Modeling population dynamics, landscape structure, and management decisions for controlling the spread of invasive plants

Spatial prioritization for widespread invasive species control: Trade-offs between current impact and future spread

Spatially explicit prioritization of invasive species control is a complex issue, requiring consideration of trade-offs between immediate and future benefits. This study aimed to prioritize management efforts to account for current and future threats from widespread invasions and examine the strength of the trade-off between these different management goals. As a case study, we identified spatially explicit management priorities for the widespread invasion of introduced willow into riparian and wetland habitats across a 102,145-km2 region in eastern Australia. In addition to targeting places where willow threatens biodiversity now, a second set of management goals was to limit reinfestation and further spread that could occur via two different mechanisms (downstream and by wind). A model of likely willow distribution across the region was combined with spatial data for biodiversity (native vegetation, threatened species and communities), ecological conditions, management costs, and two potential dispersal layers. We used systematic conservation planning software (Zonation) to prioritize where willow management should be focussed across more than 100,000 catchments for a range of different scenarios that reflected different weights between management goals. For willow invasion, we found that we could prioritize willow management to reduce the future threat of dispersal downstream with little reduction in the protection of biodiversity. However, accounting for future threats from wind dispersal resulted in a stronger trade-off with protection of threatened biodiversity. The strongest trade-off was observed when both dispersal mechanisms were considered together. This study shows that considering current and future goals together offers the potential to substantially improve conservation outcomes for invasive species management. Our approach also informs land managers about the relative trade-offs among different management goals under different control scenarios, helping to make management decisions more transparent. This approach can be used for other widespread invasive species to help improve invasive species management decisions.

Modeling population dynamics of invasive pines to optimize their control in native grasslands of Argentina

The spread of invasive alien species over natural environments has become one of the most serious threats to biodiversity and the functioning of ecosystems worldwide. Understanding the population attributes that allow a given species to become invasive is crucial for improving prevention and control interventions. Pampas grasslands are particularly sensitive to the invasion of exotic woody plants. In particular, the Ventania Mountains undergo the advance of alien woody plants; among which the Aleppo pine (Pinus halepensis) stands out due to the extension of the area it covers and the magnitude of the ecological changes associated to its presence. Using a model that describes the population dynamics of the species in the area, we evaluated the expected behavior of the population under different environmental conditions and different management scenarios. When the effect of stochastic fires was simulated, the growth rate was greater than 1 for all the frequencies considered, peaking under fires every nine years, on average. When evaluating the effect of periodic mechanical control of the adult population, the reduction in growth rate was insufficient, except for cutting intensities that significantly exceeded the current operational capacity of the area. Under prescribed fire scenarios, on the other hand, burning frequencies greater than seven years resulted in population reductions. The results highlight the importance of fire in regulating the population of P. halepensis in the Ventania Mountains, with contrasting effects depending on the frequency with which it occurs, which allows considering it as an effective environmental management option for the control of the species.

Sustainable synthesis of bionanomaterials using non-native plant extracts for maintaining ecological balance: A computational bibliography analysis

Biological approaches via biomolecular extracts of bacteria, fungi, or plants have recently been introduced as an alternative approach to synthesizing less or nontoxic nanomaterials, compared to conventional physical and chemical approaches. Among these biological methods, plant-mediated approaches (phytosynthesis) are reported to be highly beneficial for large-scale, nontoxic nanomaterial synthesis. However, plant-mediated synthesis of nanomaterials using native plant extract can lead to bioprospecting issues and deforestation challenges. On the other hand, non-native or invasive plants are non-indigenous to a particular geographic location that can grow and spread rapidly, ultimately disrupting the local and endogenous plant communities or ecosystems. Thus, controlling or eradicating these non-native plants before they damage the ecosystem is necessary. Even though mechanical, chemical, and biological approaches are available to control non-native plants, all these methods possess certain limitations, such as environmental toxicity, disturbance in the nutrient cycle, and loss of genetic integrity. Therefore, non-native plants were recently proposed as a novel sustainable source of phytochemicals for preparing nanomaterials via green chemistry, mainly metallic nanoparticles, as an alternative to native, agriculture-based, or medicinal plants. This work aims to cover a literature gap on plant-mediated bionanomaterial synthesis with an overview and bibliography analysis of non-native plants via novel data mining and advanced visualization tools. In addition, the potential of non-native plants as a sustainable, green chemistry-based alternative for bionanomaterial preparation for maintaining ecological balance, the mechanism of formation via phytochemicals, and their possible applications to promote their control and spread were also discussed. The bibliography analysis revealed that only an average of 4 articles have been published in the last 10 years (2013-2023) on non-native/invasive plants for nanomaterial synthesis, which shows the significance of this article.

