies and occasions of sense. The ways inwhich phenomena are delineated as sense data are one part of this operat ionof becoming sensible, but the ways in which sensory monitoring gives rise tonew format ions of sense within and through data and computat ional modesof relat ing as well as across humans, more-than-humans and environmentsalso mobilize dist inct dist ribut ions of sense. Since sensor networks are seento of fer dist inct insights into the complex interact ions and processes withinenvironments, then the ways in which these relat ionships are joined up,art iculated, and t ransformed into new observat ional capacit ies mat ters.27

Distributing SenseThe init ial developments of ubiquitous comput ing are of ten at t ributed to MarkWeisers 1991 suggest ion for computat ion to move f rom desktops to theenvironment , so that computat ional processes would become a more

integrated and invisible part of everyday lif e.28 Yet another possible referencepoint could be Alan Turings 1948 ruminat ions on how to build intelligentmachinery with sensing capacit ies on par with humans. Turing reviews theopt ions for such a project , f irst considering how to atomize every part of thehuman ensemble and replace it with equivalent machinery. Emulat ing humanvision, speech, hearing and mobilit y, such a cont rapt ion would includetelevision cameras, microphones, loudspeakers, wheels and handling servo-mechanisms as well as some sort of elect ronic brain.29 This project wouldinevitably be of immense size, Turing notes, even if the brain part werestat ionary and cont rolled the body f rom a distance. But data would not enterthe thinking machine through it s remaining stat ic, and so in order that themachine should have a chance of f inding things out for it self it should beallowed to roam the count ryside. But in such a scenario the danger to theordinary cit izen would be serious. Add to this all of the usual act ivit ies ofhuman interest , and such a machine would be altogether unwieldy. Turingsmore pract ical recommendat ion is to behead the body, to work with the brainas the crit ical site of processing, and later at tend to the sensory apparatus.30

Even if Turings proposal does consolidate the thinking machine into a cent raland seemingly Cartesian apparatus, his thought experiment on the sensingbody in pieces and dist ributed throughout the count ryside remains a potentf igure for ubiquitous comput ing. What is st riking about Turings example is theway in which the thinking machine even when dist ributed would emulate thehuman body, which serves as a template for understanding how sensory datawould be captured and cent rally computed. While computat ional sensingtechnology can now be understood as more than a double of or prosthesis forthe human sensing body, Turings f igure of the body in pieces raisesquest ions about how part icular dist ribut ions of sense might reconf igure thesites and processes of sensat ion. Could such dist ribut ions of sense pointtoward modes of sensat ion where computat ion reassembles not as a singularsensing subject , but rather as a processual and mult i-located experiencecomprised of numerous sensing ent it ies? In this way, sensing also assemblesnot as a mental or cognit ive operat ion, but as an environmental and relat ionalart iculat ion across mult iple bodies and sites of sensing.31 Within Turingsexample of the sensing body in pieces, this could mean that we at tend not tohow the body might reassemble toward human percept ion and funct ionalit y,but rather to how the count ryside and the many inhabitants, processes andprocessors of this dist ributed and dist ribut ive milieu begin to rework how thethinking-sensing machine captures, conf igures and acts upon it s inputs.Perception in the worldTurings dist ributed sensing apparatus then points to the dist ributedprocesses that make sensing possible, even if the sites of sensat ion do notreturn to a coherent human processor. Indeed, as Whitehead suggests,percept ion might be understood to be in the world and dist ributed throughinnumerable nonhuman processesit is not the special preserve of a humandecoding subject . Instead, mult iple part icipants unfold a dist inct experience ofthe world, independent ly but contemporaneously within an immanent series ofevents.32 At the same t ime, the excitat ions of environments are fused to allmodes of mat ter, where the environment with it s peculiarit ies seeps into thegroup-agitat ions which we term mat ter, and the group-agitat ions extend theircharacter to the environment .33 There are numberless living things,Whitehead writes, that show every sign of taking account of theirenvironment . 34 This taking account of environments is a way of capturingwhat is relevant , and through being af fected also t ransforming environmentsand relat ions.Sense data might be seen as a concrescence of mult iple ways of takingaccount of environments, whether through researchers or devices orenvironmental events. But these data are necessarily art iculat ions of theways in which environments are gathered and expressed through varyingsubjectshere, with subjects understood in the broadest possible way.Sensing systems generate dist inct art iculat ions of environmental relat ionswithin and through data and across sensing subjects/superjects. Rather thantake on a Kant ian view of how the world emerges f rom the subject ,Whitehead with his philosophy of organism seeks to understand how thesubject emerges f rom the world, thereby const itut ing a superject , or asubject that is always cont ingent upon actual occasions and experience.35 AsSteven Shaviro notes in relat ion to Whitehead:

There is always a subject , though not necessarily a human one.Even a rock and for that mat ter even an elect ron hasexperiences, and must be considered a subject /superject to acertain extent . A falling rock feels, or perceives, the gravitat ionalf ield of the earth. The rock isnt conscious, of course; but it isaf fected by the earth, and this being-af fected is it s experience.

36

Sensor technologies are const itut ive of sensethey too experience theworld and generate percept ive capacit ies. 37 Sensors that map in real-t ime agreater densit y of ecological relat ions could be seen as an at tempt to workthrough a processual approach to environments, by focusing on interact ionsand even mult iple modes of percept ion. At the same t ime, to ident if y aphenomenon as const itut ing sense data is to make a commitment to dist inctforms of process, so that environmental processes are selected andconcret ized in those forms. The process of select ing sense data involvescapturing a moment in t ime, an instant , that is then re-sutured with other

data to form a pat tern of any given ecological process. While approximat ing amore process-based and even real-t ime monitoring of environments, sensorsare also product ive of pract ices of select ing and interrelat ing discreteobservat ions in order to arrive at an understanding of environmental process.The select ion of temperature, vibrat ion, light levels, humidit y, and othermeasurements across primarily physical, although to some extent chemicaland biological criteria, informs the instants that are sensed, the forms thatare documented, and the processes that might be reconf igured.The basis for developing facts within the sensing experiment then direct lypertains to the forms and processes of experience that are generated andconnected up across sensing subjects.38 The emergence of data alsorequires subjects that can produce and parse this data. Subjects may beat tuned or resistant to receiving data based on prior or emergentexperiences. But data and the means of gathering data may also cont ributeto the possibilit ies for processing and integrat ing data. In this way, sense datamay be generat ive of a superject where the experiences and percept ionsgenerated are in turn format ive of the subjects that experience. This runscounter to the not ion that a founding subject is the ent it y that experiences. If ,as Whitehead suggests, subjects are always superjects, then subjects arealways necessarily dist ributed and emergent in relat ion to actual occasions.39

