A novel approach to assessing the ecosystem-wide impacts of reintroductions

Reintroducing a species to an ecosystem can have significant impacts on the recipient ecological community. Although reintroductions can have striking and positive outcomes, they also carry risks; many well intentioned conservation actions have had surprising and unsatisfactory outcomes. A range of network-based mathematical methods have been developed to make quantitative predictions of how communities will respond to management interventions. These methods are based on the limited knowledge of which species interact with each other and in what way. However, expert knowledge isn’t perfect and can only take models so far. Fortunately, other types of data, such as abundance time-series, is often available, but, to date, no quantitative method exists to integrate these various data types into these models, allowing more precise ecosystem-wide predictions. In this paper, we develop mathematical methods that combine time-series data of multiple species with knowledge of species interactions and we apply it to proposed reintroductions at Booderee National Park in Australia. There have been large fluctuations in species abundances at Booderee National Park in recent history, following intense feral fox (Vulpes vulpes) control – including the local extinction of the greater glider (Petauroides volans). These fluctuations can provide information about the system isn’t readily obtained from a stable system, and we use them to inform models that we then use to predict potential outcomes of eastern quoll (Dasyurus viverrinus) and long-nosed potoroo (Potorous tridactylus) reintroductions. One of the key species of conservation concern in the park is the eastern bristlebird (Dasyornis brachypterus), and we find that long-nosed potoroo introduction would have very little impact on the eastern bristlebird population, while the eastern quoll introduction increased the likelihood of eastern bristlebird decline, although that depends on the strength and form of any possible interaction.We thank the ARC Centre of Excellence for Environmental Decisions, The National Environmental Research Project Decisions Hub and an ARC Linkage Project (LP160100496) for funding. CB is the recipient of a John Stocker Postdoctoral Fellowship from the Science and Industry Endowment Fund. MB is supported by an ARC Future Fellowship (FT170100274). EMM is a current ARC Future Fellowship (FT170100140) and was supported by an ARC DECRA Fellowship for the majority of this work

Informing network management using fuzzy cognitive maps

Modern conservation requires robust predictions about how management will affect an ecosystem and its species. The large uncertainties about the type and strength of interactions make model predictions particularly unreliable. In this paper, we show how fuzzy cognitive maps can produce robust predictions in complex and uncertain ecosystems. The use of fuzzy cognitive maps has been increasing markedly, but there are two critical issues with the approach: translation of expert knowledge into the FCM is often done incorrectly; and sensitivity analyses are rarely conducted. Translating expert knowledge is a constant challenge for ecological modellers, often because experts know about the behaviour of a system, but modellers need to know model parameters, which subsequently lead to system behaviour. We describe how to correctly incorporate expert knowledge into FCMs, and we describe how to appropriately conduct uncertainty and sensitivity analysis. We illustrate this process with a previously published network for feral cat and black rat control on Christmas Island. Perverse indirect effects of conservation management are a key concern, and methods to help us make informed decisions are required. Fuzzy cognitive maps are a promising approach for this, but it requires the methodological improvements that we present here

Indigenous plants promote insect biodiversity in urban greenspaces

The contribution of urban greenspaces to support biodiversity and provide benefits for people is increasingly recognized. However, ongoing management practices favor vegetation oversimplification, often limiting greenspaces to lawns and tree canopy rather than multi-layered vegetation that includes under- and midstorey, and the use of nonnative species. These practices hinder the potential of greenspaces to sustain indigenous biodiversity, particularly for taxa like insects that rely on plants for food and habitat. Yet, little is known about which plant species may maximize positive outcomes for taxonomically and functionally diverse insect communities in greenspaces. Additionally, while cities are expected to experience high rates of introductions, quantitative assessments of the relative occupancy of indigenous vs. introduced insect species in greenspace are rare, hindering understanding of how management may promote indigenous biodiversity while limiting the establishment of introduced insects. Using a hierarchically replicated study design across 15 public parks, we recorded occurrence data from 552 insect species on 133 plant species, differing in planting design element (lawn, midstorey, and tree canopy), midstorey growth form (forbs, lilioids, graminoids, and shrubs) and origin (nonnative, native, and indigenous), to assess (1) the relative contributions of indigenous and introduced insect species and (2) which plant species sustained the highest number of indigenous insects. We found that the insect community was overwhelmingly composed of indigenous rather than introduced species. Our findings further highlight the core role of multi-layered vegetation in sustaining high insect biodiversity in urban areas, with indigenous midstorey and canopy representing key elements to maintain rich and functionally diverse indigenous insect communities. Intriguingly, graminoids supported the highest indigenous insect richness across all studied growth forms by plant origin groups. Our work highlights the opportunity presented by indigenous understory and midstorey plants, particularly indigenous graminoids, in our study area to promote indigenous insect biodiversity in urban greenspaces. Our study provides a blueprint and stimulus for architects, engineers, developers, designers, and planners to incorporate into their practice plant species palettes that foster a larger presence of indigenous over regionally native or nonnative plant species, while incorporating a broader mixture of midstorey growth forms