Partial differential equation models for invasive species spread in the presence of spatial heterogeneity

Models of invasive species spread often assume that landscapes are spatially homogeneous; thus simplifying analysis but potentially reducing accuracy. We extend a recently developed partial differential equation model for invasive conifer spread to account for spatial heterogeneity in parameter values and introduce a method to obtain key outputs (e.g. spread rates) from computational simulations. Simulations produce patterns of spatial spread which appear qualitatively similar to observed patterns in grassland ecosystems invaded by exotic conifers, validating our spatially explicit strategy. We find that incorporating spatial variation in different parameters does not significantly affect the evolution of invasions (which are characterised by a long quiescent period followed by rapid evolution towards to a constant rate of invasion) but that distributional assumptions can have a significant impact on the spread rate of invasions. Our work demonstrates that spatial variation in site-suitability or other parameters can have a significant impact on invasions and must be considered when designing models of invasive species spread.

From UAV to PlanetScope: Upscaling fractional cover of an invasive species Rosa rugosa

Invasive plant species pose a direct threat to biodiversity and ecosystem services. Among these, Rosa rugosa has had a severe impact on Baltic coastal ecosystems in recent decades. Accurate mapping and monitoring tools are essential to quantify the location and spatial extent of invasive plant species to support eradication programs. In this paper we combined RGB images obtained using an Unoccupied Aerial Vehicle, with multispectral PlanetScope images to map the extent of R. rugosa at seven locations along the Estonian coastline. We used RGB-based vegetation indices and 3D canopy metrics in combination with a random forest algorithm to map R. rugosa thickets, obtaining high mapping accuracies (Sensitivity = 0.92, specificity = 0.96). We then used the R. rugosa presence/absence maps as a training dataset to predict the fractional cover based on multispectral vegetation indices derived from the PlanetScope constellation and an Extreme Gradient Boosting algorithm (XGBoost). The XGBoost algorithm yielded high fractional cover prediction accuracies (RMSE = 0.11, R² = 0.70). An in-depth accuracy assessment based on site-specific validations revealed notable differences in accuracy between study sites (highest R² = 0.74, lowest R² = 0.03). We attribute these differences to the various stages of R. rugosa invasion and the density of thickets. In conclusion, the combination of RGB UAV images and multispectral PlanetScope images is a cost-effective method to map R. rugosa in highly heterogeneous coastal ecosystems. We propose this approach as a valuable tool to extend the highly local geographical scope of UAV assessments into wider areas and regional evaluations.

Climatic Variability Caused by Topographic Barrier Prevents the Northward Spread of Invasive Ageratina adenophora

Ageratina adenophora (Spreng.) R.M.King & H.Rob. is one of the most threatening invasive alien plants in China. Since its initial invasion into Yunnan in the 1940s, it spread rapidly northward to southern Mount Nyba in Sichuan, which lies on the eastern edge of the Qinghai-Tibet Plateau. During fieldwork, we found an interesting phenomenon: A. adenophora failed to expand northward across Mount Nyba, even after the opening of the 10 km tunnel, which could have served as a potential corridor for its spread. In this work, to explore the key factors influencing its distribution and spread patterns, we used a combination of ensemble species distribution models with the MigClim model. We found that the temperature annual range (TAR), precipitation of driest month (PDM), highway density (HW), and wind speed (WS) were the most predominant factors affecting its distribution. The north of Mount Nyba is not suitable for A. adenophora survival due to higher TAR. The spatial-temporal dynamic invasion simulation using MigClim further illustrated that the northward invasion of A. adenophora was stopped by Mount Nyba. Overall, Mount Nyba may act as a topographic barrier that causes environmental differences between its south and north sides, preventing the northward invasion of A. adenophora. However, other suitable habitats on the northern side of the mountain still face challenges because A. adenophora is likely to invade via other routes. Therefore, long-term monitoring is needed to prevent human-induced long-distance spread events.

