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Sand mines represent anthropogenically impacted habitats found worldwide, which bear potential for bee conservation. Although floral resources can be limited at these habitats, vegetation free patches of open sandy soils and embankments may offer good nesting possibilities for sand restricted and other bees. We compared bee communities as found in three reclaimed sand mines and at adjacent roadside meadows in Maryland, USA, over two years. Both sand mines and roadsides hosted diverse bee communities with 111 and 88 bee species, respectively. Bee abundances as well as richness and Shannon diversity of bee species were higher in sand mines than at roadsides and negatively correlated with the percentage of vegetational ground cover. Species composition also differed significantly between habitats. Sand mines hosted a higher proportion of ground nesters, more uncommon and more ‘sand loving’ bees similar to natural sandy areas of Maryland. Despite the destruction of the original pre-mining habitat, sand mines thus appear to represent a unique habitat for wild bees, particularly when natural vegetation and open sand spots are encouraged. Considering habitat loss, the lack of natural disturbance regimes, and ongoing declines of wild bees, sand mines could add promising opportunities for bee conservation which has hitherto mainly focused on agricultural and urban habitats.
Reports of major losses in insect biodiversity have stimulated an increasing interest in temporal population changes. Existing datasets are often limited to a small number of study sites, few points in time, a narrow range of land‐use intensities and only some taxonomic groups, or they lack standardised sampling. While new monitoring programs have been initiated, they still cover rather short time periods.
Daskalova et al. 2021 (Insect Conservation and Diversity, 14, 1‐18) argue that temporal trends of insect populations derived from short time series are biased towards extreme trends, while their own analysis of an assembly of shorter‐ and longer‐term time series does not support an overall insect decline. With respect to the results of Seibold et al. 2019 (Nature, 574, 671–674) based on a 10‐year multi‐site time series, they claim that the analysis suffers from not accounting for temporal pseudoreplication.
Here, we explain why the criticism of missing statistical rigour in the analysis of Seibold et al. (2019) is not warranted. Models that include ‘year’ as random effect, as suggested by Daskalova et al. (2021), fail to detect non‐linear trends and assume that consecutive years are independent samples which is questionable for insect time‐series data.
We agree with Daskalova et al. (2021) that the assembly and analysis of larger datasets is urgently needed, but it will take time until such datasets are available. Thus, short‐term datasets are highly valuable, should be extended and analysed continually to provide a more detailed understanding of insect population changes under the influence of global change, and to trigger immediate conservation actions.
Land cover is a key variable in monitoring applications and new processing technologies made deriving this information easier. Yet, classification algorithms remain dependent on samples collected on the field and field campaigns are limited by financial, infrastructural and political boundaries. Here, animal tracking data could be an asset. Looking at the land cover dependencies of animal behaviour, we can obtain land cover samples over places that are difficult to access. Following this premise, we evaluated the potential of animal movement data to map land cover. Specifically, we used 13 White Storks (Cicona cicona) individuals of the same population to map agriculture within three test regions distributed along their migratory track. The White Stork has adapted to foraging over agricultural lands, making it an ideal source of samples to map this land use. We applied a presence-absence modelling approach over a Normalized Difference Vegetation Index (NDVI) time series and validated our classifications, with high-resolution land cover information. Our results suggest White Stork movement is useful to map agriculture, however, we identified some limitations. We achieved high accuracies (F1-scores > 0.8) for two test regions, but observed poor results over one region. This can be explained by differences in land management practices. The animals preferred agriculture in every test region, but our data showed a biased distribution of training samples between irrigated and non-irrigated land. When both options occurred, the animals disregarded non-irrigated land leading to its misclassification as non-agriculture. Additionally, we found difference between the GPS observation dates and the harvest times for non-irrigated crops. Given the White Stork takes advantage of managed land to search for prey, the inactivity of these fields was the likely culprit of their underrepresentation. Including more species attracted to agriculture - with other land-use dependencies and observation times - can contribute to better results in similar applications.
Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients.
Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales.
Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5–10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements.
The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.
Chapter 1 – General Introduction
One of the greatest challenges of ecological research is to predict the response of ecosystems to global change; that is to changes in climate and land use. A complex question in this context is how changing environmental conditions affect ecosystem processes at different levels of communities. To shed light on this issue, I investigate drivers of biodiversity on the level of species richness, functional traits and species interactions in cavity-nesting Hymenoptera. For this purpose, I take advantage of the steep elevational gradient of Mt. Kilimanjaro that shows strong environmental changes on a relatively small spatial scale and thus, provides a good environmental scenario for investigating drivers of diversity. In this thesis, I focus on 1) drivers of species richness at different trophic levels (Chapter 2); 2) seasonal patterns in nest-building activity, life-history traits and ecological rates in three different functional groups and at different elevations (Chapter 3) and 3) changes in cuticular hydrocarbons, pollen composition and microbiomes in Lasioglossum bees caused by climatic variables (Chapter 4).
