W

olves have returned to Germany. An estimated 1300 of them, or some 60 packs, roam the countryside, more than anywhere else in Europe by population density. Most have settled in North and East Germany, where pasture feeding is a common practice. The upward trend started about 20 years ago, and since then an increasing number of livestock has fallen prey to the previously absent predators, among them sheep, cattle and horses. This "rewilding" of Germany has also sparked some polarizing debates within rural populations, which have even bubbled up into provincial electoral campaigns in recent years.  They concern wolves as contributors to livestock loss (its prevention and compensation measures), as vital participants in conservation of biodiversity efforts, and as risks to the safety of children.

The strict conservation status of wolves prohibits their killing. As free roaming species they count as “wild animals”, i.e. they are not owned by anyone. Wolves are typically unseen; they move quietly, quickly, and mostly at night. As a result, monitoring technologies such as camera traps, transmitter collars, or forensic analysis have each become important tools for understanding this rewilding of Germany, in part by helping to map the wolves' movements  and ongoing coexistence with human and other nonhuman populations.

In this essay, we focus on the ordinary technology of the camera trap.  We argue that camera traps operate as part of an “infrastructure of evidence” (Calkins and Rottenburg 2017), an apparatus that serves to arrange various entities — species, communities, and technologies, etc. — in such a way as to provide coherent “proof” for certain claims. Looking at camera trappings is a relational visualization practice, a making-visible of a formerly absent and usually invisible species. In so doing, camera traps can make specific individual wolves identifiable as a danger to humans and livestock, sometimes leading to their illegal killing. They can also produce important evidence of biodiversity, coherent images of successfully rewilded ecologies. 

Of course, none of these images, nor the claims for which they provide evidence, are ever as coherent and stable as they seem. Rather, we argue that the camera trap participates in these political disputes and enacts the wolf as a political matter. Though aimed at providing proof, it simultaneously produces uncertainty — a “wild wolf” that is elusive and “slippery” (Law and Lien 2013), that exists in more than one register, and that matters differently to different groups, whether as individuals or as a species. (Think of all the symbolic meanings a wolf can have, e.g. for power, freedom or myth; see Scarce 1998). The camera trap does not resolve these disputes, but fuels them and participates in the wolf’s slippery enactment. Like all infrastructures, then, camera traps are political. Instead of enabling the movement of people, capital, things, and nonhumans, however, these infrastructures create the grounds for the production of evidence (or uncertainty) while also playing a key role in organizing the many debates surrounding wolves and rewilding.

Compared to other monitoring technologies (e.g. transmitter collars, forensic analysis), camera traps are affordable (around 60 euros each), accessible through neighborhood electronics stores, and easy to work with (requiring only a memory card and batteries). In rural Germany, farmers use them to surveil their properties, but scientists, hunters, shepherds and foresters use them too. On a basic level, camera traps enable humans to make observations while being absent — an important feature when human presence tends to deter what they want to ‘capture’ in the first place. A movement in front of a camera trap’s built-in sensor triggers continuous stream of data in the form of pictures and videos. For that reason, these technologies have also gained popularity in citizen science projects on biodiversity, in which remotely collected images are pooled and tasks of labeling and categorizing them are crowd-sourced.

Despite the ease of access and democratization of science celebrated by its widespread use, the camera trap nevertheless raises a number of important political and ethical questions, including who can and should participate in rewilding, and what the technology is ultimately for (e.g. Gabrys 2016; Marres 2012).

In Julia’s research area in Northern Germany, camera traps are an especially thorny political and ethical matter. They provide both laypeople and professionals with the means to render wild animals visible, but they also raise questions about land access, as well as what happens to privacy when inevitably there’s a “human bycatch” (Sandbrook et al. 2018). One state official, responsible for monitoring wolves in and around a large military training area in Lower Saxony, describes an element of the controversy:

Camera traps are a delicate subject, data protection officers have to deal with them all the time. […] I try to use them with caution because camera traps are a very, very important tool. […] For example, if there are humans in the pictures, I do not even check to see if I know the person. I immediately erase the pictures, even though it is a proof for trespassing on private property. I erase them, because reporting this regulatory offense is not worth risking the further use of the camera traps.

For livestock keepers and rural populations, meanwhile, camera traps play an important role beyond managing their properties.  They satisfy a certain demand for knowledge amid all of the uncertainty of living with wolves. They produce evidence of mobility patterns, the potential for cross-breeding with domestic dogs, as well as their impact on local ecologies (e.g. as “natural regulators” of boar or deer populations). But as proof of a wild wolf or wolfpack, the evidence they provide is typically insufficient to apply for funds to build fences or to receive compensation for killed livestock. That does not mean that camera traps do not play a critical role for infrastructures of evidence in these communities.  They happen to reduce uncertainties about a range of financial and ecological issues. 