Approaches to media and sensat ion of ten focus on the ways in whichtechnologies t rain or otherwise at tune the human senses within a mediatory orprosthet ic relat ion. But the interact ions and processes of sense are arguablynot f ixed within sensory organs or technologies through which mediat ions aretypically understood to take place. In this way, sensat ion is not primarily aninquiry into the relat ions between human subjects as they perceive nonhumanobjects. Instead, the sensory relat ions within which sensors are mobilized giverise to a more ontogenet ic understanding of percept ion, where sense andexpressions of percept ion are art iculated processually and across mult iplesites and subjects of emergent sensat ion. In this way, new perceptualengagements are dist ributed across sensing capacit ies and engagements(perhaps similar to what Luciana Parisi has called technoecologies ofsensat ion), which give rise to dist inct sensory processes, informat ional-material arrangements, and aesthet ico-polit ical possibilit ies.40

Such a condit ion resonates with what Pat ricia Clough refers to as theimportance of focusing on an empiricism of sensat ion, rather than anempiricism of the senses41 Technologies, including sensor systems, can beunderstood as generat ive ontologies that inform the experience andcondit ions that make sensat ion possible and changeable. Rather thanstudying the senses as given, it may be more relevant to study experienceand how dist inct t ypes of sensat ion become possible, and to consider furtherwhat modes of part icipat ion and relat ion these processes of sensat ionfacilit ate or limit . To bring this analysis back to sensor technologies, sensedata are not simply items to be read and gathered as machinic observat ionsof environments that scient ists process. Instead, sense data are indicat ionsof a process of becoming sensible, where environments, humans and more-than-humans emerge as perceiving and perceivable ent it ies.Collaborative sensingThe modes of sensing that emerge within the context of ecological sensorapplicat ions might then begin to be described as collaborat ive sensingpract ices taking place across mult iple subjects and through dist inct processesof experience. On the one hand, these more emergent modes of sensingmight be referred to as t ypes of int imate sensing, as Stefan Helmreich hassuggested in relat ion to f ieldwork undertaken with oceanographers whoemploy a complex array of sensing technologies in their research. Sensing, inthis account , is comprised of a research ecosystem, and involves much morethan a device focused on an object of study, since bodies enter into a circuitof sensat ion with inst rumentat ion technologies. As Helmreich writes, Thesescient ists see themselves as involved not so much in remote sensing as inint imate sensing. Mult iple forms of sensing emerge, across dif ferenttechnologies and researchers involved in studying ocean ecologies: Themediat ions are mult iple and so are the selves. 42 Inf luenced by CharlesGoodwins discussion of how forms of collaborat ive seeing emerge within thespace of a scient if ic vessel, 43 Helmreich develops an analysis of the sensingprocesses that becomes concret ized and embodied within these body-environment -technology relat ionships, where new registers of feeling mayeven emerge through the repeated engagement with these devices. Themult iple selves to which Helmreich refers most f requent ly refer back toscient ists and crew members on ocean sensing expedit ions, but by extendingapproach through a Whitehead-oriented understanding of experience it ispossible to include even more expanded collaborat ive format ions of sense.The experiences provided by and through more-than-human processes, aswell as the processes that unfold within sense data, inform a dif ferentapproach to what might const itute collaborat ive modes of sensing.Within the emerging area of posthuman media theory, sensat ion isincreasingly understood as dist ributed in and through more-than-humans inthe form of organisms and technologies, together with their environments. Att imes informed by Michel Foucault s well-known death-of -man statement ,media scholars as far-ranging as Friedrich Kit t ler and Katherine Hayles, as wellas Jussi Parikka and Mat thew Fuller, have in dif ferent ways undertakenanalyses of media that dispense with an assumed human subject as theprincipal site of meaning-making in order to recast the relat ions that emergein and through media technologies.44 As Hayles suggests, environmental

modes of computat ionRFID in her analysisraise quest ions about theef fects of creat ing an animate environment with agent ial and communicat ivepowers. Such technologies allow us to move toward a more processual,relat ional and accurate view of embodied human act ion in complexenvironments.45 Not just sensing, but also what counts as the human shif t sin these scenarios, since computat ional technologies t ypically now operatewithin parallel processes, and signal toward a mult iplicat ion rather than acentering of selves.46

The selves that might be discussed as parallel, mult iple, or collaborat ivewithin environmental sensing then extend not just to ent it ies mult iplied throughnonhuman technologies, but also to the incorporat ion of nonhuman f lora andfauna. Posthuman theories of subjectsor ecological approaches to subjectsare becoming increasingly well-established not just in media theory but alsoin philosophy and feminist studies, part icularly as art iculated in the work ofRosi Braidot t i, who develops these not ions through the work of Deleuze andGuat tari (with an emphasis on the not ions of ecology developed by Guat tari).Making a case for the importance of posthuman and f lat ontologies ofsubjects, Braidot t i suggests that we begin to work with an environmentallybound subject that is also a collect ive ent it y because an embodied ent it yfeeds upon, incorporates and t ransform it s (natural, social, human, ortechnological) environment constant ly.47 In this account , bodies and subjectsare even understood as collect ive informat ion machines of sorts. ForBraidot t i, t echno-bodies may be understood as sensors, or integrated sitesof informat ion networks; vectors of mult iple informat ion systems.48

Such an ecological approach to subjects resonates with Whiteheadsdiscussion of subjects/superjects, where bodies-as-sensors are expressiveand product ive of environments. The sensing that takes places is a pract iceof processing and t ransforming. If human bodies are sensors, then byextension so too are the mult iple more-than-humans that take in, express andt ransform environments. With these mult iple format ions of experience now atplay across human and more-than-human subjects, it is then relevant to turntoward the specif ic dist ribut ion of environmental sensor networks in theJames Reserve to consider how sensors are expressive of environments,what new environments and subjects emerge as experiencing ent it ies, andhow the sensing experiment is conducive to making these experiencespossible.

