Effects of herbivory on the reproductive effort of 4 prairie perennials

BACKGROUND: Herbivory can affect every aspect of a plant's life. Damaged individuals may show decreased survivorship and reproductive output. Additionally, specific plant species (legumes) and tissues (flowers) are often selectively targeted by herbivores, like deer. These types of herbivory influence a plant's growth and abundance. The objective of this study was to identify the effects of leaf and meristem removal (simulated herbivory within an exclosure) on fruit and flower production in four species (Rhus glabra, Rosa arkansana, Lathyrus venosus, and Phlox pilosa) which are known targets of deer herbivory. RESULTS: Lathyrus never flowered or went to seed, so we were unable to detect any treatment effects. Leaf removal did not affect flower number in the other three species. However, Phlox, Rosa, and Rhus all showed significant negative correlations between seed mass and leaf removal. Meristem removal had a more negative effect than leaf removal on flower number in Phlox and on both flower number and seed mass in Rosa. CONCLUSIONS: Meristem removal caused a greater response than defoliation alone in both Phlox and Rosa, which suggests that meristem loss has a greater effect on reproduction. The combination of leaf and meristem removal as well as recruitment limitation by deer, which selectively browse for these species, is likely to be one factor contributing to their low abundance in prairies

The tree cover and temperature disparity in US urbanized areas: Quantifying the association with income across 5,723 communities

Urban tree cover provides benefits to human health and well-being, but previous studies suggest that tree cover is often inequitably distributed. Here, we use National Agriculture Imagery Program digital ortho photographs to survey the tree cover inequality for Census blocks in US large urbanized areas, home to 167 million people across 5,723 municipalities and other Census-designated places. We compared tree cover to summer land surface temperature, as measured using Landsat imagery. In 92% of the urbanized areas surveyed, low-income blocks have less tree cover than high-income blocks. On average, low-income blocks have 15.2% less tree cover and are 1.5˚C hotter than high-income blocks. The greatest difference between low- and high-income blocks was found in urbanized areas in the Northeast of the United States, where low-income blocks in some urbanized areas have 30% less tree cover and are 4.0˚C hotter. Even after controlling for population density and built-up intensity, the positive association between income and tree cover is significant, as is the positive association between proportion non-Hispanic white and tree cover. We estimate, after controlling for population density, that low-income blocks have 62 million fewer trees than high-income blocks, equal to a compensatory value of $56 billion ($1,349/person). An investment in tree planting and natural regeneration of $17.6 billion would be needed to close the tree cover disparity, benefitting 42 million people in low-income blocks

Integrating genetics into marine conservation planning in South Africa

Thesis (MSc)--Stellenbosch University, 2017.ENGLISH ABSTRACT: The mounting threats to biodiversity and global alteration of habitat and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision-making. Yet there is no clear-cut guidance on how genetic features can be incorporated into conservation planning processes, with several genetic metrics with different ecological and evolutionary relevance to choose from. Genetic patterns also differ between species, but the potential trade-offs amongst different genetic objectives for multiple species in conservation planning are currently understudied. Therefore, the first chapter of this thesis compares spatial conservation prioritizations derived from two metrics of both genetic diversity (nucleotide and haplotype diversity) and genetic isolation (private haplotypes and local genetic differentiation) for five marine species. The results from Chapter One show that conservation plans based solely on habitat representation noticeably differ from those additionally including genetic data, and that all four genetic metrics select similar conservation priority areas. The second chapter builds on the findings of Chapter One by comparing conservation solutions from three marker types (mitochondrial DNA, neutral nuclear DNA, and adaptive nuclear DNA) for the two most genetically distinct species from the multi-species data set. Next generation sequencing was used to identify single nucleotide polymorphism (SNP) variation in both the Cape urchin (P. angulosus) and the Granular limpet (S. granularis), both of which showed high levels of genomic diversity and signals of adaptation to local ecotypes. When comparing the genetic variation between the mitochondrial DNA (mtDNA) and SNP markers within a spatial conservation framework, the solutions show a wide range of spatial priorities, yet the spatial similarities between the different marker types are not consistent across the different species approaches. Largely, the findings from this project suggest that selected species and genetic marker(s) chosen will alter all conservation solutions. Importantly, increasing the amount of genetic information leads to more distinct conservation priorities, resulting in a clearer picture of community-level evolutionary hotspots within the planning region.AFRIKAANSE OPSOMMING: Geen opsomming beskikbaa

Using multi-species seascape genomics to conserve areas of evolutionary importance

