In the light of the ongoing loss of biodiversity at the global scale, monitoring grasslands is nowadays of utmost importance considering their functional relevance in terms of the ecosystem services that they provide. Here, guidelines of the European Union like the Fauna-Flora-Habitat Directive and the European Agricultural fund for Rural Development with its HNV indicators are crucial. Indeed, they form the legal framework for nature conservation and define grasslands as one of their conservation targets, whose status needs to be assessed and reported by all member states on a regular basis. In the light of these reporting requirements, the need for a harmonised and thorough grassland monitoring is highly demanding since most member states are still currently adopting intensive field surveys or photointerpretation with differing levels of detail for mapping habitat distribution. To this purpose, a cost-effective solution is offered by Earth Observation data for which specific grassland monitoring methodologies shall be then implemented which are capable of processing multitemporal acquisitions collected throughout the entire growing season. Although optical data are most suited for characterising vegetation in terms of spectral information content, they are actually subject to weather conditions (especially cloud coverage), which hinder the possibility of collecting enough information over the full phenological cycle. Furthermore, so far only few studies started employing high and very high resolution optical time series for grassland habitat monitoring since they have become available e.g., from the RapidEye satellites, only in the recent past. To overcome this limitation, SAR systems can be employed which provide imagery independent from weather or daytime conditions, hence enabling vegetation analysis by means of complete time series. Compared to optical data, radar imagery is less affected by the physical-chemical characteristics of the surface, but rather it is sensitive to structural features like geometry and roughness. However, in this context presently only very few techniques have been implemented, which are anyhow not suitable to be employed in an operational framework. Furthermore, to address the classification task, supervised approaches (which require in situ information for all the land-cover classes present in the study area) represent the most accurate methodological solution; nevertheless, collecting an exhaustive ground truth is generally expensive both in terms of time and economic costs and is not even feasible when the test site is remote. However, in many applications the end-users are generally only interested in very few specific targeted land-cover classes which, for instance, have high ecological value or are associated with support actions, subsidies or benefits from national or international institutions. The categorisation of specific grasslands and habitat types as those addressed in this thesis falls within such category of problems, which is defined in the literature as targeted land-cover classification. In this framework, a robust and effective targeted classification system for the automatic identification of grassland types by means of multi-temporal and multi-polarised SAR data has been developed within this thesis. In particular, the proposed system is composed of three main blocks: the preprocessing of the SAR image time series including the Kennaugh decomposition, the feature extraction including multi-temporal filtering and texture analysis, and the hierarchical targeted classification, which consist of two phases where first a one-class classifier is employed to outline the merger of all the grassland types of interest considered as a single information class and then a multi-class classifier is applied for discriminating the specific targeted classes within the areas identified as positive by the one-class classifier. To evaluate the capabilities of the proposed methodology, several experimental trials have been carried out over two test sites located in Southern Bavaria (Germany) and Mecklenburg Western-Pomerania (Germany) for which six diverse datasets have been derived from multitemporal series of dualpol TerraSAR-X as well as dual-/quadpol Radarsat-2 images. Four among the Natura 2000 habitat types of the Fauna-Flora-Habitat Directive as well all High Nature Value grassland types have been considered as targeted classes for this study. Overall, the proposed system proved to be robust and confirmed the effectiveness of employing multitemporal and multi-polarisation VHR SAR data for discriminating habitat types and High Nature Value grassland types, exhibiting high potential for future employment even at larger scales. In particular, it could be demonstrated that the proposed hierarchical targeted classification approach outperforms the available state-of-the-art methods and has a clear advantage with respect to the standard approaches in terms of robustness, reliability and transferability.