Sensing an Experimental Forest Returning now to a more detailed discussion of one embedded sensornetwork project , the CENS sensor installat ions at the James Reserve forest , Iconsider how this analysis of dist ributed sensing might be put to work in thecontext of this experimental project and test site. The CENS init iat ive is oneof many sensor developments as discussed previously, and it is a well-knownand f requent ly cited project for sensor research. Established in 2002 as a

Nat ional Science Foundat ion Science and Technology Center, the CENSproject is a collaborat ion between several California-based universit ies. Theproject , which f inished in 2012, focuses on four key areas of research, includingTerrest rial Ecology Observing Systems (TEOS); Contaminant T ransport andManagement ; Aquat ic Microbial Observing Systems; and Seismology. A f if tharea of research, Part icipatory Sensing, has grown out of the project researchinto ecology and focused on how sensor applicat ions may be used for cit izenengagement in environmental and social issues.49 This discussion focuses onthe TEOS sensing deployments, which are primarily situated at the JamesReserve (while the other study areas are located in a diverse range of sites).Part icipatory Sensing is a further area that I brief ly address in the conclusionto this discussion.The James Reserve ecological study site is in many ways an environment fordeveloping experimental pract ices as well as for t ransport ing laboratorytechniques into the wild. The f ieldwork that I conducted at the JamesReserve also moved f rom the laboratory to the f ield, as I f irst visited theCENS laboratory at UCLA where most of the sensor prototypes weredeveloped, and then observed the sensors at work in situ at James Reserve. Iheld informal interviews with researchers involved in the CENS project ,mapped the dif ferent locat ions and funct ions of sensors in the f ield at JamesReserve, and compared the online records of sense data with the sites wheresensors were installed. However, this is not a project of f ollowing thescient ists, which is by a now a well-established area within science andtechnology studies.50 Instead, through f ieldwork and within this paper Iat tempt to understand emerging processes and sites of sensing as theyintersect with ecological pract ice and cultures of computat ion. Rather thanfocus exclusively on how ecologists use sensors to obtain scient if ic meaningor generate data or facts, I concent rate on James Reserve as a part icularecological research site, which emerges through a dist ribut ion of sensingprocesses across organisms, ecological processes, sensing technologies inthe form of computat ional hardware and sof tware, online interfaces,conservat ion inf rast ructures, resident scient ists, environmental change,cit izen scient ists, publics, and visit ing researchers.The nearly 12-hectare and 1640-meter-high site is characterized by a complexintersect ion of ecosystems, including montane mixed conifer and oak forest ,montane chaparral, wet and dry meadows, montane riparian forest , aperennial st ream, and an art if icial lake.51 Since James Reserve is located in arelat ively remote wilderness set t ing, it is ef fect ively of f the grid, and is astudy area that generates it s own solar power and has it s own well for water.In this sensing lab or experimental forest , inf rast ructures are realigned, not asobvious allocat ions of roads, elect ricit y and water, but rather as newarrangements of energy, sensat ion and observat ion. Sensing in the JamesReserve is dist ributed not just across this experimental site, and at dist inctlocat ions for the study of ecological processes, but also across larger sensornetworks. Many of the CENS James Reserve sensors are measuringphenomena over t ime, and enable researchers to study sequences of datathat are f ine-grained and relat ively cont inuous in comparison to more discretedata sets, with data captures taking place in localized set t ings as f requent lyas every 15 minutes. St ill other sensor test beds are in place to connect up tolarger networks, including the Nat ional Ecological Observatory Network(NEON). Observat ions are successively gathered and joined up in far-reachingnetworks, such that sense data becomes an amalgamated and comparat ivenetworked inf rast ructure of ecological observatories for studyingenvironments and environmental change.CENS sensor systems are then developed and deployed within a largerproject of collect ing detailed data in order to respond more ef fect ively toenvironmental challenges. Higher-resolut ion data promises to generate moreef fect ive models for predict ing and managing environmental events. This newmechanist ic understanding of the environment involves a near-futurecommitment to developing a crit ical inf rast ructure resource for society in theform of detailed environmental monitoring.52 The promise to respond tocrises more ef fect ively develops not just through larger data sets, but alsothrough more detailed data-gathering that is bet ter tuned to detect inganomalies and ext reme events, since most ecological data has largelyconsisted of document ing ecological condit ions within a logic of averages andgeneralit ies. However, data expressive of average condit ions do not capturethe ef fects that major if singular disrupt ive events have on environments andrapidly shif t ing ecological relat ions and processes.53 CENS and relatedprojects such as NEON are then oriented toward the object ives of monitoringchanging environmental processes, where an increasing number ofdisturbance events due to environmental change are cont ribut ing to the needto develop dif ferent pract ices and technologies for sensing environments.The expression and agitat ion of environments, which as Whitehead suggestsseep into all things, also turn up in and t ransform the sensing pract ices andtechnologies that monitor them. Inst ruments for capturing sense data arehere specif ically honed toward disturbance, as environmental changebecomes more of a mat ter of concern within ecological study. At the samet ime, disturbance-detect ion rather than observat ion of norms begins toinform what counts as relevant sense data.Machine ecologiesThe sensors at work in the James Reserve within the TEOS group of researchprojects consist of everything f rom soil sensors that detect moisture levels; aRhizot ron installat ion of tubes that allows robot ic cameras to capture imagesof root growth and CO2 sensors at three dif ferent soil depths to est imate soil

f lux; a bird-audio system involving sonic booms t riggered by camera act ivit yto capture woodpecker auditory data; weather stat ions for gaugingmicroclimat ic condit ions; t ree sap f low sensor systems; nest boxes withcameras and audio installed within bird boxes; pan-t ilt -zoom tower camerason 30-foot tall poles; and a MossCam web camera. At the t ime of thisf ieldwork, there were over 550 connected and untethered sensor nodes, aswell as reconf igurable robot ic mobile sensors working above and belowground, within waterways and across t rees, capturing data on plants, animals,birds, soil, microclimate and more.54 Sensor observat ions provide the abilit y toobserve fungal growth pat terns, soil CO2 product ion, the t imes at whichplants shut down their CO2 f ixing, and all manner of plant , animal and birdact ivit y that t ypically takes place outside the scope of direct humanobservat ion.55