Simultaneous multi slice (SMS) balanced steady state free precession first-pass myocardial perfusion cardiovascular magnetic resonance with iterative reconstruction at 1.5T

Background: Simultaneous-Multi-Slice (SMS) perfusion imaging has the potential to acquire multiple slices, increasing myocardial coverage without sacrificing in-plane spatial resolution. To maximise signal-to-noise ratio (SNR), SMS can be combined with a balanced steady state free precession (bSSFP) readout. Furthermore, application of gradient-controlled local Larmor adjustment (GC-LOLA) can ensure robustness against off-resonance artifacts and SNR loss can be mitigated by applying iterative reconstruction with spatial and temporal regularisation. The objective of this study was to compare cardiovascular magnetic resonance (CMR) myocardial perfusion imaging using SMS bSSFP imaging with GC-LOLA and iterative reconstruction to 3 slice bSSFP. Methods: Two contrast-enhanced rest perfusion sequences were acquired in random order in 8 patients: 6-slice SMS bSSFP and 3 slice bSSFP. All images were reconstructed with TGRAPPA. SMS images were also reconstructed using a non-linear iterative reconstruction with L1 regularisation in wavelet space (SMS-iter) with 7 different combinations for spatial (λσ) and temporal (λτ) regularisation parameters. Qualitative ratings of overall image quality (0 = poor image quality, 1 = major artifact, 2 = minor artifact, 3 = excellent), perceived SNR (0 = poor SNR, 1 = major noise, 2 = minor noise, 3 = high SNR), frequency of sequence related artifacts and patient related artifacts were undertaken. Quantitative analysis of contrast ratio (CR) and percentage of dark rim artifact (DRA) was performed. Results: Among all SMS-iter reconstructions, SMS-iter 6 (λσ 0.001 λτ 0.005) was identified as the optimal reconstruction with the highest overall image quality, least sequence related artifact and higher perceived SNR. SMS-iter 6 had superior overall image quality (2.50 ± 0.53 vs 1.50 ± 0.53, p = 0.005) and perceived SNR (2.25 ± 0.46 vs 0.75 ± 0.46, p = 0.010) compared to 3 slice bSSFP. There were no significant differences in sequence related artifact, CR (3.62 ± 0.39 vs 3.66 ± 0.65, p = 0.88) or percentage of DRA (5.25 ± 6.56 vs 4.25 ± 4.30, p = 0.64) with SMS-iter 6 compared to 3 slice bSSFP. Conclusions: SMS bSSFP with GC-LOLA and iterative reconstruction improved image quality compared to a 3 slice bSSFP with doubled spatial coverage and preserved in-plane spatial resolution. Future evaluation in patients with coronary artery disease is warranted

Multiorgan MRI findings after hospitalisation with COVID-19 in the UK (C-MORE): a prospective, multicentre, observational cohort study