Understanding the relative importance of density-dependent and density-independent factors in driving population dynamics is one of the oldest challenges in ecology, and may play a critical role in predicting the effects of climate change on populations. We used long-term observational data to describe patterns in plant population regulation for 57 forb and grass species from three different ecosystems (arid desert grassland, semiarid sagebrush steppe, and subhumid mixed-grass prairie). Using a hierarchical partitioning approach, we (i) quantified the relative influence of conspecific density, heterospecific composition, and climate on temporal variation in population growth rates, and (ii) asked how the relative importance of these drivers depends on site aridity, species growth form and life expectancy, and abundance and spatial patterns. The data from one of the sites in this analysis are presented in one of the chapters of this thesis. We found that density-dependence had the strongest effect on species. Climate often had a significant effect, but its strength depended on growth form. Community composition rarely explained significant variation in growth rates. The relative importance of density, composition, and climate did not vary among sites, but was related to species' life histories: compared to forbs, grasses were more sensitive to climate drivers. Abundance and spatial clustering were negatively correlated with the importance of density dependence, suggesting that local rarity is a consequence of self-limitation. Our results show that interspecific interactions play a weaker role than intraspecific interactions and climate variability in regulating plant populations. Forecasting the impacts of climate change on populations may require understanding how changes in climate variables will affect the strength of density-dependence, especially for rare species.

The dominant habitat-type of Omo National Park (ONP), Ethiopia, is grassland. 111 This grassland supports a variety of wild herbivores and indigenous people; the latter hunt large herbivores for subsistence or graze their domestic livestock in the Park. Therefore, an understanding of grassland dynamics is a high priority for ONP management. Grazing and fire are major factors influencing species composition and vegetation change in East African grasslands . Rainfall regime, in tum, can influence both grassland response to grazing and fire. The ONP grasslands occur along a rainfall gradient ranging from subhumid to semiarid. Research objectives were to: (1) test the Milchunas, Sala, and Lauenroth grazing response model at three sites along the rainfall gradient; (2) determine how basal cover for dominant perennial grasses along the rainfall gradient was influenced by an extended period of intensive defoliation; and (3) determine if current distribution of grassland species associations was related to fire frequency. Species composition changes associated with defoliation were consistent with predictions of the Milchunas, Sala, and Lauenroth model; large changes occurred in subhumid grasslands while minimal changes occurred in semiarid sites . Furthermore, an intermediate response was found at the site that received an intermediate level of rainfall. Basal cover of dominant grasses was not adversely affected by intensive defoliation, and this tolerance was expressed under all three moisture regimes. Significant reductions in basal cover were found, however, in >50% of dominant grasses as a result of protection from grazing and fire . Estimated fire frequency pattern was unrelated to the distribution of species associations within grasslands. Conceptual models of vegetation change were developed for the three grasslands using research results. At the current level of management these models provide information that can be used to improve relations between Park staff and local pastoralists . Given the tolerance of most perennial grasses to intensive defoliation, ONP managers could modify the current policy of no grazing within the Park to one of limited grazing . If management capabilities were to improve, conceptual models could guide an active approach to grassland management.

Land degradation is one of the most important drivers of landscape change around the globe. This dissertation examines land use-land cover change within a mosaic landscape in Eastern Terai, India, and shows evidence of anthropogenic factors contributing to landscape change. Land use and land cover change were examined within the Alipurduar Subdivision, a representative of the Eastern Terai landscape and the Jaldapara Wildlife Sanctuary, a protected area nested within Alipurduar through the use of multi-temporal satellite data over the past 28 years (1978 – 2006). This study establishes the potential of remote sensing technology to identify the drivers of landscape change; it provides an assessment of how regional drivers of landscape change influence the change within smaller local study extents and provides a methodology to map different types of grassland and monitor their loss within the region. The Normalized Difference Vegetation Index (NDVI) and a Normalized Difference Dry Index (NDDI) were found instrumental in change detection and the classification of different grasslands found inside the park based on their location, structure, and composition. Successful spectral segregation of different types of grasslands and their direct association with different grassland specialist species (e.g., hispid hare, hog deer, Bengal florican) clearly showed the potential of remote sensing technology to efficiently monitor these grasslands and assist in species conservation. Temporal analysis provided evidence of the loss of dense forest and grasslands within both study areas with a considerably higher rate of loss outside the protected area than inside. Results show a decline of forest from 40% in 1978 to 25% in 2006 across Alipurduar. Future trends project forest cover and grassland within Alipurduar to reduce to 15% and 5%, respectively. Within the Alipurduar, deforestation due to growth of tea industry was the primary driver of change. Flooding changed the landscape, but more intensely inside the wildlife preserve. Change of the river course inside Jaldapara during the flood of 1968 significantly altered the distribution of grassland inside the park. Unless, the direction of landscape change is altered, future trends predict growth of the tea industry within the region, increased forest loss, and homogenization of the landscape.

