Climate Mismatch Between Introduced Biological Control Agents and Their Invasive Host Plants: Improving Biological Control of Tropical Weeds in Temperate Regions

Many weed biological control programs suffer from large-scale spatial variation in success due to restricted distributions or abundances of agents in temperate climates. For some of the world’s worst aquatic weeds, agents are established but overwintering conditions limit their survival in higher latitudes or elevations. The resulting need is for new or improved site- or region-specific biological control tools. Here, we review this challenge with a focus on low-temperature limitations of agents and propose a roadmap for improving success. Investigations across spatial scales, from global (e.g., foreign exploration), to local (selective breeding), to individual organisms (molecular modification), are discussed. A combination of traditional (foreign) and non-traditional (introduced range) exploration may lead to the discovery and development of better-adapted agent genotypes. A multivariate approach using ecologically relevant metrics to quantify and compare cold tolerance among agent populations is likely required. These data can be used to inform environmental niche modeling combined with mechanistic modeling of species’ fundamental climate niches and life histories to predict where, when, and at what abundance agents will occur. Finally, synthetic and systems biology approaches in conjunction with advanced modern genomics, gene silencing and gene editing technologies may be used to identify and alter the expression of genes enhancing cold tolerance, but this technology in the context of weed biological control has not been fully explored.

Genesis, Evolution, and Genetic Diversity of the Hexaploid, Narrow Endemic Centaurea tentudaica

Within the genus Centaurea L., polyploidy is very common, and it is believed that, as to all angiosperms, it was key in the history of its diversification and evolution. Centaurea tentudaica is a hexaploid from subsect. Chamaecyanus of unknown origin. In this study, we examined the possible autopolyploid or allopolyploid origin using allozymes and sequences of three molecular markers: nuclear-ribosomic region ETS, and low-copy genes AGT1 and PgiC. We also included three species geographically and morphologically close to C. tentudaica: C. amblensis, C. galianoi, and C. ornata. Neighbor-Net and Bayesian analyses show a close relationship between C. amblensis and C. tentudaica and no relationship to any of the other species, which suggest that C. tentudaica is an autopolyploid of C. amblensis. Allozyme banding pattern also supports the autopolyploidy hypothesis and shows high levels of genetic diversity in the polyploid, which could suggest multiple origins by recurrent crosses of tetraploid and diploid cytotypes of C. amblensis. Environmental niche modeling was used to analyze the distribution of the possible parental species during the present, Last Glacial Maximum (LGM), Last Interglacial Period (LIG), and Penultimate Glacial Maximum (PGM) environmental conditions. Supporting the molecular suggestions that C. tentudaica originated from C. amblensis, environmental niche modeling confirms that past distribution of C. amblensis overlapped with the distribution of C. tentudaica.

Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage

We examine how different datasets, including georeferenced hardcopy maps of different extents and georeferenced herbarium specimens (spanning the range from 100 to 85,000 km2) influence ecological niche modeling. We check 13 of the available environmental niche modeling algorithms, using 30 metrics to score their validity and evaluate which are useful for the selection of the best model. The validation is made using an independent dataset comprised of presences and absences collected in a range-wide field survey of Carpathian endemic plant Leucanthemum rotundifolium (Compositae). Our analysis of models’ predictive performances indicates that almost all datasets may be used for the construction of a species distributional range. Both very local and very general datasets can produce useful predictions, which may be more detailed than the original ranges. Results also highlight the possibility of using the data from manually georeferenced archival sources in reconstructions aimed at establishing species’ ecological niches. We discuss possible applications of those data and associated problems. For the evaluation of models, we suggest employing AUC, MAE, and Bias. We show an example of how AUC and MAE may be combined to select the model with the best performance.

A reassessment of Mappia (Icacinaceae) taxonomy using environmental data

Background and Aims: Mappia (Icacinaceae) is a genus comprising four species inhabiting Mesoamerica and the Greater Antilles. In the most recent phylogenetic analysis based on morphological data, three species, representing a continental clade (Mappia longipes, M. mexicana and M. multiflora) sister to the Antillean species M. racemosa, were supported. Our aims in this study were to evaluate whether environmental data support the previous hypothesis in Mappia entities. Methods: In this study, we use ecological niche analysis (environmental niche modeling and niche divergence/conservatism tests) and multivariate analysis of variance (MANOVA) to test the previous morphological hypothesis at species and infraspecific level. Key results: Ecological differentiation between M. multiflora distributed from southeast Mexico to Costa Rica and M. racemosa occurring in Cuba, Jamaica, and Puerto Rico (Greater Antilles) was found, but not between the infraspecific taxa within the Antilles (M. racemosa var. brachycarpa, and M. racemosa var. racemosa). Conclusions: Our study brings an important signal of the ecological divergence between closely related species, but with disjunct patterns of distribution.

