Animal Harms and Food Production: Informing Ethical Choices

Simple Summary

Consideration of animal welfare in food choices has become an influential contemporary theme. Traditional animal welfare views about food have been largely restricted to direct and intentional harms to livestock in intensive animal agriculture settings. However, many harms to animals arising from diverse food production practices in the world are exerted indirectly and unintentionally and often affect wildlife. Here we apply a qualitative analysis of food production by considering the breadth of harms caused by different food production systems to wild as well as domestic animals. Production systems are identified that produce relatively few and relatively many harms. The ethical implications of these findings are discussed for consumers concerned with the broad animal welfare impacts of their food choices.

Abstract

Ethical food choices have become an important societal theme in post-industrial countries. Many consumers are particularly interested in the animal welfare implications of the various foods they may choose to consume. However, concepts in animal welfare are rapidly evolving towards consideration of all animals (including wildlife) in contemporary approaches such as “One Welfare”. This approach requires recognition that negative impacts (harms) may be intentional and obvious (e.g., slaughter of livestock) but also include the under-appreciated indirect or unintentional harms that often impact wildlife (e.g., land clearing). This is especially true in the Anthropocene, where impacts on non-human life are almost ubiquitous across all human activities. We applied the “harms” model of animal welfare assessment to several common food production systems and provide a framework for assessing the breadth (not intensity) of harms imposed. We considered all harms caused to wild as well as domestic animals, both direct effects and indirect effects. We described 21 forms of harm and considered how they applied to 16 forms of food production. Our analysis suggests that all food production systems harm animals to some degree and that the majority of these harms affect wildlife, not livestock. We conclude that the food production systems likely to impose the greatest overall breadth of harms to animals are intensive animal agriculture industries (e.g., dairy) that rely on a secondary food production system (e.g., cropping), while harvesting of locally available wild plants, mushrooms or seaweed is likely to impose the least harms. We present this conceptual analysis as a resource for those who want to begin considering the complex animal welfare trade-offs involved in their food choices.

Habitat suitability, live abundance and their link to road mortality of Tasmanian wildlife

ContextTasmania has been called the roadkill capital of Australia. However, little is known about the population-level impact of vehicle mortality on native mammals in the island state. AimsThe aims were to investigate the predictability of roadkill on a given route, based on models of species distribution and live animal abundance for three marsupial species in Tasmania – the Tasmanian pademelon (Thylogale billardierii), Bennett’s wallaby (Macropus rufogriseus) and the bare-nosed wombat (Vombatus ursinus) – and to assess the possibility of predicting the magnitude of state-wide road mortality based on live animal abundance. MethodsRoad mortality of the three species was measured on eight 15-km road segments in south-eastern Tasmania, during 16 weeks over the period 2016–17. Climate suitability was predicted using state-wide geographical location records, using species distribution models, and counts of these species from 190 spotlight survey roads. Key resultsThe Tasmanian pademelons were the most frequently killed animal encountered over the study period. Live abundance, predicted by fitting models to spotlight counts, did not correlate with this fatality rate for any species. However, the climate suitability index generated by the species distribution models was strongly predictive for wombat roadkill, and moderately so for pademelons. ConclusionsAlthough distributional and wildlife abundance records are commonly available and well described by models based on climate, vegetation and land-use predictors, this approach to climate suitability modelling has limited predictability for roadkill counts on specific routes. ImplicationsRoad-specific factors, such as characteristics of the road infrastructure, nearby habitats and behavioural traits, seem to be required to explain roadkill frequency. Determining their relative importance will require spatial analysis of roadkill locations.

Dynamic models in research and management of biological invasions

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.

A systematic review of the impacts and management of introduced deer (family Cervidae) in Australia

Deer are among the world’s most successful invasive mammals and can have substantial deleterious impacts on natural and agricultural ecosystems. Six species have established wild populations in Australia, and the distributions and abundances of some species are increasing. Approaches to managing wild deer in Australia are diverse and complex, with some populations managed as ‘game’ and others as ‘pests’. Implementation of cost-effective management strategies that account for this complexity is hindered by a lack of knowledge of the nature, extent and severity of deer impacts. To clarify the knowledge base and identify research needs, we conducted a systematic review of the impacts and management of wild deer in Australia. Most wild deer are in south-eastern Australia, but bioclimatic analysis suggested that four species are well suited to the tropical and subtropical climates of northern Australia. Deer could potentially occupy most of the continent, including parts of the arid interior. The most significant impacts are likely to occur through direct effects of herbivory, with potentially cascading indirect effects on fauna and ecosystem processes. However, evidence of impacts in Australia is largely observational, and few studies have experimentally partitioned the impacts of deer from those of sympatric native and other introduced herbivores. Furthermore, there has been little rigorous testing of the efficacy of deer management in Australia, and our understanding of the deer ecology required to guide deer management is limited. We identified the following six priority research areas: (i) identifying long-term changes in plant communities caused by deer; (ii) understanding interactions with other fauna; (iii) measuring impacts on water quality; (iv) assessing economic impacts on agriculture (including as disease vectors); (v) evaluating efficacy of management for mitigating deer impacts; and (vi) quantifying changes in distribution and abundance. Addressing these knowledge gaps will assist the development and prioritisation of cost-effective management strategies and help increase stakeholder support for managing the impacts of deer on Australian ecosystems.