The init ial proposal for this project made a bid to develop dist ributedsensor/actuator networks [that ] will enable cont inual spat ially-denseobservat ion (and ult imately, manipulat ion) of biological, environmental, andart if icial systems.56 Mid-way through the project , many of the init ial proposalsfor comprehensively dist ribut ing a large number of small sensors within anarea of study shif ted to a pract ice of st rategically deploying sensors inprecise locat ions to study specif ic ecological act ivit ies, and developing ahierarchy of sensing plat forms that span f rom small-scale motes to largersenses such as imaging robots on cables.57 The sensor pract ices andarrangements developed in the James Reserve context are specif icresponses to site condit ions and processes, so that phenomena to beobserved have come to inform which sensors will be used and how. Thispoints to a key aspect of the sensor systems: they are almost alwaysphysically proximate to that which they monitor. Sensors are dist ributed in theenvironment , and networks are developed and paired with environments.58Sensors in the f ield at James Reserve are wrapped around t ree t runks in aconcatenat ion of foil and cables; they are interspersed in the ground asarrays at regular intervals; and they are clustered at bird boxes to cross-correlate microclimate in relat ion to nest ing at dist inct locat ions.The ways in which sensors are paired with environments are not a simplemirroring, however. Sensors proximate to roots and soil, for instance, do notst ream all possible data all the t ime. Instead, sensor motes within a networktalk to each other to coordinate data detected, processed and sentaccording to dist inct algorithms. Part of this conf igurat ion has to do withenergy ef f iciency, where motes are t riggered to record events only at selectt imes and are turned of f during t imes of inact ivit y to save energy. Indeed, akey aspect of imagining the possibilit ies of sensors as environmental systemsinvolves thinking through how it may be possible to realize pervasive sensingwithout pervasive inf rast ructure,59 which primarily means not requiring acent ral elect rical grid for power. The sensors at James Reserve are in partpowered by a solar array that is the primary source of energy to power thiselaborate sensing lab, which is supplemented by bat teries, includingmotorcycle bat teries, for dist inct devices that t ypically t ransmit their sensorydata via wireless connect ions.Part of the algorithmic processing of sensor data then involves set t ingsensors to pick up, f ilt er and amalgamate data within established ranges. Theprocessing that sensors undertake is ad hoc and in situ, rather than acont inual capturing and st reaming of environmental act ivit y. Each mote withina network is already set to detect some things and not others, to makecorrelat ions among certain data criteria, and to discard anomalies andredundancies according to predetermined phenomenal ranges. Sensor motesdetect events within a specif ic range, and then process and communicate thisdata across short distances or hops to other sensors within the network forcollect ion at sensor nodes. Data are t ypically fused and processed at eachindividual mote in order to make real-t ime st reaming more ef f icient andef fect ive.While sensors are physically proximate to what they sense, that which issensed and communicated t ravels through channels of algorithmic detect ionand processing. While on the one hand sensor applicat ions are intended torecord ext reme events and anomalies, the algorithms that capture data havea tendency to smooth and fuse data at source in order to conserve energyand generate manageable quant it ies of data, which even with these f ilt eringmechanisms can easily run to several million records per year per sensorpatch. These syntheses are intended to turn data into high-level informat ion,where the mult itude of records and raw data t ransform into something likeobservat ions or experience.60 This t ransformat ion requires data reduct ion inthe form of in-network processing that aggregates similar data and f ilt ersredundant data.61 As Jeremy Elson and Deborah Est rin write,

For example, emerging designs allow users to task the networkwith a high-level query such as not if y me when a large regionexperiences a temperature over 100 degrees or report thelocat ion where the following bird call is heard.

62In this way, processes of f ilt ering, aggregat ing, and select ing have alreadybeen put into place to turn sense data into relevant informat ion. At the samet ime, these f ilt ers may not always capture intended phenomena. A researcherwalking through the James Reserve forest may generate noise that is pickedup on sonic booms, which through algorithmic parsing act ivates cameras torecord act ivit y. In this f ield of environmental sensing, researchers may fall

within the data event -space of mot ion detect ion, but inaudible birds t ravelingin a dif ferent column of air might not be detected.Processes of generat ing data are then also processes of making sense: theexperiment is generat ive of modes of experience. These processes includehow sensors are developed in the lab, tested in the f ield by technologists andscient ists, merged within historic ecological study pract ices, read across newdata sets, while also producing dist inct insights into ecological relat ionships byconnect ing up mult iple subjects. The architectures and algorithmic processesfor relat ing sense data are a crit ical part of how sensor systems operate, andof art iculat ing how sense data will come together into arrangementsindicat ive of environmental and planetary processes.Inevitably, the focus on gathering massive amounts of sense data raisesissues related to the ontologies and incompat ibilit ies of data. Sensornetworks provide the basis for monitoring and act ing upon environments, andyet the data and connect ions made across sensors are select ively capturedand joined up, and are also subject to failure and incompat ibilit y of data.63Dif ferent data standards, classif icat ion techniques, and dispersed pract icesinform the content and processing of data-spacesa topic that Geof f reyBowker among others has discussed at length.64 Databases and data spacesare more than collect ions of object ively observable facts, but are embeddedwithin and performed through inf rast ructures of sciences, governance andpublic out reach. On the one hand, there are issues related to how an ent it ybecomes data, as Wolf f -Michael Roth and G. Michael Bowen have discussedin relat ion to the digit izat ion of lizards.65 On the other hand, there arequest ions about what const itutes data (a lizard may seem to be a clearart ifact of digit izat ion, but when it s habit s and habitat become part of thesensed data, where does the organism begin and the environment leave of f?).Data ontologies inform which data are collected, but they also informpossibilit ies of sense by giving rise to new actual ent it ies and occasions ofrelevant sense data.

