This paper examines aspects of the relationship between (1) the recently typified form of biodiversity crime, (2) information made available to the public through the Internet, and (3) cultural dynamics quantified through info-surveillance methods through Culturomics techniques. Two conceptual models are proposed: (1) the building-up process of a biodiversity crime culturome, in a language, and (2) a multi-stage biodiversity conservation chain and biodiversity-crime activities relating to each stage. Crowd search volumes on the Internet on biodiversity crime-related terms and topics are used as proxies for the public’s interest measurement. The main findings are: (1) the concept of biodiversity-crime per se is still immature and presents low penetration to the general public; (2) biodiversity-crime issues, which are not recognized as such, are amalgamated in conservation-oriented websites and pages; and (3) differences in perceptions and priorities between general vs. ‘niche’ public with particular interest(s) in environmental issues- are discernable.
Research Article
Uncovering Patterns of Public Perceptions Towards Biodiversity Crime Using Conservation Culturomics
https://doi.org/10.21203/rs.3.rs-770642/v1
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The Convention on Biological Diversity (Rio de Janeiro 1992) is the epitome of liberal conservation strategy, a compromise between the designation of Protected Areas (PAs hereafter), re-regulation of the environment, and commodification of biotic resources (Secretariat CBD 2005). Real-world results in implementing this conservation strategy are relatively weak (e.g., Butchart et al. 2010; Perrings et al. 2010; Tittensor et al. 2014; Blicharska et al. 2016; Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) 2019; XXXX 2021). Research on the so-called biodiversity conservation ‘implementation gap or space’ (e.g., Maas et al. 2019), i.e., disciplinary and geographical biases and limited communication between scientists, practitioners, and decision-makers, is actively developing. Overall, there are ca 450 papers cataloged in the Web of Knowledge/ Science (WoK/S hereafter) as of July 2021 responding to the search string “conservation AND implementation AND gap AND biodiversity”; and > 145,000 papers tagged with the term “biodiversity” are listed in WoK/S, during 1987–2021). The academic effort repeatedly highlights the divergent directions of (1) political commitments, Conventional and legal framework (> 700 International Agreements and domestic conservation accords, e.g., Chester and Moomaw 2008) and (2) capacity building, awareness campaigns, or funding (hundreds of International/local ENGOs and billions of US$ or € invested, e.g., Fulton and Vercammen 2014; EU/Neemo/Ernst&Young 2016) versus the meager advances in the field. Several causes, ranging from opportunism in protected areas designation (e.g., Meir et al. 2004) to administrative incapacities and institutional weaknesses (e.g., Mascia and Pailler 2011), to reduced public participation in decision-making (e.g., Irvin and Stansbury 2004), have been proposed for this ineffectiveness, i.e., the measure of ‘true’ conservation achievement per cost (e.g., Arponen et al. 2010). Environmental and biodiversity crime is gaining currency in the interdisciplinary study of human-nature interactions as a proximate cause of threat to biodiversity conservation (e.g., Rose 2011; Sundstrom 2016; Elliott 2017; Moreto 2017). Biodiversity crime is considered as a specific class of pressure(s) upon (1) biological entities, i.e., genes, individuals, and populations of species and their habitats; (2) the ecosystem functions and services they support and generate; and (3) conservation policies of communities, societies, or States (e.g., Hoggt and Carrington 1998).
