Climate change represents a planetary emergency that is exacerbating the loss of native biodiversity. In response, efforts promoting climate change adaptation strategies that improve ecosystem resilience and/or mitigate climate impacts are paramount. Invasive Alien Species are a key threat to islands globally, where strategies such as preventing establishment (biosecurity), and eradication, especially invasive mammals, have proven effective for reducing native biodiversity loss and can also advance ecosystem resilience and create refugia for native species at risk from climate change. Furthermore, there is growing evidence that successful eradications may also contribute to mitigating climate change. Given the cross-sector potential for eradications to reduce climate impacts alongside native biodiversity conservation, we sought to understand when conservation managers and funders explicitly sought to use or fund the eradication of invasive mammals from islands to achieve positive climate outcomes. To provide context, we first summarized available literature of the synergistic relationship between invasive species and climate change, including case studies where invasive mammal eradications served to meet climate adaptation or mitigation solutions. Second, we conducted a systematic review of the literature and eradication-related conference proceedings to identify when these synergistic effects of climate and invasive species were explicitly addressed through eradication practices. Third, we reviewed projects from four large funding entities known to support climate change solutions and/or native biodiversity conservation efforts and identified when eradications were funded in a climate change context. The combined results of our case study summary paired with systematic reviews found that, although eradicating invasive mammals from islands is an effective climate adaptation strategy, island eradications are poorly represented within the climate change adaptation and mitigation funding framework. We believe this is a lost opportunity and encourage eradication practitioners and funders of climate change adaptation to leverage this extremely effective nature-based tool into positive conservation and climate resilience solutions.

Timely and accurate detection and estimation of animal abundance is an important part of wildlife management. This is particularly true for invasive species where cost-effective tools are needed to enable landscape-scale surveillance and management responses, especially when targeting low-density populations residing in dense vegetation and under canopies. This research focused on investigating the feasibility and practicality of using uncrewed aerial systems (UAS) and hyperspectral imagery (HSI) to classify animals in the wild on a spectral—rather than spatial—basis, in the hopes of developing methods to accurately classify animal targets even when their form may be significantly obscured. We collected HSI of four species of large mammals reported as invasive species on islands: cow (Bos taurus), horse (Equus caballus), deer (Odocoileus virginianus), and goat (Capra hircus) from a small UAS. Our objectives of this study were to (a) create a hyperspectral library of the four mammal species, (b) study the efficacy of HSI for animal classification by only using the spectral information via statistical separation, (c) study the efficacy of sequential and deep learning neural networks to classify the HSI pixels, (d) simulate five-band multispectral data from HSI and study its effectiveness for automated supervised classification, and (e) assess the ability of using HSI for invasive wildlife detection. Image classification models using sequential neural networks and one-dimensional convolutional neural networks were developed and tested. The results showed that the information from HSI derived using dimensionality reduction techniques were sufficient to classify the four species with class F1 scores all above 0.85. The performances of some classifiers were capable of reaching an overall accuracy over 98%and class F1 scores above 0.75, thus using only spectra to classify animals to species from existing sensors is feasible. This study discovered various challenges associated with the use of HSI for animal detection, particularly intra-class and seasonal variations in spectral reflectance and the practicalities of collecting and analyzing HSI data over large meaningful areas within an operational context. To make the use of spectral data a practical tool for wildlife and invasive animal management, further research into spectral profiles under a variety of real-world conditions, optimization of sensor spectra selection, and the development of on-board real-time analytics are needed.

Islands are hotspots of biological and cultural diversity that face growing threats from invasive species and climate change. Invasive mammal eradication on islands is a proven conservation intervention that prevents biodiversity loss and is a foundational activity for restoring degraded island-ocean ecosystems. However, these interventions are prioritized and evaluated primarily on biodiversity-based objectives despite growing evidence that invasive species removal may also serve as an effective nature-based solution to increase climate resilience of island-ocean ecosystems and contribute to climate change solution by protecting and restoring unique carbon stocks of native woody vegetation. To assess the effectiveness of interventions at the global scale, we developed a consistent and scalable framework for the long-term monitoring of tree cover, forest extent, forest carbon, and vegetation productivity in 1078 islands across 17 ecozones. Time-series of satellite-derived estimates of tree cover and the Normalized Difference Vegetation Index over 36 yr (1984–2020) were used to establish annual baselines and changes in forest extent, carbon stocks, and vegetation productivity. The analysis revealed significant and sustained positive trends in all the indices on islands with eradication. The magnitude and potential biological relevance of these effects was highly variable across ecozones, but the overall sustained effects provide strong evidence of a positive ecosystem response to invasive mammal removal. We also found that, collectively, these islands sustain more than 940 000 ha of forest and 53 million MgC of forest carbon. This novel framework enables measuring the climate co-benefits of island restoration interventions in relevant policy terms using a low cost and globally consistent methodology that is applicable across the range of spatial and temporal scales pertinent to ecosystem recovery dynamics on islands.

Feral cats have significant negative impacts on island ecosystems and are a major threat to resident seabird populations. In an attempt to restore populations of Brandt’s Cormorants, western gulls, and other native species on San Nicolas Island, California, feral cats were targeted for eradication. In over 83 successful feral cat eradications from islands, removal by padded leg-hold traps was the most commonly used eradication technique. However, the size of San Nicolas, 5,896 ha (14,562 acres) and the presence of >600 diminutive (average 1.7 kg) endemic island fox presented challenges. A telemetry-based trap monitoring system was developed to remotely check trap status, decrease staff time spent checking traps, and decrease response time to captured animals to limit fox injuries and mortalities due to exposure. This system enabled a team of 6 staff to maintain daily checks of approximately 250 traps and have a response time to captures of <60 minutes during daylight hours. Field staff were trained to assess fox health in the field, and a mobile veterinary hospital was established on island to treat any injuries. The trap monitoring system was composed of transmitter units connected to traps, an island-wide repeater system, a GIS database with field PDA data collection, and a user interface hosted on a local internet network. When activated, each transmitter sent a trapspecific ID code every 4 hours, indicating it was operational. When sprung, a modified ID code was transmitted every 30 minutes until the trap transmitter was reset. Repeaters relayed trap status data, both to a dedicated PC where a set of scripts filtered the raw data to find capture events, and simultaneously to the internet. A web-based software user interface was designed to combine capture events with location information from a GIS database, allowing field staff to quickly identify which traps were sprung and plan the most effective route between all sprung traps. Ultimately, this system was a powerful adaptive management tool that increased staff efficiency and minimized effects on non-target species.