System as sensor and proxy sensingIn order to generate a more ef fect ive parsing of environmental phenomena,sensors are rarely used as individual devices that simply generate discretesense data. Instead, mult iple sensors and sense criteria within a sensornetwork are of ten brought together to form a composite picture of a dist inctenvironment under study. Chemical analysis of pollut ion may provide readingson contaminant concent rat ion levels, but addit ional sensors may also work outthe direct ion and speed of contaminant t ravel, as well as the size of anaf fected area, by cross-correlat ing mult iple sensor data. In this process ofdata fusion, the system is the sensor.66 Sensors working together within anetwork establish a computat ional network of correspondences, where thephysical sight ing, sensor t ype, coding, and correlat ing of data coalesce intoan environment of sensor data that inform observat ions on the environmentof study. When the system is the sensor and the network operates as a sort

of dist ributed inst rument ,67 it is possible to generate models and forecasts ofenvironmental processes, and through these sensor systems to act uponenvironments.Sensor systems may also be proxies of the environments they sense.Sensors as proxies are not standing in for a more-real version ofenvironments, but rather are sensory operat ions that mobilize environments indist inct ways. Proxy sensing could be understood to operate in mult iple waysin the use of sensor systems for environmental monitoring. Sensor networksperformand so t ransformenvironmental systems. Data may be correlatedacross sensor t ypes, or sensors may t rigger other sensors to capturephenomena or t rigger actuators to collect samples for later study.68Inferences can be made about phenomena through sensors and actuators,and sensors can be arranged through f lexible, mult iscalar plat forms thatinvest igate part icular sensing relat ionships. As a CENS Dist ributed SensingSystems white paper notes, embedded sensing can involve a mix ofobservat ions with inherent ly dif ferent characterist ics. For instance, it iscommon for systems to include mult iple sensors, each with a dif ferent form ofsensory percept ion or modalit y.69 This is the case in James Reserve, whereseemingly t radit ional image and audio technologies provide a new way tosense phenomena in the absence of direct biological sensors. While themajorit y of sensors now available are capable of detect ing physical andchemical at t ributes, devices such as cameras become newly deployed asbiological sensors in the absence of direct biological sensing capabilit ies,where physical and chemical sensors algorithmically set to f ilt er for eventdetect ion automat ically t rigger cameras to record biological events.70 Imagerand audio modes of sensing are then act ivated within a computat ionalnetwork that mobilizes these forms of sensing as dist inct and of ten proxyoperat ions within a hierarchy of sensing. The possibilit y to art iculaterelat ionships and interact ions within environments to a higher f idelit y is thensomething that is generated and emerges through sensor applicat ions thatjoin up environments across sensor system hardware, sof tware, databases,cyber-inf rast ructures, as well as dist inct sites and the more-than-humanprocesses that unfold there.The proxy modes of sensing do not just extend to sensors t riggering othersensors or actuators to perform sensing operat ions, but also include proxiesthat emerge vis--vis more-than-human processes. A not -uncommontechnique within environmental study, where climate change in deep t ime maybe studied through ice cores as proxies for past climate events, proxies withinsensor-based environmental monitoring are mobilized to infer and detectt races of ecological processes. In the James Reserve, for instance, phenologyis a cent ral area of study. In order to capture seasonal relat ionships,organisms may be observed for the ways in which they processenvironments. At the James Reserve, the percept ive capacit ies of Violet -Green Swallows and Western Bluebirds, in addit ion to Star Moss and otherorganisms, are placed under observat ion through web cams and Cyclopsnetworked image sensors, which capture images and data related to theseorganisms of ten at least every f if teen minutes per day, if not moref requent ly.71 The bird cams and MossCam, or web camera specif icallymonitoring the growth of Star Moss, generate a store of image data that canbe compared to micro-local temperature and related data, as well as datacaptured throughout the James Reserve site. The birds choice of a nest inglocat ion, or the failure to raise chicks due to absence of food or lowtemperatures, can be captured in this context where the birds act ivit ies aremade available as a sort of proxy sensor of phenological processes. Birdsmay provide key environmental sense data through computat ional networksthat make sensible these registers of more-than-human experience. What isclear is that sensors do not just capture data, they shif t the processes ofsense across these mult iple registers, so that more-than-human percept iveprocesses emerge in newly relevant arrangements.Similarly, the Moss Cam generates images and daily records that cont ributeto a picture of seasonal pat terns and event ef fects. These ef fects mightinclude lack of moisture in the summer, which cont ributes to mosses burningthrough their CO2 reservesin other words, higher temperatures cancorrelate to an increased release of CO2 by mosses, as they consume storedenergy and move toward states of dehydrat ion and dormancy. Here, whatcounts as sensing is not a simple mat ter of observing mosses through a webcamera over t ime, but instead involves observing how the moss is a sensor, ora biomonitor that is it self detect ing and responding to changes in theenvironment .72 The mosses morphological changes to local condit ions are anexpression of an ecological relat ionship that is further entangled in thecomplex shif t s of climate change. In this respect , the mosses may beexpressing sensory responses to human-altered worlds, yet to understandmore fully what those alterat ions involve, it is necessary to observe sensingorganisms in order to register the ef fects of our act ions. The delay andresonance within these environments is not as immediate as a t ypical sensoryexample might assume. Yet in this study, the ways in which sensing organismstake account of environments mult iply, where the sensory input and meansof detect ion are dist ributed and computat ional.In a sensor-based study of phenology, sense operat ions are dist ributed andcollaborat ive. In these forms of collaborat ive sense, sensors experience andprovide proxy experiences across a sensing system that generates dist inctoccasions of sense. But the collaborat ive qualit ies of sense emerge notthrough researchers primarily, but through the dynamic responses oforganisms to environments, and the sensors that collect data through which

algorithms query, f ilt er and record these changes. The more dynamic sensorymodalit ies that emerge in this relat ionship are examples of emergingecological experiences and superjects, as discussed earlier. The t imings atwhich plants leaf out , for instance, might even begin to disrupt and alterscient if ic models that expect seasonal t imings to unfold at t imes establishedthrough prior empirical study. In these encounters and format ions of sensorypract ice across organisms, ontologically prior categories of sense becomemore mutable and ontogenet ic, where more-than-human modalit ies of senseindicate the shif t ing encounters of sense in which we are engaged. Sensorsystems mobilize mult i-located and mult ispecies processes of sensing, whichin part enable the development of dist inct capacit ies to sense change, wherethe scope of computat ional sensing and proxy sensing expands to includemore-than-technological perceptual processes.In an account of ubiquitous comput ing as dist ribut ion cognit ion, Haylessuggests that dist ributed computat ion could operate as machines for aidingand so enhancing human percept ion.73 Here, however, computat ional devicesare not augment ing human percept ion as such, and humans are not even thecent ral perceptual processors toward which dist ributed sensat ion andcomputat ion might be directed. Instead, more-than-human proxy sensingpoints to the ways in which sensor technologies might be seen not asproviding super-sensing or cognizing capabilit ies to supplement humanmodalit ies, but rather as technologies that f ilt er, connect up and mobilizeenvironmental relat ions in dist inct ways, and so change what modes of sensehumans may even experience. New ecological arrangements of subjectsandsuperjectsemerge through these sensory processes.Environmental monitoring through sensor networks is a pract ice of makingand not just capturingenvironments as process. Sensor networks are tunedto dist ribut ions of relat ions. They tune into discrete sense criteria,amalgamate these across sensor networks and through proxy modes ofsensing, to make more evident and sensible environmental relat ions.Environmental monitoring through sensory networks mobilizes and generatesenvironments in dist inct ways by localizing computat ional processes ofsensing within environments and across more-than-humans, while alsoart iculat ing those relat ions through algorithmic processes for parsing data. Asthis process inevitably composes the possibilit y of sensing environments inpart icular ways, it also informs which part icipants and part icipatory modes ofsensing register in the percept ive processes of sensor technologies. Suchsensing pract ices, moreover, are replete with polit ical ef fects. Within thecontext of sensor networks, the sensory arrangements that are ident if iedwithin data may become the basis for ident if ying and protect ing mat ters ofconcern; or otherwise overlooking or missing those non-sensuous backgroundevents that may st ill generate new arrangements, but which are notinterpretable within present modes of sense data.74