As a criminological issue per se, the sparse biodiversity-crime literature attempts to integrate narrative and normative (e.g., Biber 2017), legal and statutory (e.g., Apel 2013), sociological (e.g., Kavish and Boutwell 2018), or economic (e.g., Lacey et al. 2018; Pogarsky et al. 2018) definitions and explanations of individual and/or syndicate deviations from the commonly adopted norm of social order. The cultural dimension(s) of the multivalent problem of anti-social behavior and unlawful acts (e.g., Eysenck 1996) in the domain of biodiversity conservation is somehow neglected. Biodiversity crime, situated at the interface of multiple disciplines, including common Law (e.g., Zhu 2014; Do Vale 2015), environmental and green criminology (e.g., Tosun 2012; Beirne et al. 2018; Rodriguez Goyes and Sollund 2018; Brisman and South 2019; Brisman 2020), economics (e.g., Le Gallic 2008; Lynch et al. 2017), sociology (e.g., Huebschle 2017) and conservation science (e.g., Cafaro 2015; Solomon et al. 2015; Maas et al. 2019; XXXX and XXXX 2020), presents interesting conceptual and methodological peculiarities. For instance, in terms of ethical judgments, biodiversity crime is often difficult to grasp, for it offends intrinsic and inherent values of nature (e.g., Diaz et al. 2015) that are culturally defined but not ecumenically protected by human Law. The controversial example of circus animals, bullfighting in Hispanic countries, or bear-subduing in the Balkans, until some decades ago, generated the popular legend of tamers and are (or were) considered a cultural event, heritage, or entertainment attraction. What differentiates bullfighting and bear-subduing is that the latter is listed as an endangered species and not the mistreatment per se of both animals. What makes the difference between the illegal trade of a lion vs. its exposition in a zoo is the existence of an incumbent scientific discourse considering the latter as conservation-positive. It is not a straightforward task for the average citizen, who is a carrier of unclear value systems (e.g., Pascual et al. 2017) and is exposed to complex scientific and legal discourses to assess criminal harms and damages caused to biological beings that are generated by the accumulative deterioration of their biotopes or the illicit appropriation of scarce biotic resources. Harms and damages that are not immediately visible, often ‘victimless’ (Cardwell et al. 2011) and certainly ‘voiceless’ (Solomon et al. 2015).
According to Europol, the European Union’s Law enforcement Agency, environmental and biodiversity crime intensifies, especially during the Covid-19 circumstances (Europol/SOCTA 2021). Partial causes of biodiversity-crime dynamics might be identified in recent environmental and criminological literature (e.g., Brisman 2020). At first, one could note the likely lack of substantial public interest in conservation issues (e.g., Novacek 2008; Mccallum and Bury 2013; Ficetola 2013; Nghiem et al. 2016; Burivalova et al. 2018; ΧΧΧΧ 2017a,b; 2019). Second, the cultural variations and linguistic differences in people’s perceptions of nature (e.g., Funk and Rusowsky 2014; Roll et al. 2016; XXXX 2021) often estranges them when coupled with scientific terminology and conservation concepts (e.g., Fischer and Young 2007). Third, the mismatches between scientific effort and conservation needs (Fisher et al. 2010). Fourth, the weak correspondence between biodiversity crime ontologies and legal typification, as in the case of ordinary crime (e.g., Brantingham 2016), might make it challenging to integrate into the penal system, the prosecution procedures, and its fuzzily functioning green benches. Fifth, the inefficiency in international cooperation is an additional cause for navigating the conservation implementation space unsuccessfully (e.g., Rose 2011; Elliott 2017; ΧΧΧΧ and ΧΧΧΧ 2020). As Elliott (2017) eloquently stated, the complexity per se of the conventional international framework on environmental and biodiversity crime leads to legal indeterminacy, normative ambiguity, and regulatory uncertainty.
However, although a vital component of cultural human-nature interactions, the repercussions of such indirect drivers upon the public interest in biodiversity crime issues have not yet been studied or remain partially unexploited, to our best knowledge. Understanding people’s perceptions, awareness, and interest in the benefits and costs of biodiversity crime are of primary importance for determining whether crime-combatting policies will succeed to curve it in the long term. We hypothesize that this challenge might be approached methodologically through the emergent Culturomics epistemology (Michel et al. 2011), i.e., the quantitative investigation of cultural trends through the automated linguistic and lexicographic analysis of millions of digitized books (ca 16 M as of the end of 2019; data available through Google Books Ngrams Viewer service). Michel et al. (2011) made further the point that “culturomics extends the boundaries of rigorous quantitative inquiry to a wide array of new phenomena spanning the social sciences and the humanities” (p. 176). Further, Conservation Culturomics (CC henceforth) is an epistemology per se that seeks to understand the evolution of human-nature relationship(s) through discursive expressions that define human acts and behavior (e.g., Ladle et al. 2016, p. 269; Sutherland et al. 2018; ΧΧΧΧ and ΧΧΧΧ 2020).
We will utilize data from Google crowd searches on biodiversity crime-related words and topics to uncover patterns of perceptions across time, possible behavioral change over time, and pinpoint drivers of the public's behavioral uptake. This approach might complement the fragmentary yet use of big online data (Web, mass media, social media), although they represent a rich opportunity to investigate public perceptions on emerging topics such as conservation and biodiversity (e.g., Correia et al. 2016; Correia et al. 2017; XXXX 2017; Toivonen et al. 2019). We expect that bridging this gap could be of great importance for improving the efficacy and success of conservation and biodiversity crime prosecution in the long term.