Spatially explicit removal strategies increase the efficiency of invasive plant species control

Effective management strategies are needed to control expansion of invasive alien plant species and attenuate economic and ecological impacts. While previous theoretical studies have assessed optimal control strategies that balance economic costs and ecological benefits, less attention has been paid to the ways in which the spatial characteristics of individual patches may mediate the effectiveness of management strategies. We developed a spatially explicit cellular automaton model for invasive species spread, and compared the effectiveness of seven control strategies. These control strategies used different criteria to prioritize the removal of invasive species patches from the landscape. The different criteria were related to patch size, patch geometry, and patch position within the landscape. Effectiveness of strategies was assessed for both seed dispersing and clonally expanding plant species. We found that, for seed-dispersing species, removal of small patches and removal of patches that are isolated within the landscape comprised relatively effective control strategies. For clonally expanding species, removal of patches based on their degree of isolation and their geometrical properties comprised relatively effective control strategies. Subsequently, we parameterized the model to mimic the observed spatial distribution of the invasive species Antigonon leptopus on St. Eustatius (northern Caribbean). This species expands clonally and also disperses via seeds, and model simulations showed that removal strategies focusing on smaller patches that are more isolated in the landscape would be most effective and could increase the effectiveness of a 10-yr control strategy by 30-90%, as compared to random removal of patches. Our study emphasizes the potential for invasive plant species management to utilize recent advances in remote sensing, which enable mapping of invasive species at the high spatial resolution needed to quantify patch geometries. The presented results highlight how this spatial information can be used in the design of more effective invasive species control strategies.

Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty

Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13-20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.

Time to cut: population models reveal how to mow invasive common ragweed cost-effectively

Roadsides are an important habitat for invasive common ragweed, Ambrosiaartemisiifolia L., by facilitating seed dispersal. Reducing the size of roadside populations is therefore essential for confining this highly allergenic species. Here, we aim to determine the cost-effectiveness of mowing regimes varying in frequency and timing, by analysing population-level effects and underlying demographic processes. We constructed population models of A.artemisiifolia parameterised by demographic data for four unmanaged reference populations across Europe in two years. We integrated the effects of four experimental mowing regimes along Austrian road sides on plant performance traits of five years and experimental data on seed viability after cutting. All four experimental regimes reduced the projected intrinsic population growth rates (r) compared to the unmanaged controls by reducing plant height and seed viability, thereby counteracting increased size-dependent fecundity. The prevailing 2-cut regime in Austria (cutting during vegetative growth, here in June and just before seed ripening, here in September) performed least well and the reduction in r was mainly due to reduced seed viability after the second cut. The efficacy of the two best experimental regimes (alternative schemes for 2 or 3 cuts) was mainly due to cutting just before female flowering (here in August) by decreasing final adult plant height dramatically and thereby reducing seed numbers. Patterns were consistent across reference populations and years. Whether regimes reduced r below replacement level, however, varied per population, year and the survival rate of the seeds in the soil bank. Our model allowed projecting effects of five theoretical mowing regimes with untested combinations of cuts on r. By plotting r-cost relationships for all regimes, we identified the most cost-effective schemes for each cutting frequency (1–3 cuts). They all included the cut just before female flowering, highlighting the importance of cutting at this moment (here in August). Our work features i) the suitability of a modelling approach for the demography of an annual species with a seed bank, ii) the importance of seed viability in assessing mowing effects, iii) the use of population models in designing cost-effective mowing regimes.

