Inferential and forward projection modeling to evaluate options for controlling invasive mammals on islands

A framework for identifying fertility gene targets for mammalian pest control

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit. This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression and results from mouse knockout models. This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals. In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

Using a Modeling Approach to Inform Progress Towards Stoat Eradication From the Orkney Islands

Invasive non-native species eradication attempts are typically large and expensive projects that benefit from the support of quantitative tools, such as population models, to be completed within the scheduled and funded time. Managed ecosystems are constantly changing due to population and ecosystem dynamics. Accordingly, any model predictions need to be updated, using different sources of data, to inform the project about the progress toward eradication. The stoat Mustela erminea was introduced to the hitherto predatory land mammal free Orkney archipelago around 2010. In 2016, a project aiming to eradicate stoats to preserve ecologically and economically important native wildlife was designed and implemented. It entailed a “knockdown” phase followed by a “mopping-up” phase to remove stoats that escaped capture. We used data from this project to iteratively predict the progress toward eradication. We applied spatially explicit individual-based models to estimate the proportion of stoats being exposed to capture, and then compared these simulation-based predictions with removal data, allowing us to estimate changes in the population size through time. We also used sighting data from members of the public to refine eradication probability. We were also able to demonstrate how the initially wide uncertainty gradually diminished as more evidence accumulated. The information derived from different types of data and quantitative models allowed us to track the effectiveness of current trapping approaches and to help to inform project managers about when the project achieved the knockdown phase milestone. Our analyses confirmed that the expected magnitude of the initial knockdown phase has been achieved in some areas, but also revealed spatial and temporal heterogeneity in the distribution of captures, most likely caused by the sequential trapping and stoat movement and trap shy stoats exposed to capture but not caught. This heterogeneity calls for additional data sources (e.g., from camera traps or detection dogs) to estimate the proportion of trap-shy individuals and the size of the untrapped population, and ultimately the feasibility of eradication.

How important is individual foraging specialisation in invasive predators for native-prey population viability?

Predation by invasive species is a major threat to the persistence of naïve prey. Typically, this negative effect is addressed by suppressing the population size of the invasive predator to a point where the predation pressure does not hinder the viability of the prey. However, this type of intervention may not be effective whenever a few specialised predators are the cause of the decline. We investigated the effects of varying levels of specialised invasive stoats (Mustela erminea) abundance on the long-term viability of simulated kiwi (Apteryx spp.) populations. We explored four scenarios with different proportions of highly specialised stoats, which were those that had a ≥ 0.75 probability of predating kiwi eggs and chicks if they were within their home range: (i) a stoat population composed mostly of generalists (mean: 0.5 probability of predation across the population); (ii) 5% of highly specialised stoats and the remaining being generalists; (iii) 10% of highly specialised stoats and the remaining being generalists; and, (iv) half highly specialised stoats and half generalists. We found that stoat home range sizes, rather than stoat density or the density of highly specialised stoats, was the main driver of kiwi population trends. Stoats with large home ranges were more likely to predate kiwi eggs and chicks as these were more likely to fall within a large home range. More broadly, our findings show how the daily individual ranging and foraging behaviour of an invasive predator can scale-up to shape population trends of naïve prey.

Caribou in the cross-fire? Considering terrestrial lichen forage in the face of mountain pine beetle (Dendroctonus ponderosae) expansion

Mountain pine beetle (MPB) has become an invasive forest pest of mature pine in western North America as it spreads beyond its former endemic range. Management actions such as timber harvest can reduce the spread of MPB but may affect species of conservation concern like woodland caribou. Our goal was to inform MPB management within caribou ranges by exploring the impacts of MPB on caribou habitat-focusing on terrestrial lichens, an important winter food for caribou. We evaluated differences in lichen cover among four MPB management actions: timber harvest, wildfires, leaving MPB killed trees as-is, and single-tree cut-and-burn control. We found little evidence that leaving MPB killed trees as-is or controlling MPB using single-tree cut-and-burn impacted lichen cover. However, we found that lichen cover was lower in timber harvested and burned areas compared to intact undisturbed forest but only 10 to 20 years post-disturbance, respectively. Our results suggest that despite short-term reductions in lichen cover, using timber harvesting and prescribed burns to control MPB may balance management needs for MPB while maintaining lichen cover over time. However, using timber harvesting and prescribed burns to manage MPB is likely to have detrimental population-level effects on caribou by increasing the proportion of disturbed habitat and thus predators within caribou ranges. Among the four management actions that we evaluated, the cut-and-burn control program balances the need to limit the spread of MPB while also limiting negative impacts on caribou food. Our work addresses some of the challenges of managing competing forest and ecosystem values by evaluating the consequence of forest pest management actions on an important food resource for a species-at-risk.

Monitoring, modeling and harvest management of non-native invasive green iguanas on Grand Cayman, Cayman Islands

The green iguana (Iguana iguana) was most likely introduced as a pet and became overabundant during the last 20 years on Grand Cayman. Because negative impacts were unmanageable (e.g., damage to buildings and other infrastructure), a harvest management strategy was developed and implemented, and over 874,252 green iguanas were removed between October 2018 and August 2019. Distance sampling surveys were conducted to estimate abundance in February 2019 and annually in August 2014–2019. Abundance estimates were used to develop a Bayesian state-space logistic model, generate the posterior distributions of population and harvest management parameters, and make future predictions of abundance for August 2020–2030. Abundance increased over fivefold between August 2014 and 2018, from an average of 254,162 to 1,319,939 green iguanas. However, after harvesting for 5 months, abundance declined to an average of 600,113 green iguanas in February 2019; and after 11 months, abundance declined to an average of 103,020 green iguanas in August 2019. Maximum population growth rate averaged 1.552, carrying capacity averaged 1,611,013, equilibrium abundance averaged 805,506, maximum sustainable total harvest averaged 628,491, and maximum sustainable harvest rate averaged 0.776. With harvest rates between 0.600 and 0.800, predicted abundance averaged 28,751 green iguanas for August 2020–2030. However, harvest mortality may have unforeseen outcomes due to the release from density dependence and overcompensation through high survival and fecundity rates. Because natural resource managers have partial control over harvesting and incomplete understanding of green iguana population dynamics, monitoring and modeling are essential to assess population response and guide harvest management decisions.

A concise guide to developing and using quantitative models in conservation management

Quantitative models are powerful tools for informing conservation management and decision-making. As applied modeling is increasingly used to address conservation problems, guidelines are required to clarify the scope of modeling applications and to facilitate the impact and acceptance of models by practitioners. We identify three key roles for quantitative models in conservation management: (a) to assess the extent of a conservation problem; (b) to provide insights into the dynamics of complex social and ecological systems; and, (c) to evaluate the efficacy of proposed conservation interventions. We describe 10 recommendations to facilitate the acceptance of quantitative models in conservation management, providing a basis for good practice to guide their development and evaluation in conservation applications. We structure these recommendations within four established phases of model construction, enabling their integration within existing workflows: (a) design (two recommendations); (b) specification (two); (c) evaluation (one); and (d) inference (five). Quantitative modeling can support effective conservation management provided that both managers and modelers understand and agree on the place for models in conservation. Our concise review and recommendations will assist conservation managers and modelers to collaborate in the development of quantitative models that are fit-for-purpose, and to trust and use these models appropriately while understanding key drivers of uncertainty.