In this paper, we attempt (1) to define a biodiversity-crime ‘culturome’, i.e., a linguistic set of words, terms, or topics that encapsulate its various meanings, aspects, and domains at the reach of people (Sect. 2.1); (2) to explore general trends of public interest in biodiversity crime themes using Google Trends-crowd search data as a well-established technique of CC (Sect. 2.2. and 3); (3) to propose a hierarchical ontology of acts that could be considered as biodiversity crimes (Sect. 4); and (4) to discuss ontological correspondences between modern forms of crime (Sect. 4).
We base our overall approach upon two conceptual models. These models serve as explanatory bases for constructing a specialized pool of associated terms (or phrases) on biodiversity criminal issues addressable through conservation culturomics epistemology. The first model introduces a mechanism explaining the assembly of words or terms in the kernel lexicon of a language encapsulating the biodiversity crime phenomenon. The second model introduces a typified form of the conservation implementation chain and its sequential stages governing biodiversity components and conservation policy conditions against which criminal activities and acts are perpetrated. The CC methodology is expected to help understand how initial public interest – or curiosity - expressed through crowd searches on the Internet might reflect sustained public adherence to biodiversity crime importance; and, therefore, to be investigated as a significant component- into the overall biodiversity-conservation strategy implementation, in the future.
2.1.Conceptual model 1: a mechanism for the public construction of biodiversity crime culturome.
Petersen et al. (2012) qualify a language as an ‘ecosystem of words’ that is permeable to other languages; they further distinguish time scales in its evolution. One can identify three primary sources of words (terms) –and phrases- relating to biodiversity crime issues: (1) the “kernel” lexicon consisting of words emanating from scientific vocabulary and more frequently used words; (2) the “unlimited” lexicon comprising terms and phrases commonly used in “public” communication channels, e.g., mass media, social media and, most importantly, vernacular names or expressions of biodiversity entities; and, (3) “exotic” terms to the reference language, incoming from other languages. Altogether, they form a pool of words (terms) focusing on this specific issue. The public, i.e., the Internet users, searches massively for information on a subset of this pool: it is a sampling process from which a culturome is constructed after the systematic association of terms in large volumes of crowd searches. In direct analogy to the concepts of ‘gene’ and ‘Genomics’, individual words, i.e., terms conveying a concept, are discrete inherited units of a language. Linguistics refers to the study of etymology and expressive evolution of terms in a language’s lexicon. In contrast, besides its neological character, culturomics aims to develop computational lexicography to investigate cultural phenomena by analyzing digitized texts and data mining on the Internet (Michel et al. 2011).
Specialized Internet services provide sets of associated terms (e.g., Google Adwords Tool, Wordstream Free Keywords Tool, Keywords Everywhere). Such associations present trend lines of crowd search volumes and altogether form evolving culturomes with a series of properties (Fig. 1). Two issues are calling for caution in this mechanism. First, several scientific terms correspond to broader topics, e.g., climate change, global warming, greenhouse gases and effects, et cetera. Second, although vernacular names of species are essential components of a culturome and eventually semantically identical in the public’s mindscape regarding their scientific names (e.g., Correia et al. 2016; Jarić et al. 2019), they might hide taxonomic differentiations: e.g., the African elephant corresponds to two species, Loxodonta africana, and Loxodonta cyclotis.
Terms are connected to specific segments of the conservation implementation chain (see Conceptual model, Sect. 2.2. here below). Some of them contribute conceptual emphasis: e.g., biodiversity, ecosystem, species, or conservation. Others are complementary within the same segment: e.g., scientific and vernacular names of species; others complement segments: e.g., PAs vs. EU Natura 2000 conservation sites.