Introduction: The multiorgan impact of moderate to severe coronavirus infections in the post-acute phase is still poorly understood. We aimed to evaluate the excess burden of multiorgan abnormalities after hospitalisation with COVID-19, evaluate their determinants, and explore associations with patient-related outcome measures. Methods: In a prospective, UK-wide, multicentre MRI follow-up study (C-MORE), adults (aged ≥18 years) discharged from hospital following COVID-19 who were included in Tier 2 of the Post-hospitalisation COVID-19 study (PHOSP-COVID) and contemporary controls with no evidence of previous COVID-19 (SARS-CoV-2 nucleocapsid antibody negative) underwent multiorgan MRI (lungs, heart, brain, liver, and kidneys) with quantitative and qualitative assessment of images and clinical adjudication when relevant. Individuals with end-stage renal failure or contraindications to MRI were excluded. Participants also underwent detailed recording of symptoms, and physiological and biochemical tests. The primary outcome was the excess burden of multiorgan abnormalities (two or more organs) relative to controls, with further adjustments for potential confounders. The C-MORE study is ongoing and is registered with ClinicalTrials.gov, NCT04510025. Findings: Of 2710 participants in Tier 2 of PHOSP-COVID, 531 were recruited across 13 UK-wide C-MORE sites. After exclusions, 259 C-MORE patients (mean age 57 years [SD 12]; 158 [61%] male and 101 [39%] female) who were discharged from hospital with PCR-confirmed or clinically diagnosed COVID-19 between March 1, 2020, and Nov 1, 2021, and 52 non-COVID-19 controls from the community (mean age 49 years [SD 14]; 30 [58%] male and 22 [42%] female) were included in the analysis. Patients were assessed at a median of 5·0 months (IQR 4·2–6·3) after hospital discharge. Compared with non-COVID-19 controls, patients were older, living with more obesity, and had more comorbidities. Multiorgan abnormalities on MRI were more frequent in patients than in controls (157 [61%] of 259 vs 14 [27%] of 52; p<0·0001) and independently associated with COVID-19 status (odds ratio [OR] 2·9 [95% CI 1·5–5·8]; padjusted=0·0023) after adjusting for relevant confounders. Compared with controls, patients were more likely to have MRI evidence of lung abnormalities (p=0·0001; parenchymal abnormalities), brain abnormalities (p<0·0001; more white matter hyperintensities and regional brain volume reduction), and kidney abnormalities (p=0·014; lower medullary T1 and loss of corticomedullary differentiation), whereas cardiac and liver MRI abnormalities were similar between patients and controls. Patients with multiorgan abnormalities were older (difference in mean age 7 years [95% CI 4–10]; mean age of 59·8 years [SD 11·7] with multiorgan abnormalities vs mean age of 52·8 years [11·9] without multiorgan abnormalities; p<0·0001), more likely to have three or more comorbidities (OR 2·47 [1·32–4·82]; padjusted=0·0059), and more likely to have a more severe acute infection (acute CRP >5mg/L, OR 3·55 [1·23–11·88]; padjusted=0·025) than those without multiorgan abnormalities. Presence of lung MRI abnormalities was associated with a two-fold higher risk of chest tightness, and multiorgan MRI abnormalities were associated with severe and very severe persistent physical and mental health impairment (PHOSP-COVID symptom clusters) after hospitalisation. Interpretation: After hospitalisation for COVID-19, people are at risk of multiorgan abnormalities in the medium term. Our findings emphasise the need for proactive multidisciplinary care pathways, with the potential for imaging to guide surveillance frequency and therapeutic stratification

Eradicating down the food chain: optimal multispecies eradication schedules for a commonly encountered invaded island ecosystem

Islands are global hotspots of both biodiversity and extinction. Invasive species are a primary threat, and the majority of islands have been invaded by more than one. Multispecies eradications are essential for conserving the biodiversity of these islands, but experience has shown that eradicating species at the wrong time can be disastrous for endemic species. Managers not only have to decide how to eradicate each invasive species, they need to determine when to target each species, and how to control multiple species with a limited budget. We use dynamic control theory to show that, when resources are limited, species should be eradicated in a particular order (an eradication schedule). We focus on a common invaded island ecosystem motif, where one invasive predator consumes two prey species (one endemic, one invasive), and managers wish to eradicate both invasives while ensuring the persistence of the endemic species. We identify the optimal eradication schedule for this entire class of problem. To illustrate the application of our solution, we also analyse a particular case study from California's Channel Islands. For any island ecosystem that shares this motif, managers should begin by allocating all of their resources towards invasive predator control. Only later should resources be shifted towards controlling the invasive prey. This shift should ideally be gradual, but an abrupt shift is very close to optimal. The Channel Islands case study confirms these findings. Targeting both species simultaneously is substantially suboptimal. We reach the robust conclusion that the same eradication schedule should be applied to any island with this ecosystem motif, even if the ecosystem contains different species to the Channel Islands case study. Synthesis and applications. Although very numerous, the world's invaded island ecosystems could be described by a limited range of invaded ecosystem motifs. By calculating robust optimal eradication schedules for each motif, the approach defined in this study could offer rapid decision-support for a large number of future conservation projects where specific data are scarce

