Km2 Square Research Articles

Trends in abundance and occupancy of the protected water beetle Graphoderus bilineatus in the Netherlands

The European Habitats Directive prescribes Member States to report on trends in abundance and distribution of protected species. One of these species is Graphoderus bilineatus (De Geer, 1774), a middle-sized predaceous aquatic beetle, listed in Annex II and IV of the Habitats Directive. In the Netherlands, a monitoring scheme for this species has been set up to assess the national trend as well as the trend in the national Natura2000 sites. In this scheme, a selection of 1 km2 squares is surveyed in cycles of six years using a standardized field method by professional fieldworkers. In each selected square, five locations were sampled per annum (September–October) by two different observers using hand netting. The data of the first two rounds (2011–2016 and 2017–2022) have been analysed using both an occupancy model and a Poisson GLMM. We found evidence of a declining trend in occupancy as well as in population size. The decreases were stronger outside than within Natura2000 sites and also stronger than those of three other beetle species that are often found together with G. bilineatus. In addition, considerable differences between observers were detected in the data, despite the application of a standardized field method.Implications for insect conservationGraphoderus bilineatus is declining and the decline is stronger outside Natura2000 sites then within, most likely due to differences in the development of water quality, vegetation structure and water management. Further research is required to identify the exact causes of the decline; however water quality improvement seems essential to turn the tide. The study also shows the benefits of a monitoring scheme for trend assessments. The recent decline would probably not have been noticed based on distribution data alone.

Habitat and other environmental correlates of the decline of breeding Whinchats Saxicola rubetra in the UK since the mid-1990s

ABSTRACT Capsule Declines in Whinchat Saxicola rubetra breeding abundance in the UK vary with habitat and other environmental conditions. Aims To test for associations between changes in Whinchat abundance between 1994 and 2018 and measures of habitat and environmental conditions on UK breeding sites. Methods Whinchat counts collected through a national monitoring scheme were tested at coarse 1 km2 square and finer 200 m transect scales against habitat data collected in 2017/2018, plus remotely sensed data to test for long-term change. Results At the 1 km2 square scale, mean change in Whinchat abundance was more negative where woodland occurred more frequently, and at more northerly latitudes. Rates of decline were lower where there was greater cover of Purple Moor-grass Molinia caerulea and non-bracken vegetation height was taller. At the finer 200 m transect scale, more closely resembling Whinchat territory size, rates of decline were greatest in areas dominated by human sites, woodland, and enclosed farmland, compared to unenclosed open semi-natural habitats; however, within the latter category, declines were lower in grass-dominated relative to heather-dominated habitats. Rates of decline were also lower closer to valley bottoms, with greater Bracken Pteridium aquilinum cover and at mid-elevations (300 m), and greatest where there was greater cover of bare ground and trees, and moderate cover of grasses (excluding Molinia and Lolium spp.). The strength of the finer-scale associations varied between dominant habitat types. Whinchat abundance was lower where a remotely sensed index of vegetation productivity (normalized difference vegetation index [NDVI]) was higher, and abundance change more negative where temporal increases in NDVI were greater. Conclusion Unenclosed semi-natural grassland showed the lowest rate of decline and offers the best opportunities to conserve Whinchats. Woodland expansion is likely to have a detrimental impact on breeding Whinchats. Future research should investigate how important habitat and environmental correlates influence key demographic rates affecting recruitment.

A graph approach for fast dense array inter-station phase delay interpretation

SUMMARY We present a phase-delay detection procedure adapted for seismic arrays composed of a large number of stations. We use graph formalism to introduce a direct method to compute station phase delays starting from inter-station phase differences deduced from noise cross-correlation functions. We focus this study on surface wave main arrival as phase-difference evaluation at each station requires high coherence level. Then, we perform numerical experiments with synthetic data computed as a realistic and dense network of 79 stations in a 400 by $400\, \mathrm{km^2}$ square box. For one of the 79 stations, we simulate a phase difference of 15 per cent of the signal period. Further, we evaluate the accuracy and precision of phase-delay estimation at each station with regard to the quality of the cross-correlation functions (i.e. the signal-to-noise ratio). When the inter-station coherence levels are larger than 0.6 (i.e. a high-quality signal), we show good agreement between the phase-delay estimation and its expected value of 15 per cent of the signal period. We introduce a coherence-weighted estimate of phase delay and show that applying this weighting allows us to be less vulnerable to phase-delay underestimation for intermediate-quality signals. Then, the method is applied to experimental data recorded by a high density nodal array with 923 vertical geophones with 19 d of continuous records, centred on the 600 by $600\, \mathrm{m^2}$ damage zone of the Clark branch of the San Jacinto Fault Zone, Southern California (USA). We verify that the San Jacinto network is well synchronized, as most of the estimated phase delays are less than 2 per cent of the central period of the signal, and they are associated with high levels of inter-station coherence. More surprisingly, the spatial features of the estimated phase delays show deterministic geographical patterns that are related to topography and that exhibit similarities with phase velocity maps at $4.5\, \mathrm{Hz}$ from previous 3-D velocity inversions. This suggests that the topographic effect may be accounted for to estimate accurate phase delays. Also, we note that the temporal variability of the estimated phase delays in the case of the San Jacinto data set are related to atmospheric forcing. Our direct method for estimating phase delays is applicable to structure-oriented monitoring studies, and it opens perspectives in the monitoring of seismic velocity variations.