Conclusion: Inventing Experience From an experimental forest , this analysis of environmental sensing then turnsback to Turings count ryside discussed previously, that apparent ly stat icbackdrop through which sensing takes place. While Turing imagines adist ributed sensing ent it y processing it s bucolic surroundings, in this analysisof test sensors installed in a forest set t ing it becomes clear that thesurroundings to be sensed are in f lux and yet format ive to establishingcondit ions and pract ices of sense. Through this reading, Turings dist ributedcomputer becomes a superject , integrated with and format ive of theenvironments and experiences it would decode. This is not a recursive logic,but as discussed throughout this paper, provides space for taking account ofthe abst ract ions and ent it ies that lure feeling and set t le into forms ofenvironmental understanding.The environment or milieu as dif ferent ly understood by writers f romWhitehead to von Uexkll, Canguilhem and Foucault , has been discussed aseverything f rom the condit ions of possibilit y to a zone of t ransformat ion andnecessary extension within and through which experience is possible.75 Withinthe work of von Uexkll, the now well-cited example of the t ick that isprovoked to act in relat ion to certain environmental cues, is referenced tosignal both the ways in which sensat ion is t ied to environments, and tosuggest the species-specif ic coupling between these.76 Sensing beyond thehuman subject can be f igured through more-than-human agencies that unfoldwithin environments. But if we take the provocat ions of Whitehead seriously,together with posthuman media theory and philosophy, then the milieu is notjust a site where sensing joins up, but is also a t ransformat ive and immanentprocess where modes, capacit ies and dist ribut ions of sense emerge throughthe experiences of mult iple subjects.Any given milieu or subject /superject is then expressive not of stat ic couplingas the work of von Uexkll suggests, but of creat ivit y, as demonst rated in thework of Whitehead.77 If invent iveness is a necessary part of percept iveprocesses, then the environment -as-agitat ion necessitates a moreontogenet ic, collaborat ive and extensive understanding of sensing. In thisway, percept ion might also move beyond the not ion of hybridit ies or evenmediat ions of sense, and instead focus on the sensing condit ions and ent it iesthat emerge, as well as that which environmental percept ive processes makepossible, and how invent ive processes might further emerge.The complex interact ions that are the focus of study for environmentalsensor systems are t ransformed through the percept ive processes thatthese systems generate. The dist inct ways in which environments become or

appear to be animate are in part driven by the dist ribut ions of senseart iculated through sensor devices and programs. The ecological relat ionsthat are to be discovered and studied are bound up with the detect ion ofpat terns within sense data. Sensor hardware and sof tware do not simplygather sense data in the world, but are part of the process of perceptualpossibilit y, both as more-than-human registers of percept ion and throughmaking dist inct relat ions sensible as subjects of ecological concern.The possibilit y to relate and to make aspects of relat ions evident is animportant aspect of sensor systems, with polit ical and pract icalconsequences. Sensat ion might be understood as dist ributed and automatedon one level, yet on another level such automat ion in relat ion to environmentalprocesses involves not just running scripted funct ions, but also addressing theopen and indeterminate aspects of sensors in relat ion to environmentalprocesses. This is one way of saying that whatever the computat ionalprogram, sensors never operate st rict ly within a coded space, but by virtueof drawing together alternat ive percept ive processes inevitably make way fora generat ive technics of environments.There are then polit ical implicat ions to the implement ing of sensor processes:relat ions are not just discovered, they emerge through these dist inctcomputat ional sensing processes, and they also orient environmentalpract ices and polit ics, where increased data and improved awareness ofecological relat ionships are expected to t ranslate into an improved abilit y tomanage environments and potent ially prevent the spread of environmentaldamage. These crucial relat ionships emerge not just through pract ices ofdata collect ion and monitoring, as well as sharing and uploading data withinlarger networks, but also through drawing inferences across data sets thatilluminate key ecological relat ionships that are to become the basis ofconcern or protect ion. On the one hand, as Whitehead suggests, that whichcounts as form or data is what endures within a process of composit ion,which is expressive of historic character.78 What counts as empirical requiresacts of interpretat ion, but also describes a concrescence that cont inues tohave the force of natural fact . Drawing on Locke, Whitehead notes, theproblem of percept ion and the problem of power are one and the same, atleast so far as percept ion is reduced to mere prehension of actual ent it ies.79