2.2. Conceptual model 2: the conservation implementation chain, gaps and crime.
This simplified linear conceptual model depicts a 5-stage ideal implementation process for conservation policy presented in Fig. 2. Stages are identified as science, rhetoric, gazettement or institutionalization, policy instrument building and confirmation. The model includes dominant processes per stage, actors and major drivers as well. The science stage corresponds to the identification of biodiversity "objects" such as species or habitats. Rhetoric is the stage where social processes of argument construction in favor of biodiversity conservation occur; scholars or Environmental NGO experts are the main actors who establish the basis of biodiversity conservation needs through a cognitive process. If science and rhetoric are efficiently combined, then decisions on gazettement (or institutionalization) are taken through political processes; there is a shift in dominance from actors to drivers since the economy or national sovereignty issues play a core role in shaping the procedure. Technology and technocratic knowledge dominate and drive the stage of policy instruments building; decisions on spatial planning or selection of sites to be protected or organizational structures and functions of governance systems are key issues at this stage. Finally, confirmation is the stage of action on the ground; specific management plans should be drafted, personnel should be authorized and hired, budget and cashflows secured, et cetera. One might expect that several feedbacks among constituent stages of the implementation chain that speed it up or slow it down in actual conditions might exist. If the implementation process fails or does not perform efficiently, there should be ‘cracks’ or ‘chasms’ between the stages (Fig. 2). For instance, there might be inefficient communication of scientific knowledge and message, the Sc-Rh crack; or, resistances in transboundary agreements, collaboration and coordination, the Rh-Gz crack; or, difficulties and lack of political and administrative will to confirm in the ground the previous stages, the Gz-PIb crack; or, capacity building issues, the PIb-Con crack; or, most likely some combination of all these conditions.
Biodiversity crime actions or activities (examples) are mirrored into each stage. Each one might affect components of a particular stage or, most importantly, it might energize the ‘cracks’ that block the sequence of the conservation implementation process.
2.3. Conservation Culturomics and biodiversity crime
Ladle et al. (2016, p. 269) established a 5-axes epistemic program of Conservation Culturomics. A conceptual translation or correspondence of this program into non-compliance conservation concepts, i.e., biodiversity crime, is attempted or summarized in Table 1. This attempted correspondence might have various connotations, from recognition –and valuation- of crime activities per se to educative schemes against criminal activities.
|
Conservation Culturomics Program (Ladle et al. 2016) |
Conservation significance |
Biodiversity crime actors/ players (examples) |
|---|---|---|
|
Recognizing conservation-oriented constituencies and demonstrating public interest in nature |
Creation of Internet/Social Media communities, identification of Conservation adepts, NGOs militants, political supporters and thinkers, environmental-friendly citizens, … |
Hunters’ Associations, Rangers, Forestry Department Officials, NGOs activists, media reporters, … |
|
Identifying conservation emblems |
Protection of keystone -species, species with wide-range territories and/or historical/ cultural symbolism |
Species with appeal in common public/media discourse: elephant, tiger, rhino, monk seal, endemics, ethno-diversity species, … |
|
Providing new metrics and tools for near-real-time environmental monitoring and to support conservation decision making |
Complementary but no-substitutive information on public opinion evolving at various time scales and cultural entities |
Analyses of biodiversity crime approximate information through Internet-based crowd search services, such as Google Trends, Adwords, N-gram viewer, Wikipedia, Twitter, FB, … |
|
Assessing the cultural impact of conservation interventions |
Role of culture-driven human-biodiversity relationship in terms of appropriation of biotic/ ecosystemic resources |
Regional/local (mostly) economy platforms relating to primary, secondary and tertiary production (e.g. green/biological agriculture, circular economy, low carbon industry), etc. |
|
Framing conservation issues and promoting public understanding |
Environmental education, awareness and information activities… |
Typical and a-typical activities within environment-related groups such as scouts, school pupils, outdoor activities associations, tourism promoters, … |
2.4. Worldwide trends of public interest in biodiversity crime
In order to approximate public interest in biodiversity crime issues, we accessed Internet crowd-search activity (specifically through Google search engine and Google Trends service, GTs hereafter) from January 1, 2004 to August 31, 2020. We targeted explicitly (1) collections of animal species, under both their vernacular/popular names and scientific names, in most cases; this information was meant to trace the evolution of public interest in species that the International Union for Conservation of Nature (IUCN) lists as vulnerable, threatened, endangered, or critically endangered. The status of such listed species is highly related to various forms of biodiversity-crime types. Notice that the two collections do not match exactly since the ‘vernacular’ sub-group emphasizes on the popularity of species (e.g., Correia et al. 2016). Interestingly, 80% of queried species returned consistent time series. (2) The biodiversity crime-related pool of terms; we queried GTs service for > 150 terms and/or phrases search strings, of which just 30 crime-related crowd-searched terms and phrases (ca 20% of a hypothetical unlimited lexicon, in the sense of Petersen et al. 2012) returned consistent time-series. The selection of searched terms obeys two criteria: (i) terms are addressing the five ideal stages of the conservation implementation process, i.e., science – rhetoric – institutionalization - capacity-building - policy confirmation; (ii) terms are selected to serve as broad conceptual generalizations/stage, albeit occasionally overlapping in meaning. (3) The identification of web pages dedicated to themes and issues (1) and (2) here above; we contrasted these findings to the number of relative publications in the WoK/S, during the same period. The most significant observation is the low specialization of web pages since many of them refer to multiple biodiversity-crime types and conservation implementation issues.