Thesis (PhD)--Stellenbosch University, 2021.ENGLISH ABSTRACT: Understanding the environmental footprints on species and genetic biodiversity is a key concern in molecular ecology and conservation genetics. As species are increasingly under pressure from anthropogenic climate change, understanding how rapid environmental changes will influence intra- and interspecific diversity is essential if we are to conserve functioning ecosystems. This PhD thesis used the unique environmental backdrop of the South African coastline to infer how environmental variables over space and time shape multiple facets of biological variation. Specifically, this thesis utilised seascape genomic analyses to test the strong environmental gradients within South Africa against the molecular variation of three rocky intertidal species: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis). The first chapter evaluated which contemporary seascape features most strongly correlate with neutral and adaptive intraspecific diversity across species. Here, the results show that gene-environment relationships are species-specific, with the crab showing less population differentiation, strongly influenced by sea-surface salinity, and the urchin and limpet showing a west-east population differentiation predominantly influenced by sea-surface and air temperature. Chapter Two tested the relative influence of historical climatic stability versus contemporary species distributions in shaping patterns of neutral diversity of the three species. The results from this chapter indicate that historical climatic refugia since the Last Glacial Maximum are potentially stronger predictors of contemporary molecular diversity hotspots than the species’ current distribution. The third research chapter evaluated the vulnerability of the three study species with regards to future climatic change, both at two time-points and under two emission scenarios. Here, the results highlight how future responses to global change will likely differ among species, as well as among populations within each species. In the final chapter, the patterns uncovered in the three data chapters, pertaining to genomic diversity and vulnerability, climatic stability, and adaptive potential, are combined in a conservation planning framework to identify areas of evolutionary importance, which can be thought of as priority areas for forward-thinking conservation action. As a whole, this thesis used novel ecological and evolutionary models to understand the spatio-temporal interplay between species, genes, and environment, and used this information to guide conservation action within South Africa.AFRIKAANSE OPSOMMING: Geen opsomming beskikbaar.Doctora

Biophilia beyond the Building: Applying the Tools of Urban Biodiversity Planning to Create Biophilic Cities

In response to the widely recognized negative impacts of urbanization on biodiversity, many cities are reimagining urban design to provide better biodiversity support. Some cities have developed urban biodiversity plans, primarily focused on improving biodiversity support and ecosystem function within the built environment through habitat restoration and other types of urban greening projects. The biophilic cities movement seeks to reframe nature as essential infrastructure for cities, seamlessly integrating city and nature to provide abundant, accessible nature for all residents and corresponding health and well-being outcomes. Urban biodiversity planning and biophilic cities have significant synergies in their goals and the means necessary to achieve them. In this paper, we identify three key ways by which the urban biodiversity planning process can support biophilic cities objectives: engaging the local community; identifying science-based, quantitative goals; and setting priorities for action. Urban biodiversity planning provides evidence-based guidance, tools, and techniques needed to design locally appropriate, pragmatic habitat enhancements that support biodiversity, ecological health, and human health and well-being. Developing these multi-functional, multi-benefit strategies that increase the abundance of biodiverse nature in cities has the potential at the same time to deepen and enrich our biophilic experience in daily life

Opportunities and Constraints in Characterizing Landscape Distribution of an Invasive Grass from Very High Resolution Multi-Spectral Imagery

Understanding spatial distributions of invasive plant species at early infestation stages is critical for assessing the dynamics and underlying factors of invasions. Recent progress in very high resolution remote sensing is facilitating this task by providing high spatial detail over whole-site extents that are prohibitive to comprehensive ground surveys. This study assessed the opportunities and constraints to characterize landscape distribution of the invasive grass medusahead (Elymus caput-medusae) in a ∼36.8 ha grassland in California, United States from 0.15m-resolution visible/near-infrared aerial imagery at the stage of late spring phenological contrast with dominant grasses. We compared several object-based unsupervised, single-run supervised and hierarchical approaches to classify medusahead using spectral, textural, and contextual variables. Fuzzy accuracy assessment indicated that 44–100% of test medusahead samples were matched by its classified extents from different methods, while 63–83% of test samples classified as medusahead had this class as an acceptable candidate. Main sources of error included spectral similarity between medusahead and other green species and mixing of medusahead with other vegetation at variable densities. Adding texture attributes to spectral variables increased the accuracy of most classification methods, corroborating the informative value of local patterns under limited spectral data. The highest accuracy across different metrics was shown by the supervised single-run support vector machine with seven vegetation classes and Bayesian algorithms with three vegetation classes; however, their medusahead allocations showed some “spillover” effects due to misclassifications with other green vegetation. This issue was addressed by more complex hierarchical approaches, though their final accuracy did not exceed the best single-run methods. However, the comparison of classified medusahead extents with field segments of its patches overlapping with survey transects indicated that most methods tended to miss and/or over-estimate the length of the smallest patches and under-estimate the largest ones due to classification errors. Overall, the study outcomes support the potential of cost-effective, very high-resolution sensing for the site-scale detection of infestation hotspots that can be customized to plant phenological schedules. However, more accurate medusahead patch delineation in mixed-cover grasslands would benefit from testing hyperspectral data and using our study’s framework to inform and constrain the candidate vegetation classes in heterogeneous locations

