Anthropogenic factors affecting wildlife species status outcomes: why the fixation on pesticides?
Notice bibliographique
Résumé
Most Americans are at least three generations removed from the farm, thereby at least three generations removed from the reality of where their food comes from. Not surprisingly, there are many misconceptions about modern food production, including the potential collateral environmental damage attributed to agriculture, particularly the application of pesticides. However, the implication of conventional agriculture in the broader narrative of wildlife species status outcomes (SSOs) lacks context and relativity. Since the dawn of civilization, humans have had a profound impact on their environment. Originating as hunter-gatherer societies, our ancient ancestors initially exploited anything that could be consumed or brought to bear. With the advent of the "first proto-farmers," humans began manipulating their environments to maximize available resources. Urban centers propagated and flourished proximal to agricultural origins, where modern societies have been built primarily on an abundance of food. As societies "developed," and continue to develop, an inevitable economic transition occurs from agriculture to industry/service predominance, culminating in a corresponding shift in land use. Developed countries have typically experienced maximal expansion of the agricultural frontier, where farmland is now steadily eroding by a proverbial flood of urban development. In contrast, in developing countries, this shift in economic development has not yet fully manifested and the agricultural footprint continues to expand at the expense of native habitats. Thus, the relative influence of "agriculture" on SSOs, in terms of land use, is primarily dependent on economic developmental status, which can be, at least in part, ameliorated via technology by increasing yield from existing land. Moreover, in addition to the land use challenge, there are multiple other factors affecting wildlife SSOs, including a figurative plague of invasive species, a literal plague of disease, a barrage of buildings, bumpers, grilles, and windshields to collide with, light pollution to confuse cues with, poachers to contend with, and even more complicated factors such as climate change. Being an easy target does not mean pesticides are the right target, and this fixation can potentially detract from public awareness regarding the primary drivers affecting SSOs as well as the opportunity to proactively address them. So, relatively speaking, how do these other factors compare to "pesticides" in terms of driving SSOs? Moreover, why is the popular media so fixated on the pesticide narrative? Based on the available evidence, this manuscript attempts to address these questions from a holistic and relative perspective within the context of land use change, economic development, population growth, and associated implications of global connectivity and commerce.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,005 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».