All search strings are in English; therefore, the information collected is coarse-grained from a Culturomics perspective. Results presented hereafter are bound to a worldwide vocabulary that sidesteps linguistic, cultural, societal, and technological variations (e.g., Funk and Rusowsky 2014; ΧΧΧΧ 2019). In other words, we used no geographical and linguistic restrictions when investigating GTs, so our data strictly reflect worldwide results from those users searching the Internet with Google in English (see Conclusions section for further details).
Four configurations of GTs analyses are provided hereafter:
(1). Figure 3 presents the ordination in a 2D slope (x-axis) – r2 (y-axis) plane of the two collections of species: (a) popular species after their vernacular name; (b) species after their scientific names. It is assumed that this comparison signalizes differences in public interest between the general public and some “niche” public, which most likely represents scientists, officials of Non-Governmental Environmental Organizations, members of various animal-watching groups, and zoophilic charities, et cetera. In our terminology (see Sect. 2.1 here above), the culturomes constructed after vernacular/popular and the scientific names ordinated in the slope/r2 plane present a U-shape distribution. We suggest that a 2nd-degree polynomial or parabola might approach such a U- slope/r2 curve; and that the coefficients a, b, c of the corresponding f(GT) = aGT2 + bGT +c equations have specific physical meaning that might be used in comparing these culturomes. For instance, a coefficient controls the curvature of the parabola, with higher values of a indicating stronger internal coherence of the culturome. The b coefficient in combination with a in the form 
indicates the x-ordinate of the U-curve (the slope component). Moreover, c coefficient indicates the y-ordinate (the r2 component); higher c indicates increased linearity of GTs of constituent terms.
(2). Figure 4 presents linear vs. cyclical trends of public interest in the two collections of species nomenclature. In both cases, the predictor of individual term results was time, and the response variable was search-volume/term as expressed by corresponding GTs. The deviation of ca 38 [r2 linear vs r2polynomial] points from the 1:1 diagonal in the corresponding plane shows that the overall public interest in species under pressure from biodiversity crime-related activities follows time cycles analogous to the core concept of biodiversity (ΧΧΧΧ 2017b). This graphical representation complements results presented in Fig. 3: ‘niche’ public seems more reactive to variations in crime pressures upon conservation flag species.
(3) Fig. 5 presents normalized GTs crowd-search data to identify –mostly- long-term linear evolution of the global public interest in the selected topics of the conservation implementation chain during 1/2004-8/2020. This configuration is typical of early publications in Conservation culturomics (e.g., Mccallum and Bury 2013; Ficetola 2013; Proulx et al. 2013; Wilde and Pope 2013). The merits and flaws of such approach are discussed in ΧΧΧΧ and ΧΧΧΧ (2020).
(4) Fig. 6 [A, B, C] presents a synthesis of long term evolution of an ensemble of ca 30 biodiversity crime-related concepts available in two different media environments: (1) scientific publications cataloged in WoK/S, ‘the scholar pool of knowledge’; and, (2) number of web pages, ‘the public pool of knowledge’, dedicated to the same issues. The search period extends from January 1, 1990, to August 31, 2020. The starting date was determined after almost all core environmental meta-concepts, i.e., biodiversity, sustainability, and planetary change were constructed, in the late ‘80s. ‘Poaching’ is the term attracting most interest in academic literature; ‘wildfire forest arson(s)’, a criminal activity, is by far the phrase repeatedly appearing in environmental/biodiversity oriented web pages.