Evaluating natural and anthropogenic inputs on the distribution of potentially toxic elements in urban soil of Valdivia, Chile.

The increasing population in urban areas in the last decades requires an effort to understand the geochemistry of contaminant elements in urban soil. Topsoil plays a crucial role in the exposure of Potentially Toxic Elements (PTEs) to humans through ingestion, dermal contact, and inhalation. In Chile, the last census revealed that 88.6% of people live in cities or towns and only 11.4% in rural areas. This study presents the first systematic geochemical survey of urban soil in the city of Valdivia, in the South of Chile. Topsoil samples (0-10cm depth) were collected in less disturbed locations within the city at 130 sampling sites using a grid of 0.25km2 squares covering a total area of approximately 30km2. The concentrations of Al, Fe, Na, Ca, Mg, K, Ti, Be, V, Cr, Mn, Co, Ni, Cu, Zn, As, Mo, Sn, Cd, Se, Pb and Hg were measured. The results showed that high concentrations of Cu, V, Zn and Pb are located mainly in the city's northern area and exceed international soil quality legislation for agricultural use. Data processing comprised plotting of individual spatial distribution maps and the use of a combination of multivariate statistical methods. Hierarchical cluster analysis and principal component analysis identified three element associations. The two element groups V-Al-Ti-Fe-Cr-Co-Mn-Be-Ni and Ca-Na-K-As-Mg are interpreted as a dominant lithological origin related to the most pristine soil conditions in less populated areas. By contrast, the Sn-Pb-Zn-Mo-(Cu-Hg) association presents a significant correlation with urbanization indicators, including vehicular traffic and industrial activities developed since the end of the nineteenth century in Valdivia.

Roadmaps for heating and cooling system transitions seen through uncertainty and sensitivity analysis

Future district heating systems should enable efficient and economic energy supply, which can be achieved by lowering the system temperatures and boosting it at demand-side. Current solutions include the ultra-low-temperature district heating (ULTDH) and fifth generation district heating and cooling (5GDHC) systems. The transition towards these systems is subject to multiple future uncertainties such as the energy price, investment cost, and demand changes, which were missing in previous works. To investigate the effects of these uncertainties on conclusions brought by established design roadmaps for future DHCs, a five-step framework, which combines the energy system optimization with stochastic simulations, uncertainty analysis and sensitivity assessment, is developed in this study. The framework is applied on a hypothetical 0.25 km2 square district with varying uncertain parameters. Based on stochastic cases, the index named cost-saving probability (CSP) is utilized to reflect the potential of being economic attractive when comparing the energy systems. For the transition towards the ULTDHC, 5GDHC, and individual systems, the most sensitive factors for the CSP are the area demand density, overlapping heating and cooling demand, and linear demand density, respectively. The investment in thermal energy storage (TES) becomes important only when the integration of a larger share of renewable energy is targeted. A roadmap summarizing the promoting and hindering factors for the system transition is provided, pointing out the future focus area for DHC design. The results from the sensitivity analysis also revealed the limited role of TES in integrating variable renewable energy in high-efficiency DHC systems.