Chapter 2 – Climate and food resources shape species richness and trophic interactions of cavity-nesting Hymenoptera
Drivers of species richness have been subject to research for centuries. Temperature, resource availability and top-down regulation as well as the impact of land use are considered to be important factors in determining insect diversity. Yet, the relative importance of each of these factors is unknown. Using trap nests along the elevational gradient of Mt. Kilimanjaro, we tried to disentangle drivers of species richness at different trophic levels. Temperature was the major driver of species richness across trophic levels, with increasing importance of food resources at higher trophic levels in natural antagonists. Parasitism rate was both related to temperature and trophic level, indicating that the relative importance of bottom-up and top-down forces might shift with climate change.
Chapter 3 – Seasonal variation in the ecology of tropical cavity-nesting Hymenoptera
Natural populations fluctuate with the availability of resources, presence of natural enemies and climatic variations. But tropical mountain seasonality is not yet well investigated. We investigated seasonal patterns in nest-building activity, functional traits and ecological rates in three different insect groups at lower and higher elevations separately. Insects were caught with trap nests which were checked monthly during a 17 months period that included three dry and three rainy seasons. Insects were grouped according to their functional guilds. All groups showed strong seasonality in nest-building activity which was higher and more synchronised among groups at lower elevations. Seasonality in nest building activity of caterpillar-hunting and spider-hunting wasps was linked to climate seasonality while in bees it was strongly linked to the availability of flowers, as well as for the survival rate and sex ratio of bees. Finding adaptations to environmental seasonality might imply that further changes in climatic seasonality by climate change could have an influence on life-history traits of tropical mountain species.
Chapter 4 – Cryptic species and hidden ecological interactions of halictine bees along an elevational Gradient
Strong environmental gradients such as those occurring along mountain slopes are challenging for species. In this context, hidden adaptations or interactions have rarely been considered. We used bees of the genus Lasioglossum as model organisms because Lasioglossum is the only bee genus occurring with a distribution across the entire elevational gradient at Mt. Kilimanjaro. We asked if and how (a) cuticular hydrocarbons (CHC), which act as a desiccation barrier, change in composition and chain length along with changes in temperature and humidity (b), Lasioglossum bees change their pollen diet with changing resource availability, (c) gut microbiota change with pollen diet and climatic conditions, and surface microbiota change with CHC and climatic conditions, respectively, and if changes are rather influenced by turnover in Lasioglossum species along the elevational gradient. We found physiological adaptations with climate in CHC as well as changes in communities with regard to pollen diet and microbiota, which also correlated with each other. These results suggest that complex interactions and feedbacks among abiotic and biotic conditions determine the species composition in a community.
Chapter 5 – General Discussion
Abiotic and biotic factors drove species diversity, traits and interactions and they worked differently depending on the functional group that has been studied, and whether spatial or temporal units were considered. It is therefore likely, that in the light of global change, different species, traits and interactions will be affected differently. Furthermore, increasing land use intensity could have additional or interacting effects with climate change on biodiversity, even though the potential land-use effects at Mt. Kilimanjaro are still low and not impairing cavity-nesting Hymenoptera so far. Further studies should address species networks which might reveal more sensitive changes. For that purpose, trap nests provide a good model system to investigate effects of global change on multiple trophic levels and may also reveal direct effects of climate change on entire life-history traits when established under different microclimatic conditions. The non-uniform effects of abiotic and biotic conditions on multiple aspects of biodiversity revealed with this study also highlight that evaluating different aspects of biodiversity can give a more comprehensive picture than single observations.
Plant-associated fungi can affect the plants‘ interaction with herbivores and
other microorganisms. For example, many common forage grasses are infected
with Epichloë endophytes. The endophytes systemically colonize the aerial
parts of the plants. They produce bioprotective alkaloids that can negatively
affect insects and livestock feeding on the grasses, and interact with other
fungal species which living from the plants‘ nutrients. Environmental conditions
strongly influence Epichloë endophytes. Endophyte-mediated effects
on herbivores are more pronounced under increased temperatures and the
endophytes may benefit from land use in managed grasslands. Under the
framework of the large-scale German project “Biodiversity Exploratories”, I
investigated whether infection rates and alkaloid concentrations of Epichloë
festucae var. lolii in Lolium perenne (Chapter I) and Epichloë endophytes (E.
uncinata, E. siegelii) in Festuca pratensis (Chapter II) depend on land use and
season. Further I analysed, whether foliar fungal assemblages of L. perenne
are affected by the presence of Epichloë endophytes (Chapter IV).
Epichloë endophytes associated with cool-season grass species can protect their hosts from herbivory and can suppress mycorrhizal colonization of the hosts’ roots. However, little is known about whether or not Epichloë endophyte infection can also change the foliar fungal assemblages of the host. We tested 52 grassland study sites along a land-use intensity gradient in three study regions over two seasons (spring vs. summer) to determine whether Epichloë infection of the host grass Lolium perenne changes the fungal community structure in leaves. Foliar fungal communities were assessed by Next Generation Sequencing of the ITS rRNA gene region. Fungal community structure was strongly affected by study region and season in our study, while land-use intensity and infection with Epichloë endophytes had no significant effects. We conclude that effects on non-systemic endophytes resulting from land use practices and Epichloë infection reported in other studies were masked by local and seasonal variability in this study’s grassland sites.