Simultaneous invasive alien predator eradication delivers the best outcomes for protected island species

Invasive species on islands rarely occur in isolation, and their removal will affect other species, both natives and invasives. Hence, conservation interventions must proceed carefully to avoid unintended consequences. A common invaded ecosystem motif consists of an invasive apex predator, an invasive mesopredator, and a native prey species—for example feral cats, rats and native seabirds. Eradication programs that specifically target apex predators can lead to mesopredator release, which may (and paradoxically) increase negative impacts on native species. We seek to develop management strategies that can remove both invasive predators, while allowing for the best recovery scenario for the native species. Specifically, we use systems of differential equations to model interacting species, and we seek to understand whether the two invasive species should be eradicated sequentially or simultaneously, when the latter option means that scarce management resources must be shared between the species. We find that (1) simultaneous eradication of both invasive species provides the greatest benefit for the native species, but (2) a sequential approach can be cheaper. Importantly, cheaper strategies incur the risk of poor native species recovery. Whether the cheaper option is to remove the apex predator first or the mesopredator first depends primarily on whether the mesopredator prefers the native species or alternative food sources. Hence, with limited knowledge of prey preferences, the simulations predator eradication strategy has the best chance of minimising unintended negative effects for native prey species

Data from: Translocation strategies for multiple species depend on interspecific interaction type

Conservation translocations – anthropogenic movements of species to prevent their extinction – have increased substantially over the last few decades. Although multiple species are frequently moved to the same location, current translocation guidelines consider species in isolation. This practice ignores important interspecific interactions, and thereby risks translocation failure. We model three different two-species systems to illustrate the inherent complexity of multi-species translocations, and to assess the influence of different interaction types (consumer-resource, mutualism, and competition) on translocation strategies. We focus on how these different interaction types influence the optimal founder population sizes for successful translocations, and the order in which the species are moved (simultaneous or sequential). Further, we assess the effect of interaction strength in simultaneous translocations, and the time delay between translocations when moving two species sequentially. Our results show that translocation decisions need to reflect the type of interaction. While all translocations of interacting species require a minimum founder population size, which is demarked by an “extinction boundary”, consumer-resource translocations also have a maximum founder population limit. Above the minimum founder size, increasing the number of translocated individuals leads to a substantial increase in the extinction boundary of competitors and consumers, but not of mutualists. Competitive and consumer-resource systems benefit from sequential translocations; but the order of translocations does not change the outcomes for mutualistic interaction partners noticeably. Interspecific interactions are important processes that shape population dynamics, and should therefore be incorporated into the quantitative planning of multispecies translocations. Our findings apply whenever interacting species are moved, for example, in reintroductions, conservation introductions, biological control or ecosystem restoration

Identifying species at coextinction risk when detection is imperfect: Model evaluation and case study

Losing a species from a community can cause further extinctions, a process also known as coextinction. The risk of being extirpated with an interaction partner is commonly inferred from a species' host-breadth, derived from observing interactions between species. But observational data suffers from imperfect detection, making coextinction estimates highly unreliable. To address this issue and to account for data uncertainty, we fit a hierarchical N-mixture model to individual-level interaction data from a mutualistic network. We predict (1) with how many interaction partners each species interacts (to indicate their coextinction risk) and (2) how completely the community was sampled. We fit the model to simulated interactions to investigate how variation in sampling effort, interaction probability, and animal abundances influence model accuracy and apply it to an empirical dataset of flowering plants and their insect visitors. The model performed well in predicting the number of interaction partners for scenarios with high abundances, but indicated high parameter uncertainty for networks with many rare species. Yet, model predictions were generally closer to the true value than the observations. Our mutualistic plant-insect community most closely resembled the scenario of high interaction rates with low abundances. Median estimates of interaction partners were frequently much higher than the empirical data indicate, but uncertainty was high. Our analysis suggested that we only detected 14-59% of the flower-visiting insect species, indicating that our study design, which is common for pollinator studies, was inadequate to detect many species. Imperfect detection strongly affects the inferences from observed interaction networks and hence, host specificity, specialisation estimates and network metrics from observational data may be highly misleading for assessing a species' coextinction risks. Our study shows how models can help to estimate coextinction risk, but also indicates the need for better data (i.e., intensified sampling and individual-level observations) to reduce uncertainty