Evaluation of comparative scenarios from different sites of chestnut production using life cycle assessment (LCA): Case study in the Beira Interior region of Portugal

The evaluation of the environmental impacts of chestnut production in the Beira Interior region (Portugal) is accessed. The comparative life cycle assessment (LCA) was performed with the use of openLCA software with 16 Environmental Footprint (EF) impact categories retrieved from the AGRIBALYSE database. The system boundary was from “cradle-to-farm gate” and the functional unit was 1 ton of chestnut delivered to consumers (only wholesale buyers). The processes model for the production of agricultural machinery, pesticides, fertilizers, and materials was modeled based on surveys and existing literature. The data was gathered from four different production areas: Serra da Estrela, Malcata, Gardunha, and Plateau area. Each site has two selected representative producers inner 250 km2 square radius environment. The results showed that the average GHG emissions in the low-input group (Estrela and Gardunha) were 1.83 kg CO2-eq/ton with the energy burden (80–89%) as main contribution emissions and in the intensive-input group (Malcata and Plateau) were 2.61 kg CO2-eq/ton with the main contribution source of emissions are fertilizer (76–83%). Sensitivity analysis results indicate shift input material and cultivation activities in chestnut production systems can be possible for all study areas without reducing yield production. The suggestions in this article can be used by farmers, policymakers, and other stakeholders to adopt new alternative production scenarios.

Book Review

Book Review

Association between the distribution of Capercaillies Tetrao urogallus and road and track densities at a landscape scale in a national park

ABSTRACT Capsule: The inherited pattern of roads and tracks, now primarily used by people for recreation in the Cairngorms National Park, was associated with a reduced presence of Capercaillie Tetrao urogallus signs in woodland. Aims: To examine if the distribution of Capercaillies in the Cairngorms National Park was associated with the density of roads and tracks that run through woods in the Park, having accounted for habitat variables that are known to affect the distribution of Capercaillies. Methods: In 2013, Capercaillie distribution, as assessed from signs of presence, and habitat variables in seven woods totalling 142 km2 within the Cairngorms National Park were assessed along regularly spaced transects. Numbers of people walking, on bicycles, and in vehicles were counted on selected tracks, and the density of roads and tracks (a measure of human use) in 0.25 km2 squares of woodland was obtained from maps. A logistic regression compared habitat variables and road and track densities in 0.25 km2 squares of woodland where signs of Capercaillie were or were not found. Results: Greater road and track densities were associated with reduced likelihood of finding Capercaillie signs in woodland squares, but the track effect was associated only with the two woods that had the highest levels of use by people. Conclusion: In response to the landscape-scale, correlative evidence of disturbance to Capercaillies, a reduction in track density (a current mean of 2.3 km per km2 of woodland) or modifying human usage of tracks are conservation management options. This presents a challenge for forest managers, public bodies, the tourism industry, and others who wish to promote visitor access to the countryside and also to protect rare and vulnerable wildlife.

Polynuclearity as a Spatial Measure of Urban Sprawl: Testing the Percentiles Approach

Polynuclearity and polycentricity are spatial phenomena which overlap each other in the context of urban sprawl, and this sometimes hinders the possibility of clearly distinguishing the two. Hence, the basic goal of the article is to indicate the differences between polycentricity and polynuclearity as well as their conceptualization and operationalization as urban sprawl features. The article indicates that the main differences between polycentricity and polynuclearity boil down to functional connections. However, empirical exemplification was made in relation to the agglomeration of Cracow, Poland using an urban morphology approach based on 1 km2 square grids. Among the conclusions, it can be found that the identification of the central core is an important stage of research. If at least two cores appear then polynuclearity is identified and then polycentricity can be further identified. Testing of four mathematical approaches to identifying the central core showed that the most accurate results are given by the 95th percentile, i.e., the grids within the 95th percentile of building density qualify for the central core. It is also necessary to remove grids with extremely high building density from the analyses.

The breeding distribution and numbers of the Jackdaw (Corvus monedula) in Kharkiv City, Ukraine