Forecasting spatio-temporal dynamics on the land surface using Earth Observation data — a review
(2020)
Reliable forecasts on the impacts of global change on the land surface are vital to inform the actions of policy and decision makers to mitigate consequences and secure livelihoods. Geospatial Earth Observation (EO) data from remote sensing satellites has been collected continuously for 40 years and has the potential to facilitate the spatio-temporal forecasting of land surface dynamics. In this review we compiled 143 papers on EO-based forecasting of all aspects of the land surface published in 16 high-ranking remote sensing journals within the past decade. We analyzed the literature regarding research focus, the spatial scope of the study, the forecasting method applied, as well as the temporal and technical properties of the input data. We categorized the identified forecasting methods according to their temporal forecasting mechanism and the type of input data. Time-lagged regressions which are predominantly used for crop yield forecasting and approaches based on Markov Chains for future land use and land cover simulation are the most established methods. The use of external climate projections allows the forecasting of numerical land surface parameters up to one hundred years into the future, while auto-regressive time series modeling can account for intra-annual variances. Machine learning methods have been increasingly used in all categories and multivariate modeling that integrates multiple data sources appears to be more popular than univariate auto-regressive modeling despite the availability of continuously expanding time series data. Regardless of the method, reliable EO-based forecasting requires high-level remote sensing data products and the resulting computational demand appears to be the main reason that most forecasts are conducted only on a local scale. In the upcoming years, however, we expect this to change with further advances in the field of machine learning, the publication of new global datasets, and the further establishment of cloud computing for data processing.
This study investigates the surroundings of Munigua (municipium Flavium Muniguense), a small Roman town in the ancient province of Hispania Baetica (SW Spain). The city's economy was based primarily on copper and iron mining, which brought financial prosperity to its citizens. Local production of agricultural goods is thought to have been of little importance, as the regional soil conditions do not seem to be suitable for extensive agriculture.
To evaluate the recent soil agro-potential and to find evidence for prehistoric and historic land use in the surroundings of Munigua, we applied a pedo-geomorphological approach based on the physico-chemical analysis of 14 representative soil and sediment exposures. Selected samples were analyzed for bulk chemistry, texture and phytoliths. The chronostratigraphy of the sequences was based on radiocarbon dating of charcoal samples. The site evaluation of the present-day soil agro-potential was carried out according to standard procedures and included evaluation of potential rootability, available water-storage capacity and nutrient budget within the uppermost 1 m.
The results show that moderate to very good soil agro-potential prevails in the granitic and floodplain areas surrounding Munigua. Clearly, recent soil agro-potential in these areas allows the production of basic agricultural goods, and similar limited agricultural use should also have been possible in ancient times. In contrast, weak to very weak present-day soil agro-potential prevails in the metamorphic landscape due to the occurrence of shallow and sandy to stony soils.
In addition, the study provides pedo-geomorphological evidence for prehistoric and historic land use in pre-Roman, Roman and post-Roman times. Catenary soil mapping in the vicinity of a Roman house complex reveals multi-layered colluvial deposits. They document phases of hillslope erosion mainly triggered by human land use between 4063 ± 82 and 3796 ± 76 cal BP, around 2601 ± 115 cal BP, and between 1424 ± 96 and 421 ± 88 cal BP. Moreover, geochemical and phytolith analyses of a Roman hortic Anthrosol indicate the local cultivation of agricultural products that contributed to the food supply of Munigua.
Overall, the evidence of Roman agricultural use in the Munigua area indicates that the city's economy was by no means focused solely on mining. The production of basic agricultural products was also part of Munigua's economic portfolio. Our geoarcheological study thus supports the archeological concept of economically diversified Roman cities in the province of Baetica and in Hispania.
This article presents an open space concept of areas that are kept permanently free from buildings, technical infrastructure, and soil sealing. In the European Alps, space is scarce because of the topography; conflicts often arise between competing land uses such as permanent settlements and commercial activity. However, the presence of open spaces is important for carbon sequestration and the prevention of natural hazards, especially given climate change. A GIS-based analysis was conducted to identify an alpine-wide inventory of large-scale near-natural areas, or simply stated, open spaces. The method used identified the degree of infrastructure development for natural landscape units. Within the Alpine Convention perimeter, near-natural areas (with a degree of infrastructural development of up to 20%) account for a share of 51.5%. Only 14.5% of those areas are highly protected and are mostly located in high altitudes of over 1500 m or 2000 m above sea level. We advocate that the remaining Alpine open spaces must be preserved through the delimitation of more effective protection mechanisms, and green corridors should be safeguarded through spatial planning. To enhance the ecological connectivity of open spaces, there is the need for tailored spatial and sectoral planning strategies to prevent further landscape fragmentation and to coordinate new forms of land use for renewable energy production.