The discussion extends into three directions based on the findings here above. The first direction relates to drivers of biodiversity crime and its situation into a framework of social-ecological systems under exogenous vs. endogenous pressures. Within the incumbent conceptual framework of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) (Diaz et al. 2015), core literature proposes long series of higher-order multiple and interdependent causes of- and effects upon- social-ecological systems that drive the failing implementation of conservation policies. External abrupt shocks or transient pressures upon individuals and their communities' economic and social status are shown to provoke significant endogenous pressures upon the state of biodiversity and ecosystem service provision units (e.g., Roosenvell et al. 2010). Misbehavior against- and misappropriation of- biotic resources have been related to the economic downturn in various biomes and human development conditions (e.g., South East Asia, Dauvergne 1999; Venezuela, Rodriguez 2000; Greece, Lekakis and Kousis 2013; ΧΧΧΧ and ΧΧΧΧ 2020). Further, change of regime (e.g., Robinson and Milner-Gulland 2003), war (e.g., Geist and Lambin 2001; Duffy 2014; Douglas and Alie 2014; Runhovde 2017; Liévano-Latorre et al. 2021), corruption (e.g., Gore et al. 2013), but also culture and religion (e.g., Grainger 1993) and the abrupt penetration of science and technology into local socio-ecological setups (e.g., Lambin et al. 2006) are proposed as disruptive conditions altering the effectiveness of public conservation policy implementation. Recently, the Covid-19 pandemic and global human confinement conditions, including the ban of hunting and fishing, have also been related to ambivalent conservation efficiency issues (e.g., Bates et al. 2020). Such empirical cases are related to various degrees to biodiversity crime, e.g., poaching, illegal logging, and fishing, in the sense of non-compliance to- or voluntary violation of - conservation rules (e.g., Solomon et al. 2015) through mechanisms relating to market distortions and administration incapacities (ΧΧΧΧ and ΧΧΧΧ 2020). Interestingly, similar criminogenic mechanisms have been proposed or predicted to apply during and after the Covid-19 pandemic human confinement, even within protected areas (e.g., Koju et al. 2021).
However, the analysis of the multivalent problem of biodiversity crime should not rely upon episodic or short-term anomalies of social-ecological systems’ trajectories. Instead, it should focus on long-term chronic pressures generated by illegal deviations in activities such as endemic and/or endangered species trade -including trophies or biological material collection, uncontrolled wet meat markets, the need for household food appropriation such as the bushmeat case, specialized industry interests -including equipment and services supply, or the operations of organized biodiversity-crime hierarchies. In that perspective, the discussion on biodiversity entrapment into poverty (e.g., Adams et al. 2004; Barrett et al. 2011) and the debate on price-determining vs. price-determined valuation of biodiversity (e.g., Farley 2008) might constitute a guiding analytical framework relating to willingness-to-pay for illegal biological material or misuse of biotopes. This relates to the dominant assumption of Law enforcement authorities that environmental and biodiversity crime is directly linked to the search for illicit profits (e.g., Ayling 2013; Leberatto 2017). Under both conditions, i.e., transient vs. chronic pressures, it seems preferable to adopt a terminology of ‘mechanisms enabling’ biodiversity crime that allows avoiding the ‘blaming of the poor’ for biodiversity loss if criminal activities are decoupled from poverty and social justice issues (Lynch et al. 2017).
The second direction of the discussion relates to the need for developing an ontology for biodiversity crime. Such ontology should be conceptually simple to reach, intrigue positively and energize the public interest as to the connections between biodiversity crime and unsuccessful conservation. It should be explicit, allowing for conceptual enrichment in a way that facilitates interdisciplinary collaboration, transnational coordination, and ultimately judge's decision; for it addresses cases that might carry built-in ambiguity in expert terminology and semantics if examined from the perspective of different scientific disciplines. It should also be formal to avoid Courts oscillating for justice between incumbent administrative policies and choices regarding conservation (e.g., Blicharska et al. 2016); theoretical mismatches of general penal and biodiversity crime cases (e.g., Barton and Moran 2013); insufficient prosecution dossiers; insignificant judicial statistics, similar to those in unregistered crime (e.g., Stroh et al. 2016); and, theoretically unprepared benches and district attorneys (e.g., Rose 2011).
Figure 7 presents such an ontology and a typology of biodiversity crime. Classes of biodiversity crime are sets of concrete concepts defined by the Law; for example, a Person or Offender is not necessarily meant in the physical identity of a ‘biological individual’ but as a ‘personification’ through that individual of a rigorously defined criminal act. The same stands for the inverse case of the prosecuting law agent. Therefore a Class is a representation of a biodiversity crime concept relating to offense or prosecution. To make operational the proposed ontology, three Classes are necessary.