While Whiteheads analysis works across philosophic and cosmologicalregisters, and does not direct ly address socio-polit ical analysis ofenvironments, his work does point toward potent ial t ranslat ions to be madeacross experiencing subjects to polit ical possibilit ies. As Shaviro suggestsfollowing on Whitehead, experience is a site of potent ial: It is only af ter thesubject has const ructed or synthesized it self out of it s feelings, out of it sencounters with the world, that it can then go on to understand that world orto change it .80 In other words, as Whitehead notes, How the past perishes ishow the future becomes.81 That which is sustained and that which emergesas a register of novelt y are processes whereby experience may give rise tonew experiences, interpretat ive pract ices and mat ters of concern.In a dif ferent way, Foucault indicates through his discussions on the milieu thatsensory arrangements are expressive of dist ribut ions of power, and involvemaking ongoing commitments to relat ions and ways of lif e.82 Sensoryprocesses that occur across subjects are then suggest ive of aesthet ico-polit ical relat ions and possibilit ies for part icipat ion. Environmental monitoringthrough sensor networks is a technoscient if ic pract ice that pertains not just tothe study of ecological relat ions, but also to emerging modes of part icipatorysensing and cit izen science act ivit y that rely on the use of the sensingcapacit ies on mobile phones to t rack and gather data f rom environments.While there is not space here to discuss in detail the mult iple developments inthis area, the implicat ions for sensory pract ices that emerge within anenvironmental monitoring context have relevance for thinking through theprocessual, relat ional and heterogeneous aspects of sensing. Given that theCENS research has moved out of the woods, to cit izen applicat ions ofsensing, while at the same t ime a whole host of cit izen science applicat ionsincluding forest monitoring plat forms are emerging to protect forests forconservat ion, how do forests, cit izens, more-than-humans and sensortechnologies converge to invent new forms of polit ics that are at tent ive topresent mat ters of concern, and those that are yet to come? AcknowledgmentsThanks are due to the researchers on the CENS sensing project who hostedme during f ieldwork conducted both at UCLA and the UC James Reserve,including Mark Hansen, Deborah Est rin, Michael Hamilton, Eric Graham, JoshHyman, Chuck Taylor, Kat ie Shilton, Hossein Falaki and Becca Fenwick, amongothers. I am grateful to Mat thew Fuller, Mike Michael and three anonymousreviewers for their helpful suggest ions for improving and clarif ying this text .The f ieldwork for this research was made possible by through CollegeResearch Funds seed funding, administered through the Research Of f ice atGoldsmiths, Universit y of London. Addit ional research materials in support ofthis research were made possible through Cult ivat ion Research Funds,administered through the Design Department , Goldsmiths, Universit y ofLondon.

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1. Isabelle Stengers, A Const ruct ivist Reading of Process and Realit y,Theory, Culture & Society 25, no. 4 (2008): 109.

2. This paper is part of a more extensive study, Program Earth:Environment as Experiment in Sensing Technology, on the programming ofenvironments through sensor technologies, as well as the developmentof cit izen sensing applicat ions for environmental engagement . Moreinformat ion on the project and related publicat ions can be found atht tp://www.program-earth.org.

3. Ulrik Ekman, ed., Throughout: Art and Culture Emerging with UbiquitousComputing (Cambridge, MA: MIT Press, forthcoming).

4. Ian F. Akyildiz et al., A Survey on Sensor Networks, IEEECommunications Magazine (August 2002): 102114; Gregory J. Pot t ie, andWilliam J. Kaiser, Wireless Integrated Network Sensors, Communicationsof the Association for Computing Machinery 43, no. 5 (2000): 51-58; DanaCuf f , Mark Hansen, and Jerry Kang, Urban Sensing: Out of the Woods,Communications of the Association for Computing Machinery 51, no. 3(2008): 24-33. .

5. Alf red North Whitehead, Process and Reality (1927-28; repr. New York:The Free Press, 1985), 88-89.

6. Stengers, A Const ruct ivist Reading of Process and Realit y, 99. 7. As N. Katherine Hayles writes in relat ion to dist ributed cognit ion of RFID

tags, When we understand that humans are not the only cognizers whocan interpret informat ion and create meaning, we are f ree to imaginehow a world rich in embodied contextual processes might be fashionedto enhance the dist ributed cognit ive systems that surround us and thatwe ourselves are. While this research is informed by this importantposthuman media perspect ive that moves beyond human-centeredapproaches to computat ional technology, here I am interested to bringWhitehead into this discussion of dist ribut ions of sensing in order not toemphasize cognit ion (with it s potent ial connect ion to consciousness),but rather to expand upon experience as a key way of drawing togethermult iple sensing ent it ies. See N. Katherine Hayles, RFID: Human Agencyand Meaning in Informat ion-Intensive Environments, Theory, Culture &Society 26, nos. 2-3 (2009): 69.

8. Whitehead, Process and Realit y, 20. 9. Ibid., 88.

10. Stengers elaborates on this sense of t uning within experiments, andwrites, t he idea that experimentat ion appeals to facts as they areobserved by means of experimental appliances only refers to the

stabilized end-product of a dif f icult operat ion. As Andrew Pickering(1995) marvelously characterized it , in his Mangle of Practice,experimenters may well know in advance what they want to achieve what , for instance, their appliance should detect . However, a longprocess of tuning will nevertheless be needed, within which nothing willbe t rusted, neither the human hypothesis nor the observat ions made.Indeed, the process of tuning works both ways, on human as well as onnonhuman agency, const itut ively intertwining a double process ofemergence, of a disciplined human agency and of a captured materialagency. Stengers, A Const ruct ivist Reading of Process and Realit y, 96.

11. Isabelle Stengers, The Cosmopolit ical Proposal, in Making Things Public:Atmospheres of Democracy, ed. Bruno Latour and Peter Weibel(Cambridge, MA: MIT Press, 2005), 9941003.

12. Et ienne Benson, Wired Wilderness: Technologies of Tracking and theMaking of Modern Wildlife (Balt imore, MD: Johns Hopkins Universit y Press,2010).

13. Deborah Est rin, Ref lect ions on Wireless Sensing Systems: FromEcosystems to Human Systems, Radio and Wireless Symposium, IEEE(January 9-11, 2007): 1-4.

14. Center for Embedded Networked Sensing (CENS), Annual ProgressReport (Universit y of California, Los Angeles, April 30, 2010).

15. Gilman Tolle et al., A Macroscope in the Redwoods, SenSys05 (SanDiego, November 24, 2005); Jeremy Elson and Deborah Est rin, SensorNetworks: A Bridge to the Physical World, in Wireless Sensor Networks,ed. Cauligi S. Raghavendra, Krishna M. Sivalingam, and Taieb Znat i(Norwell, MA: Kluwer Academic Publishers, 2004): 3-20.

16. This paper focuses on sensor applicat ions for ecological study.However, this by no means cover the ent irety of sensor applicat ions forenvironmental uses and beyond, including agricultural management andenergy saving in buildings. A whole range of automated environments isemerging through sensor applicat ions, which is the subject for futurestudy through the Program Earth research topic area.