These uncertainties, and the challenges of producing coherent evidence, are well illustrated by the case of a nature reserve in Lower Saxony, where sheep are also farmed. Officially, the rural district is categorized as wolf-free.  Yet, the shepherds here have already lost around 300 sheep to wolves — not only because of wolf-related killings, but also because sheep kill each other in the stampedes that result from wolves roaming around stables and pastures, or because lambs and ewes sometimes die from related stress-induced abortions. However, officially, the rural district is categorized as wolf-free. Official categorizations are mainly based on DNA samples taken from droppings, killings and wolf cadavers—a rather strong form of evidence, in the scope of things. But since the den of the resident pack is located exactly on the other side of district border, these wolves are considered to be “passing through”. This means that even though there is DNA evidence of the pack near the sheep farm, they are only filed as passing through the district. Consequently, it is almost impossible for the shepherds to receive funds or compensation. The camera traps they have put up provide them with only weak evidence that wolves are continuously roaming through their area. With more evidence, they also hope to sway bureaucrats into re-categorizing their district as a “wolf district.”

The example also illustrates how complex infrastructures of ecological evidence can be.  First is the difficult matter of gaining proof of a wild wolf.  For the photograph to become “evidence,” the camera trap, the picture, the wolf itself, and the inspection of the wolf-on-the-picture by experts have to come together and interact in a certain way.  If the camera trap does not show pictures of a wolf, or the pictures are not clear enough to identify the creature as “a wolf”, it is often necessary to look for other evidence (DNA, telemetry, dead or living individual; DBBW 2020).  Then there is the question of "where it belongs,” including where an individual wolf or its pack has established its den, and if it's just "passing through".  In this “ontological choreography” (Thompson 2005; Cussins 1996), infrastructures of evidence tend to “grow.”  While chances for evidence are higher if we add more evidencing practices to the infrastructure, this also creates the need of a challenging act of coordination among ontologically heterogeneous entities in order to create coherency – and thus proof. In the case of the pack living in the other district, it seems that the choreography will fail if the evidence is too weak.

What makes some evidence strong and others weak is not a matter of the method or technology itself, but the infrastructures of evidence underlying it. The slipperiness of a wild wolf requires a certain choreography to turn its image into evidence. When a wolf enters into the frame of a camera trap, it travels along and through the infrastructures of evidence that leads to proof of its existence (at least, in a certain time and place).  Though camera traps are partly constitutive of these infrastructures, they are by no means the only entities. To have proof of either “wolves preying on livestock” or “ecological rewilding,” you need a wolf, a camera, a picture, and an inspector — and oftentimes many other sources of evidence.  What is so unique about the camera trap is that it is as an affordable and easily accessible evidencing technology, a participatory device. While not as ‘strong’ as DNA analysis, for example, camera traps — for better or worse — bring various communities into debates about rewilding. They are opening up the evidencing process, which has traditionally been controlled by experts, to forms of participation. 

Infrastructures of evidence emerge around a complex matter of concern. Their emergence means that problems remain unsolved and a lack of certainty keeps the evidencing apparatus busy. We tried to demonstrate that taking a closer look at the parts that constitute the infrastructure, we may find that practices and technologies of evidencing themselves have politics where most of us assume an unquestionable standard procedure. In this respect, following the “weak” parts of the infrastructure of evidence leads us to those arenas where (social/epistemic) inequalities, ethical concerns, and ontological politics are taking place. As a plea for the democratization of science and technology, we want to highlight that the study of infrastructures of evidence makes visible where the dichotomy of “weak/strong” evidence might also have social and ecological effects.

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References

Calkins S and Rottenburg R (2017) Evidence, infrastructure and worth. In: Harvey P, Bruun Jensen C, and Morita A (eds.) Infrastructures and social complexity: a companion. New York; London: Routledge, pp. 253–265. 

Cussins C (1998) Ontological Choreography: Agency through Objectification in Infertility Clinics. Social Studies of Science, 26(3), 575-610.

DBBW - Dokumentations- und Beratungsstelle des Bundes zum Thema Wolf (2020): “SCALP Criteria”. Retrieved here.

Gabrys, J (2016): Citizen Sensing: Recasting Digital Ontologies through Proliferating Practices. Cultural Anthropology, Editor’s Forum “Theorizing the Contemporary”. Retrieved here.

Law J and Lien ME (2013) Slippery: Field notes in empirical ontology. Social Studies of Science, 43(3), 363–378. Retrieved here.  

Marres, N (2012): Material Participation: Technology, Environment and Everyday Publics. Basingstoke: Palgrave.

Sandbrook, C, Luque-Lora, R and Adams, W (2018): Human bycatch: conservation surveillance and the social implications of camera traps. Conservation and Society 16(4), 493-504.

Scarce, R (1998): What Do Wolves Mean? Conflicting Social Constructions of Canis lupus in “Bordertown”. Human Dimensions of Wildlife 3 (3), 26-45.
Thompson C (2005) Making Parents: The Ontological Choreography of Reproductive Technologies. Cambridge, MA: MIT Press.

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Markus Rudolfi is a sociologist at Goethe-University Frankfurt, Germany. He studies conservation practices at the Transboundary Park Bavarian Forest/Šumava.

Dr. Julia Poerting is a human geographer based in Bonn, Germany, who is interested in the biopolitics of wolf rewilding in Northern Germany.