First, the Class of Malicious_Act lists in some strict way categories of offenses. According to the classification scheme, one Class might be described using a series of first order subClasses arranged in a sub-class/super-class hierarchy. For example, in Fig. 7, the Class Malicious_Act comprises five first order subClasses, i.e., illegal hunting, illegal logging, illegal fishing, trade, and collection. Each first-order subClass is further divided into second order subClasses. Therefore, a ‘Person’ who destroys nests of a bird species, be it Red-listed or not, is committing an offense of the subClass Collection of the Class Malicious_Act. Where the boundaries of a Class with its subClasses are set is a matter of classification of functionality, rigorousness in the legal definition of acts, and similarity between them. For instance, viewed from the standpoint of conservation biology, the second-order subClass_Prohibited_technique in the subClass Illegal_hunting as a case of the Class Malicious_Act is functionally similar, not to say identical, to the correspondent in the subClass Illegal_fishing; for a poacher might use banned equipment to attract flocks of waterbirds to shoot massively and/or he might use dynamite to collect fishes massively in the same wetland. The only distinction between these acts lies with the relevant Law qualifying the act, the Law on Hunting in the first case and the Law on Fishing in the latter.
The second Class refers to Responsibility. The penal system recognizes two first-order subClasses: objective and subjective responsibility, which are divided into second-order subClasses. Within the subClass Objective_responsibility, the distinction is made between Act, Attempt, and Negligence when a single individual perpetrates the crime. Commission as a second-order subClass involves a third person and is usually treated through prescriptions included in another range of the criminal Law. The Commission might be of critical importance in organized crime cases –a class that is repeatedly observed in the illegal logging/smuggling case where a hierarchy of roles should be judged. Within the subClass Subjective_responsibility, the distinction is made between Intentional and Unintentional crime.
The third Class refers to the actual provisions of the Law, i.e., the Articles that define the specific crime and predict criteria of application and sanctions. It should be noticed that both national and international legal framework governing forests, fisheries, various categories of protected areas and species, land use, and spatial planning predicts hundreds of Articles, clauses, and sub-categories about all probable and improbable situations. It indeed leads to Elliott’s (2017) conclusions on legal system mis-performance due to its inherent complexity, indeterminacy, and ambiguity.
The three Classes share a common characteristic; they describe the conditions to be satisfied, so an individual case is assigned to a specific type of biodiversity crime. Therefore, links between classes are necessary; these links are common properties within a given domain of knowledge. A given set of properties characterizes a group of individuals that should be treated equally by the penal system. For example, all hunters who intentionally shot a listed brown bear within a PA pertain in the same group of penal treatment. On the contrary, hunters who shot a wild boar intentionally in the same PA are not, but they might pertain in other Classes and/or subclasses of the same legal framework; for they all committed the crime of hunting within the PA, but one species is Red-listed, and the other is not. This Class should be further enriched with twin Laws on Hunting and/or Conservation.
The third direction relates to conceptual similarities of biodiversity crime with other modern forms of crime, as typified by Europol (SOCTA 2021). As shown in Table 2, we propose a scheme of correspondence between crime types to which the public is conceptually acquainted and their ontological equivalent in the domain of biodiversity. We assume that such an approach might help overcome the public's limited interest in- and understanding of- the various facets of biodiversity crime, individual responsibility issues, and the mechanics of organization, operation, financing, or money laundering of such criminal activities and networks.
|
Criminal activities |
Biodiversity crime equivalent |
Examples |
|---|---|---|
|
Genocide |
Interspecies genocide |
6th mass extinction |
|
Cyber-dependent crime |
Intrusion to sites of conservation importance |
Hunting in protected areas |
|
Trafficking of human beings |
Trafficking of protected species |
Violation of CITES Convention |
|
Smuggling of people |
Smuggling of biotic resources |
Transborder commerce of stolen wood |
|
Waste crimes |
The commerce of banned and hazardous substances/materials |
Violation of the Vienna Convention and the Montreal Protocol for the ban of ozone-depletion substances |
|
Organized property crime |
Trespassing private game refuges |
Illegal fishing in aquaculture installations |
|
Trade in illegal firearms and explosives |
Hunting and fishing gear and equipment |
Fishing with dynamite and banned nets |
This paper proposes an approach of the relationship between (1) a recently typified form of crime, i.e., biodiversity crime; (2) information made available to the public through alternative media, i.e., the Web, social media, and specialized academic bibliography; and, (3) cultural dynamics quantified through Culturomics surveillance techniques.