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy / The study aimed to differentiate the effect of rainfall and grazing on the compositional change of savanna grasslands, and to explain responses in terms of the life history patterns of the main species, An extinction prone perennial grass under heiry grazing was identified as a palatable, obligate seed reproducer with low seed production and poor dispersal (e.g. Themeda triandra and Reteropogon contortus), wnich could become extinct if the established population and the seed bank were eliminated. Aristrida species were expected to show the converse pattern. Grazing was manipulated for three or five years, and rainfall for one year, on a sandveld site, and two clay soil sites which supported the same species in different amounts, respectively. (Abbreviation abstract) / Andrew Chakane 2019

Growing concerns about climate change, foreign oil dependency, and environmental quality have fostered interest in perennial native grasses (e.g. switchgrass [Panicum virgatum]) for bioenergy production while also maintaining biodiversity and ecosystem function. However, biofuel cultivation in marginal landscapes such as airport grasslands may have detrimental effects on aviation safety as well as demography and conservation efforts for grassland birds including Dickcissels (Spiza americana). In 2011–2013 I studied the response of avian populations to vegetation composition and harvest frequency of switchgrass monocultures and native warm-season grass (NWSG) mixtures at B. Bryan farms in Clay Co. MS, USA. Four treatments incorporating switchgrass and NWSG with single and multiple annual harvesting were established on 16 experimental plots. I examined the relative abundance, aviation risk, and conservation value of birds associated with these treatments, evaluated contributions of habitat attributes and individual male quality towards territory productivity and determined effects of harvest regimens on nest success, nest density, and productivity for Dickcissels. Avian relative abundance was greater in switchgrass plots during winter months, whereas NWSG was favored by species during the breeding season. Conversely, treatment differences in aviation risk and conservation value were not biologically significant. Only 2.6% of observations included avian species of high risk to aircraft, suggesting that it may be feasible to use semi-natural grasslands at airports to provide grassland bird habitat while concurrently minimizing aviation risk. Regarding individual and habitat quality effects on nest survival and productivity, male song rate was not an effective surrogate for individual quality in demographic models. However, nest survival declined with increasing territory size and territories established earlier in the season had greater territory productivity relative to later arriving males, providing evidence that some metric of individual quality is important for grassland bird reproduction. Additionally, vegetation composition and harvest frequencies influenced nest density and productivity, but not nest survival. Native warm season grasses contained 54–64 times more nests relative to switchgrass treatments, and nest density was 10% greater in single harvest plots. My results suggest semi-natural grasslands can support grassland bird conservation while allowing for biofuel production and aviation risk management in airport landscapes.