Opportunities and Constraints in Characterizing Landscape Distribution of an Invasive Grass from Very High Resolution Multi-Spectral Imagery

Understanding spatial distributions of invasive plant species at early infestation stages is critical for assessing the dynamics and underlying factors of invasions. Recent progress in very high resolution remote sensing is facilitating this task by providing high spatial detail over whole-site extents that are prohibitive to comprehensive ground surveys. This study assessed the opportunities and constraints to characterize landscape distribution of the invasive grass medusahead (Elymus caput-medusae) in a ∼36.8 ha grassland in California, United States from 0.15m-resolution visible/near-infrared aerial imagery at the stage of late spring phenological contrast with dominant grasses. We compared several object-based unsupervised, single-run supervised and hierarchical approaches to classify medusahead using spectral, textural, and contextual variables. Fuzzy accuracy assessment indicated that 44–100% of test medusahead samples were matched by its classified extents from different methods, while 63–83% of test samples classified as medusahead had this class as an acceptable candidate. Main sources of error included spectral similarity between medusahead and other green species and mixing of medusahead with other vegetation at variable densities. Adding texture attributes to spectral variables increased the accuracy of most classification methods, corroborating the informative value of local patterns under limited spectral data. The highest accuracy across different metrics was shown by the supervised single-run support vector machine with seven vegetation classes and Bayesian algorithms with three vegetation classes; however, their medusahead allocations showed some “spillover” effects due to misclassifications with other green vegetation. This issue was addressed by more complex hierarchical approaches, though their final accuracy did not exceed the best single-run methods. However, the comparison of classified medusahead extents with field segments of its patches overlapping with survey transects indicated that most methods tended to miss and/or over-estimate the length of the smallest patches and under-estimate the largest ones due to classification errors. Overall, the study outcomes support the potential of cost-effective, very high-resolution sensing for the site-scale detection of infestation hotspots that can be customized to plant phenological schedules. However, more accurate medusahead patch delineation in mixed-cover grasslands would benefit from testing hyperspectral data and using our study’s framework to inform and constrain the candidate vegetation classes in heterogeneous locations

Positive litter feedbacks of an introduced species reduce native diversity and promote invasion in Californian grasslands

Questions: Californian grasslands have a long history of invasion, starting with the introduction of exotic forage species a century ago, and followed by newer waves of invaders. Both exotic and invasive species produce large amounts of litter, but the importance of litter accumulation on the growth and expansion of these species has not been rigorously assessed. We addressed the following questions: (1) do litter type (exotic or invasive species) and litter quantity affect exotic and invasive plant performance; (2) at which plant life stages does litter accumulation effects occur; and (3) is litter accumulation impacting native species recruitment and diversity? Location: Semi-natural grasslands, northern California. Methods: We created litter quantity gradients (0, 62.5, 125, 250 or 500 g.m(-2)) of three litter types (exotic or invasive species litter or a mixture of both). We evaluated litter effects on the germination, recruitment, production of flowers and biomass production of the exotic Avena fatua, the invasive Elymus caput-medusae and a mixture of native species. We used litter depth as a proxy for litter accumulation and measured litter impacts on light availability at ground level, soilmoisture, soil andmicrobial C and N. Results: We found a significant litter depth impact on all species, but no litter type effects. Litter accumulation principally reduced light availability at ground level and positively affected exotic and invasive species at different life-history stages. Above-ground biomass production of the exotic species Avena increased with increased litter depth, suggesting a litter accumulation feedback. The invasive species Elymus responded to increased litter with increased seed production, rather than biomass production. In contrast, litter negatively affected the recruitment and diversity of native species. Conclusion: Overall, our findings point to cascading effects in invasion with positive litter accumulation feedbacks of an exotic species simultaneously reducing native diversity and promoting seed production of a more recent invasive arrival. These results have strong consequences for invasion management and suggest that litter removal practices, such as burning and grazing, would better succeed at limiting the growth and spread of invasive species than herbicide application or seeding

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

<div><p>Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.</p></div

Disturbance and aspect.

<p>The effects of disturbance (grazing removal, burning) on directional change and temporal fluctuation, and the relationship between aspect (north or south facing) and directional change where bars represent means (± 1SE). Directional change is the slope of the relationship between the square root of time lag (or time between sampling points) and Bray-Curtis dissimilarity in species composition for each plot. Temporal fluctuation is quantified as the root mean square of the residuals from the linear regression line relating time lag to dissimilarity in species composition for each plotSignificant relationships are indicated with different letters.</p