Overall, biodiversity crime is at an embryonic stage within the typical penal law types, understanding, and perception(s) of the public (e.g., Brantingham 2016). For example, the classic ‘theft’ culturome, i.e., the set of associated terms in Google crowd searches, comprises 511 keywords or the ‘murder’ one, 423 keywords. On the contrary, ‘biodiversity conservation crime’ comprises only 1. It is the word ‘poaching’, a term with a long cultural history and relating more to practices than to crime per se, which comprises 286 keywords.
Most precursory conservation culturomics research focuses on public interest trends using Internet-based services that provide data on search volumes for specific keywords - e.g., the Google Trends service - or on sets/collections of related keywords - e.g., Google Adwords Keyword Tool or the public domain Wordstream Keyword Tool. Such research has helped in better understanding both structural (size of search volumes, lexicographic composition and relative frequencies of keywords) and dynamic (trajectories in time) traits of culturomes (ΧΧΧΧ and ΧΧΧΧ 2020) as well as significant determinants of their diversification across cultural, linguistic and technological setups (Funk and Rusowsky, 2014). However, such integrated information cannot address whether punctual interest in a biodiversity-crime-related keyword is sustained in time and, more importantly, whether it evolves towards increased public sensitivity for strategic conservation issues.
Models 1 and 2 have been tested against real-world data on Internet searches in the specific context of biodiversity-crime-related searches in English worldwide (data source: Google search volumes provided by WordStream Keyword Tool). It is a weakness of our approach since it rules out cross-cultural comparisons. However, it was deemed necessary to adopt such a linguistic sample in order to drop variability and noise generated by cultural, linguistic, chronological/conjectural, social, and technological determinants of the phenomenon (e.g., Rizzolo et al. 2017) because of fuzzy and vague translations of core biodiversity-crime terms provided by web-based services – especially in languages where endangered species are located, and criminal activities eventually occur, e.g., Panthera tigris tigris in Bhutan, Andrias davidianus in China, Lemur catta in Madagascar, or Varanus komodoensis in small Indonesian islands.
Segmentation of conceptual searching across the biodiversity conservation implementation chain (Model 2) is arbitrary. However, it represents a well-informed guess on articulating a suite of concepts that expresses rational progress along with conceptual differentiation in the conservation science-policy gradient.
One might hypothesize that several mechanisms interfere with a shadow process of transforming the stochastic process of an individual’s interest–e.g., new, additional, or expanded search(es) for associated biodiversity-crime-related keywords – to a somehow deterministic predictable pattern of group-behavior. Such mechanism(s) might be, among others: (1) search efficiency: individuals become mentally more confident and spend less time hesitating, learning, or making disappointing mistakes in searching biodiversity-crime related information sources; (2) replication: as information and knowledge converge to standardized arguments on biodiversity-crime, efficiency in searches tends to increase; (3) network-building: as a keyword is more widespread in information networks, an individual Google searcher uses it more efficiently because s/he is familiar with it; (4) an analogy of software engineering POLA principle (Principle Of Least Astonishment), i.e., information gathered from didactic sources regarding biodiversity-crime should comply to a discursive manner consistent with how individual users of this information are likely to expect it to behave; that is, average users should not be estranged by complicated terminology and complex explanations (Fischer and Young 2007; Novacek 2008).
Finally, our results support the idea that there might be divergence(s) among culturally determined social perceptions of criminal acts and their effects upon biodiversity and ecosystems, expressed in natural language that may lead to different interpretations of biodiversity crime -and its drivers. The cases of observed differences between the general public and the niche public (U-shape slope/r2 or the importance of recognition of cyclical trends in public interest) are characteristic, generating likely varying penal evaluation between them. It might prove pivotal in the case of inter-departmental and international collaboration for environmental/biodiversity law enforcement (e.g., Meeus 2010; Elliott 2017). In Conservation Culturomics, improved intelligence techniques are necessary to accurately predict public interest in conservation; in the biodiversity crime domain, strict ontologies are urgently needed to outline abstract crime concepts and support consequent objective judicial treatment.
Acknowledgments
The authors wish to express their thanks to two anonymous reviewers and XXXXXXXXXXXX for helpful comments and assistance during the writing of the manuscript. They dedicate this paper to the loving memory of Professor XXXXXXXX. [The names XXXXXXXXXXXXXXXXXX will be publicized after the full-blinded review process].
This research did not receive any specific grant from the public, commercial, or not-for-profit sectors.
There is no Conflict of Interest
All co-authors are mentioned and consent regarding content and submission
No experimentation with Humans and Animals
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