As human populations rise exponentially, agricultural production systems must be adapted to sustain ecosystem function. Government administered agricultural conservation programs may actualize greater gains in ecosystem services, including wildlife population gains, if conservation practices designed to target specific environmental outcomes are implemented strategically in agricultural landscapes. I evaluated multi-scale, multi-species, and multi-season avian population responses to a targeted native herbaceous buffer practice (CP33: Habitat Buffers for Upland Birds) under the continuous sign-up Conservation Reserve Program administered by the U.S. Department of Agriculture. CP33 is the first conservation practice targeted directly to support habitat and population recovery objectives of a national wildlife conservation initiative (Northern Bobwhite Conservation Initiative). I coordinated breeding season, fall, and winter point transect surveys for northern bobwhite (Colinus virginianus), priority early-succession, and overwintering birds on ≈1,150 buffered and non-buffered fields in 14 states (10 ecoregions) from 2006-2009. I also assessed northern bobwhite-landscape associations within each ecoregion to determine effects of landscape structure on observed northern bobwhite abundances. Breeding season and autumn northern bobwhite densities were 60-74% and 52% greater, respectively, over all survey points in the near term (1-4 years post-establishment). However, breeding season and autumn response and associations between northern bobwhite abundance and landscape structure exhibited substantial regional variation, suggesting northern bobwhite conservation and management should be implemented on a regional basis. Breeding season densities of dickcissel (Spiza americana) and field sparrow (Spizella pusilla) were up to 190% greater on buffered fields, whereas overwintering densities of several Emberizid sparrow species were up to 2,707% greater on buffered fields. Species sensitive to patch area or those requiring vegetation structure different from that provided by buffers exhibited limited, but regionally and annually variable responses to buffered habitats. Increased bird densities of several species in several seasons suggest wildliferiendly farming practices delivered strategically and requiring minimal change in primary land use can benefit species across broad landscapes when conservation practices are targeted toward specific recovery objectives. Targeted conservation systems combining multiple conservation practices to provide an array of ecosystem services may be a mechanism for meeting multifarious conservation objectives and enhancing biodiversity in agricultural landscapes.

Few studies have measured the impacts of mowing on bird use of habitat and the risk of bird collisions with aircraft on North American airfields. The need for this research has increased as airfields become some of the only large contiguous grasslands available to rare migratory birds in some areas. I studied bird abundance, distribution and behaviors at Westover Air Reserve Base, Massachusetts, USA in June and July 2004. I compared my data with bird strike records to discern any patterns associated with mowing of airfield vegetation. There was no difference in total number of birds or species between mowed and unmowed plots adjacent to runways and taxiways. There were more Upland Sandpipers and Eastern Meadowlarks in mowed vegetation and more sparrows (Grasshopper and Savannah) in unmowed vegetation. From 1997 to 2005, swallows were the birds most often struck by aircraft in June and July at Westover, and were also the second most numerous birds in both mowed and unmowed plots. Bird species that pose high Bird/Wildlife Aircraft Strike Hazard (BASH) risk at Westover included Turkey Vulture, Red-tailed Hawk, Great Blue Heron, and Canada Goose. I did not observe those species in paired plots of mowed or unmowed airfield vegetation adjacent to runways and taxiways at Westover. I opportunistically observed 64 incidents where species that pose high BASH risk were in or adjacent to areas where aircraft operate. Birds struck most frequently at Westover between April 1997 and January 2005 were “swallows”, American Kestrel, Killdeer, Horned Lark, Eastern Meadowlark, and Mourning Dove. Current mowing practices at Westover may have adverse effects on Upland Sandpiper and Grasshopper Sparrow, both state-listed, rare, grassland birds, but may not measurably reduce overall risk to aircraft, given the continued presence of large, high BASH risk species. I recommend methods to reduce threats posed by high-risk species at Westover, and further research to seek ways to reduce adverse effects of mowing on state-listed, rare, migratory species of birds.