17. Robert Szewczyk et al., An Analysis of a Large Scale Habitat MonitoringApplicat ion, Proceedings of the Second ACM Conference on EmbeddedNetworked Sensor Systems (Balt imore, MD: November 2004): 214-226.

18. The U.S. Long Term Ecological Research Network (LTER), accessedApril 3, 2012, ht tp://www.lternet .edu/; Nat ional Ecological ObservatoryNetwork (NEON), accessed April 3, 2012, ht tp://www.neoninc.org/.

19. Paul N. Edwards et al., Int roduct ion: An Agenda for Inf rast ructureStudies, Journal of the Association for Information Systems 10, no. 5 (May2009): 364-374; Dave Schimel et al., 2011 Science St rategy: EnablingCont inental-Scale Ecological Forecast ing, Nat ional EcologicalObservatory Network (NEON, 2011).

20. Microsof t Research, SenseWeb, accessed April 3, 2012,ht tp://research.microsof t .com/en-us/projects/senseweb/; Cosm (formerlyPachube), accessed August 7, 2012, ht tps://cosm.com/.

21. Michael Lehning et al., Inst rument ing the Earth: Next -Generat ion SensorNetworks and Environmental Science, in The Fourth Paradigm: Data-Intensive Scientific Discovery (Microsof t Research, October 2009).

22. Nokia, Sensor Planet , accessed April 3, 2012,ht tp://research.nokia.com/page/232; IBM, A Smarter Planet , accessedApril 3, 2012, ht tp://www.ibm.com/smarterplanet /uk/en/; HP Labs Cent ralNervous System for the Earth (CeNSE), accessed April 3, 2012,ht tp://www.hp.com/hpinfo/globalcit izenship/environment /tech_gallery/cense.html?jumpid=reg_r1002_usen; Planetary Skin Inst itute, accessed April 3, 2012,ht tp://www.planetaryskin.org/.

23. For a discussion of the mult iple part ies invested in ubiquitous comput ing,including governments, see Christ ian Nold and Rob van Kranenburg, TheInternet of People for a Post -Oil World, Situated Technologies Pamphlets8 (New York: The Architectural League of New York, 2011).

24. While there is not space within this paper to discuss thesedevelopments within sensor systems, for a more extensive discussionof how emerging sensing technologies and pract ices might beunderstood as forms of environmentalit y see Jennifer Gabrys,Programming Environments: Environmentalit y and Cit izen Sensing in theSmart Cit y, forthcoming. This paper draws on Foucault s reference toenvironmentalit y in Michel Foucault , The Birth of Biopolitics: Lectures at theCollge de France 1978-1979, t ranslated by Graham Burchell (2004; repr.Palgrave MacMillan, New York, 2008).

25. For a discussion of earlier at tempts to program environments withsensors through the prototypical if largely hypothet ical technology ofsmart dust , see Jennifer Gabrys, Telepathically Urban, in Circulation andthe City: Essays on Urban Culture, ed. Alexandra Bout ros and Will St raw(Mont real: McGill-Queens Press, 2010), 48-63.

26. CENS, Annual Progress Report , 3. 27. Adrian Mackenzie discusses this issue of how relat ions or it ineraries are

drawn through sof tware in Adrian Mackenzie, Cutting Code: Software andSociality (New York: Peter Lang, 2006). See also, Mat thew Fuller, Behindthe Blip: Essays on the Culture of Software (Brooklyn, NY: Autonomedia,2003).

28. Mark Weiser, The Computer for the 21st Century, Scientific American265, no. 3 (1991): 94104.

29. Alan Turing, Intelligent Machinery, in Mechanical Intelligence: CollectedWorks of A.M. Turing, ed. Darrel C. Ince. (1948; repr. Amsterdam: NorthHolland, 1992), 117.

30. Turing, Intelligent Machinery, 117. 31. Alf red N. Whitehead, Modes of Thought (1938; repr. New York: The Free

Press, 1966); Brian Massumi, Semblance and Event: Activist Philosophyand the Occurrent Arts (Cambridge, MA: MIT Press, 2011).

32. Whitehead, Modes of Thought, 158; Isabelle Stengers, Thinking withWhitehead: A Free and Wild Creation of Concepts, t rans. Michael Chase(Minneapolis: Universit y of Minnesota Press, 2011), 352-353

33. Whitehead, Modes of Thought, 138. 34. Whitehead, Modes of Thought, 158. And as Stengers writes, We do not

know how a bat , armed with it s sonar, or a dog, capable of t racking bysmell, perceive their world. We can ident if y the features theydiscriminate, but we can only dream of the cont rast between thatwhich they perceive and what they are aware of . All we know is thattheir experience is, like ours, highly interpretat ive, and that , like ours, ithas solved an ext raordinarily delicate problem: to give access, in a moreor less reliable way, to what it is important to pay at tent ion to. Payingat tent ion is the interpretat ive choice f rom which our experience hasissued. Isabelle Stengers, Thinking with Whitehead: A Free and WildCreation of Concepts, t rans. Michael Chase (Minneapolis: Universit y ofMinnesota Press, 2011), 338.

35. Whitehead, Process and Reality, 88. 36. Steven Shaviro, Without Criteria: Kant, Whitehead, Deleuze, and Aesthetics

(Cambridge, MA: MIT Press, 2009), 21. 37. While this not ion of dist ributed experience can be found within

Whiteheads writ ings, it also is a prior concept developed by WilliamJames in relat ion to radical empiricism. Adrian Mackenzie takes up thelat ter concept in relat ion to wirelessness to discuss how wirelesstechnologies unfold these dist ribut ions of experience. See AdrianMackenzie, Wirelessness: Radical Empiricism in Network Cultures(Cambridge, MA: MIT Press, 2010); and William James, Essays in RadicalEmpiricism (1912; repr. Lincoln, NE: Universit y of Nebraska Press, 1996).

38. For a more extended discussion on the development of f act icit y, seeMichael Halewood and Mike Michael, Being a Sociologist and Becominga Whiteheadian: Toward a Concrescent Methodology, Theory, Culture &Society 25, no. 4 (2008): 34; and Stengers, A Const ruct ivist Reading ofProcess and Realit y.

39. Thanks are due to Mike Michael for conversat ions that have led to thesepoints.

40. Luciana Parisi, Technoecologies of Sensat ion