Assessing the status of critically endangered Kondana soft-furred rat (Millardia kondana) using integrative taxonomy: combining evidence from morphological, molecular and environmental niche modeling

Kondana soft-furred rat is a critically endangered (CR) species, known from a single locality – Sinhgad in the northern Western Ghats, India. However, the taxonomic status of this species is uncertain due to its close resemblance to the widely distributed soft-furred field rat Millardia meltada, which has serious implications on the conservation status of Millardia kondana. In this study, we assessed the current taxonomic status of M. kondana through an integrative approach combining morphological, molecular and environmental niche modeling analyses. We collected morphological data from the specimens around Sinhgad as well as preserved specimens in the museum. Both morphological and two-dimensional (2D) morphometrical analyses showed a significant difference between M. kondana and M. meltada. Molecular phylogeny based on cytochrome b gene revealed a sister relationship between M. kondana and M. meltada, and both species form distinct well-supported monophyletic clades. Niche modeling also predicted niche segregation between the two species: M. kondana preferred areas with a high elevation and precipitation seasonality while M. meltada favored regions with a low elevation and precipitation. We confirmed that M. kondana is taxonomically distinct from M. meltada, and based on our estimates of its occurrence and occupancy, M. kondana continues to be treated as CR until further detailed investigations.

Temporal differentiation in environmental niche modeling of Nearctic narrow-winged damselflies (Odonata: Coenagrionidae)

Narrow-winged damselflies (Odonata: Coenagrionidae) can be observed in a variety of habitats, by both professional collectors and amateur odonatologists. Their abundance and ease of recognition has resulted in a large amount of occurrence data, which can be used to establish species distribution maps through environmental niche modeling. Distributional models often aim to maximize the quantity of occurrence points and environmental variables to relate to the distribution, neglecting both the quality and overlap of these two datasets when generating the models. In order to examine the effects of temporal data and environmental variables influencing change in species distributions, we used occurrence data for twelve species of Coenagrionidae damselflies to generate niche models separated by time periods of specimen collection. Our study examines environmental niche models generated for four time periods for each of these coenagrionid species: Amphiagrion abbreivatum (Selys,1876), Enallagma civile (Hagen,1861), Chromagrion conditum (Hagen in Selys, 1876), Nehalennia gracilis Morse, 1895, Enallagma hageni (Walsh, 1863), Hesperagrion heterodoxum (Selys, 1868), Nehalennia irene (Hagen, 1861), Argia moesta (Hagen, 1861), Ischnura ramburii (Selys, 1850), Argia tibialis (Rambur, 1842), Argia translata Hagen in Selys, 1865, and Argia vivida Hagen in Selys, 1865. The best supported models in each analysis were generated with occurrences of specimens collected from the 1970s to 2000s, and we used occurrence data outside of this range, from the 1800s to 2017, to compare the consistency of model predictions based on specimens of different time periods. In this approach, combining traditional environmental niche modeling and analysis of the specimen records themselves, we have found that ranges for narrow-winged damselflies expand over time, with increase in distributional coverage and decrease in model strength without temporal overlap between occurrences and environmental variables.

Temporal differentiation in environmental niche modeling of Nearctic narrow-winged damselflies (Odonata: Coenagrionidae)

Narrow-winged damselflies (Odonata: Coenagrionidae) can be observed in a variety of habitats, by both professional collectors and amateur odonatologists. Their abundance and ease of recognition has resulted in a large amount of occurrence data, which can be used to establish species distribution maps through environmental niche modeling. Distributional models often aim to maximize the quantity of occurrence points and environmental variables to relate to the distribution, neglecting both the quality and overlap of these two datasets when generating the models. In order to examine the effects of temporal data and environmental variables influencing change in species distributions, we used occurrence data for twelve species of Coenagrionidae damselflies to generate niche models separated by time periods of specimen collection. Our study examines environmental niche models generated for four time periods for each of these coenagrionid species: Amphiagrion abbreivatum (Selys,1876), Enallagma civile (Hagen,1861), Chromagrion conditum (Hagen in Selys, 1876), Nehalennia gracilis Morse, 1895, Enallagma hageni (Walsh, 1863), Hesperagrion heterodoxum (Selys, 1868), Nehalennia irene (Hagen, 1861), Argia moesta (Hagen, 1861), Ischnura ramburii (Selys, 1850), Argia tibialis (Rambur, 1842), Argia translata Hagen in Selys, 1865, and Argia vivida Hagen in Selys, 1865. The best supported models in each analysis were generated with occurrences of specimens collected from the 1970s to 2000s, and we used occurrence data outside of this range, from the 1800s to 2017, to compare the consistency of model predictions based on specimens of different time periods. In this approach, combining traditional environmental niche modeling and analysis of the specimen records themselves, we have found that ranges for narrow-winged damselflies expand over time, with increase in distributional coverage and decrease in model strength without temporal overlap between occurrences and environmental variables.