A long-standing question in ecology is understanding how the environment structures species occupancy in space and time. Specifically, identifying associations between environmental drivers - climate and land cover - and species occupancy is crucial to predicting species distributional dynamics in the future. Over the last century, research on the abiotic drivers of species occupancy has largely focused on temperate regions. Tropical mountain ecosystems harbor extraordinary levels of diversity and face some of the highest anthropogenic pressures of climate and land cover change. Yet, such regions have remained historically understudied. Bird species, due to their sheer diversity and occurrence across climatic zones and land cover types, are an ideal model for understanding how climate and land cover structure occupancy in space and time. The goal of this dissertation is to disentangle spatial and temporal associations between environmental drivers - climate and land cover - and bird species occupancy along a tropical montane gradient. I use an integrative approach that relies on citizen science, historical ecology, and bioacoustics to study bird communities in the Western Ghats biodiversity hotspot of southern India. In Chapter 1, we used observations from the world’s largest citizen science database, eBird, to ask how contemporary climate and land cover are associated with bird species occupancy across the Nilgiri and the Anamalai hills of the Western Ghats. We show that the occupancy of several forest specialist birds was negatively associated with temperature seasonality, highlighting narrow thermal niches for such species. We also show that a small number of generalist bird species are positively associated with human-modified land cover types. In Chapter 2, we combined colonial-era and modern datasets on bird species observations and land cover to ask how a century of landscape change across the Nilgiri hills has impacted bird communities. Between 1848 and 2017, 75% of grassland habitat across the Nilgiri hills was lost toward timber plantation and cash crop expansion. Such drastic declines in grassland habitat have resulted in declines in species persistence and relative abundance of grassland specialist birds over the last century. As a result, the functional trait space has undergone biotic homogenization. In Chapter 3, we ask if the reversal of landscape changes significantly affects bird communities. Using passive acoustic monitoring, we examined the impacts of ecological restoration on bird communities and other vocalizing fauna along a gradient of forest regeneration (consisting of actively restored, naturally regenerating, and mature benchmark sites) in the Anamalai hills. Encouragingly, we show that the bird community composition of actively restored sites is transitioning toward mature benchmark sites. However, when we moved beyond birds, we found that vocalizations at higher frequencies (> 12 kHz) were largely missing from actively restored and naturally regenerating sites, while the same frequency space was occupied in mature benchmark sites. Taken together, we find that climate and land cover are key determinants of bird species occupancy in the Western Ghats, and in a globally changing world, conservation interventions such as ecological restoration along with the preservation of naturally occurring land cover types are key to sustaining montane avifauna in the long run.

Grasslands cover 40% of the earth’s land area and provide numerous valuable ecosystem services. However, climate change, global land use change and increasing intensive anthropogenic interventions make grasslands to one of the most endangered ecosystem types in the world. Effective protection in the future requires a fundamental understanding of the dynamics of grasslands and their major drivers. Field experiments have been conducted for impact analyses, for example, with different management intensities, plant community composition and altered climatic conditions. Complementary, ecological models allow to extend the analysis to long-term effects of changes as well as to a deeper understanding of the underlying ecological processes. In this thesis, an individual-based grassland model and network science were applied to understand the community structure and dynamics emerging from individual plant interactions – in relation to plant traits, ecological processes, environmental and anthropogenic impacts, and the small-scale spatial distribution of plants. In the first study, an individual-based process-oriented grassland model was parameterized to simulate field data of a local biodiversity experiment using the concept of plant functional types. The influence of various functional plant traits and ecological processes on grassland productivity and functional composition were analyzed. Different functional plant traits showed partly contrasting effects on plant growth. With regard to the modeled ecological processes, competition for space between plants affected grassland productivity more than shading of plants. In the second study, the parameterized grassland model was used to analyze the impact of functional diversity, mowing frequency and air temperature on ecological processes that lead to changes in grassland productivity. The model reproduced the increase of biomass yields with functional diversity as observed in the field experiment. Modeled plant competition for space showed to be the dominant process and was responsible for an increase in biomass yields in more frequently mown grasslands. In the third study, an approach to generate a regionally transferable parameterization of the grassland model is presented. The impact of management, environment and climate change on productivity and functional composition of grasslands was analyzed within a German-wide scenario analysis. Management intensity had more influence on grassland productivity than environmental factors and correlations of productivity with environmental factors become stronger in less managed grasslands. Climate change showed to have only a minor influence on simulated vegetation attributes. In the fourth study, network science was applied to forest megaplots to quantify the spatial neighborhood structure of species-rich ecosystems. Networks at the individual-tree and tree-species levels revealed similar structures at three investigated forest sites. Tropical tree species coexisted in small-scale networks and only up to 51% of all possible connections between species pairs were realized. A null community analysis showed that details on the tree position and tree size have no major influence on the network structures identified. In summary, this thesis presents the development of advanced methods and analysis tools as well as their application to vegetation ecosystems with high diversity. Thereby, complex structures and dynamics of ecological systems could be systematically explored by combining ecological models with extensive field measurements.