Ancestral origins and invasion pathways in a globally invasive bird correlate with climate and influences from bird trade

Invasive species present a major threat to global biodiversity. Understanding genetic patterns and evolutionary processes that reinforce successful establishment is paramount for elucidating mechanisms underlying biological invasions. Among birds, the ring-necked parakeet (Psittacula krameri) is one of the most successful invasive species, established in over 35 countries. However, little is known about the evolutionary genetic origins of this species and what population genetic signatures tell us about patterns of invasion. We reveal the ancestral origins of populations across the invasive range and explore the potential influence of climate and propagule pressure from the pet trade on observed genetic patterns. Ring-necked parakeet samples representing the ancestral native range (n = 96) were collected from museum specimens, and modern samples from the invasive range (n = 855) were gathered from across Europe, Mauritius and Seychelles, and sequenced for two mitochondrial DNA markers comprising 868 bp of cytochrome b and control region, and genotyped at 10 microsatellite loci. Invasive populations comprise birds that originate predominantly from Pakistan and northern areas of India. Haplotypes associated with more northerly distribution limits in the ancestral native range were more prevalent in invasive populations in Europe, and the predominance of Asian haplotypes in Europe is consistent with the higher number of Asian birds transported by the pet trade outside the native range. Successful establishment of invasive species is likely to be underpinned by a combination of environmental and anthropogenic influences.

Integrating network ecology with applied conservation: a synthesis and guide to implementation

Ecological networks are a useful tool to study the complexity of biotic interactions at a community level. Advances in the understanding of network patterns encourage the application of a network approach in other disciplines than theoretical ecology, such as biodiversity conservation. So far, however, practical applications have been meagre. Here we present a framework for network analysis to be harnessed to advance conservation management by using plant-pollinator networks and islands as model systems. Conservation practitioners require indicators to monitor and assess management effectiveness and validate overall conservation goals. By distinguishing between two network attributes, the 'diversity' and 'distribution' of interactions, on three hierarchical levels (species, guild/group and network) we identify seven quantitative metrics to describe changes in network patterns that have implications for conservation. Diversity metrics are partner diversity, vulnerability/generality, interaction diversity and interaction evenness, and distribution metrics are the specialization indices d' and [Formula: see text] and modularity. Distribution metrics account for sampling bias and may therefore be suitable indicators to detect human-induced changes to plant-pollinator communities, thus indirectly assessing the structural and functional robustness and integrity of ecosystems. We propose an implementation pathway that outlines the stages that are required to successfully embed a network approach in biodiversity conservation. Most importantly, only if conservation action and study design are aligned by practitioners and ecologists through joint experiments, are the findings of a conservation network approach equally beneficial for advancing adaptive management and ecological network theory. We list potential obstacles to the framework, highlight the shortfall in empirical, mostly experimental, network data and discuss possible solutions.

Modeling the impacts of life-history traits, canopy gaps, and establishment location on woodland shrub invasions

We used an individual-based model to identify how localized patterns of woodland invasions by exotic shrubs are likely influenced by (1) observed variation in age at first reproduction and fecundity, (2) hypothesized effects of canopy gaps on these life-history traits and dispersal, and (3) initial establishment location. Rates of spread accelerated nearly twofold as age at first reproduction decreased from eight to three years or fecundity increased from 3 to 20 offspring per year, illustrating the need to better understand the factors that influence these life-history traits. Canopy gaps facilitated spread by influencing these life-history traits, but not through their effects on dispersal. Invasions starting at the woodland center spread more rapidly than do those starting along the woodland edge. These findings suggest that managers should not only prioritize the removal of shrubs that reproduce the earliest or produce the most offspring, but they should also focus on the invasions in woodlands with high canopy openness and/or that are located in woodland interiors. Investigated factors also affected other invasion characteristics, often in surprising ways. For example, those changes in age at first reproduction and fecundity that increased the rate of spread produced nonparallel patterns of change in the proportions of invasion reproducing, whether or not invasions exhibited clumped or scattered spatial arrangements, and invasional lag. Additionally, canopy gaps influenced these characteristics by increasing fecundity, but not by decreasing age at first reproduction or altering dispersal, suggesting that canopy gaps affect local patterns of exotic-shrub invasions primarily through their positive effects on fruit production.