The counts of breeding Jackdaws were made in Kharkiv City, Ukraine in April – early June of 2016–2017. We estimated the breeding density among different habitat types. For such a purpose the city area was divided into 0.25 km² squares (n = 1354) and we estimated the numbers of pairs within the boundaries of 40 squares (QGIS program was used to choose randomly these squares). The surveys were made in April–May (19 squares) and early June (4 squares) in 2016 and April–May (10 squares) and early June (7 squares) in 2017. The surveys were made within main habitat types such as area of residential blocks of flats, residential area (1–2-storey buildings), industrial area, forest zone, park zone and undeveloped urban areas. The data on the area occupied by every major habitat type (in km²) were calculated by QGIS program. The 90 % of the territory of Kharkiv City was analysed, except water reservoirs and traffic way areas. The data of the surveys were extrapolated across areas of the same habitat types. Also we have searched for Jackdaw colonies within the boundaries of Kharkiv City to take these data into account. According to the collected data the Jackdaw prefers to nest in crevices of old 3–5-level buildings at built-up districts or in round cross-sections of posts at blocks-of-flats areas. Thus the mean density here was 22 pairs/km². The mean density of Jackdaw in industrial areas was 15 pairs/km², in undeveloped urban areas – 1.2 pairs/km², and in residential area (1–2-storey buildings) – 0.7 pairs/km². The total number of breeding Jackdaws in Kharkiv City was estimated at 2325 to 2630 pairs. The mean density of Jackdaws was 7.5 pairs/km². Taking into account the moderate decline in the population of the Jackdaws in some European countries (although in general the population trend remains stable within the continent), and the lack of the surveys of the breeding distribution and numbers of Jackdaws in large cities of the Eastern Ukraine, it’s reasonable to use our data as an optimal starting point for the monitoring of the regional population trend of the species. The data of 2016 year survey were used in European Breeding Bird Atlas 2 (EBBA2) programme (square 37UCR2).

Global fern and lycophyte richness explained: How regional and local factors shape plot richness

AbstractAimTo disentangle the influence of environmental factors at different spatial grains (regional and local) on fern and lycophyte species richness and to ask how regional and plot‐level richness are related to each other.LocationGlobal.TaxonFerns and lycophytes.MethodsWe explored fern and lycophyte species richness at two spatial grains, regional (hexagonal grid cells of 7,666 km2) and plot level (300–500 m2), in relation to environmental data at regional and local grains (the 7,666 km2hexagonal grid cells and 4 km2square grid cells, respectively). For the regional grain, we obtained species richness data for 1,243 spatial units and used them together with climatic and topographical predictors to model global fern richness. For the plot‐level grain, we collated a global dataset of nearly 83,000 vegetation plots with a surface area in the range 300–500 m2in which all fern and lycophyte species had been counted. We used structural equation modelling to identify which regional and local factors have the biggest effect on plot‐level fern and lycophyte species richness worldwide. We investigate how plot‐level richness is related to modelled regional richness at the plot's location.ResultsPlot‐level fern and lycophyte species richness were best explained by models allowing a link between regional environment and plot‐level richness. A link between regional richness and plot‐level richness was essential, as models without it were rejected, while models without the regional environment‐plot‐level richness link were still valid but had a worse goodness‐of‐fit value. Plot‐level richness showed a hump‐shaped relationship with regional richness.Main conclusionsRegional environment and regional fern and lycophyte species richness each are important determinants of plot‐level richness, and the inclusion of one does not substitute the inclusion of the other. Plot‐level richness increases with regional richness until a saturation point is reached, after which plot‐level richness decreases despite increasing regional richness, possibly reflecting species interactions.

Implementation of an urban efficiency index to comprehend post-metropolitan territories—The case of Greater Milan in Italy

The objective of this research is to develop a large-scale interdisciplinary urban analysis of a post-metropolitan area in Northern Italy and provide outcomes that can be useful for policymakers, public utilities, urban designers, and other stakeholders in defining strategies to improve the territory. This research, implemented within a wide national academic study on several urban regions in Italy, focuses on a 100 × 100 km2 square territory around the centre of Milan that encompasses 904 municipalities. The main local input and output flows are analysed for each municipality by considering available databases. Urban performance is investigated in the research framework of urban metabolism, by applying a fuzzy logic model. The overall structure of the model, definition of subsystems, set of indicators, adopted benchmarks, and levels of importance of variables are calibrated to suit the particular context of applications.The model provides the UEI (urban efficiency index) outcome and a geographical information system (GIS) representation to facilitate the comparison between municipalities and territories and determine the low or high-performance areas that necessitate further investigations.This work represents an important attempt in developing and applying methods for supporting decisions and defining policies towards more sustainable urban areas.

Bioclimatic modeling in the Last Glacial Maximum, Mid-Holocene and facing future climatic changes in the strawberry tree (Arbutus unedo L.).

Increasing forest wildfires in Portugal remain a growing concern since forests in the Mediterranean region are vulnerable to recent global warming and reduction of precipitation. Therefore, a long-term negative effect is expected on the vegetation, with increasing drought and areas burnt by fires. The strawberry tree (Arbutus unedo L.) is particularly used in Portugal to produce a spirit by processing its fruits and is the main income for forestry owners. Other applications are possible due to the fruit and leaves’ anti-oxidant properties and bioactive compounds production, with a potential for clinical and food uses. It is a sclerophyllous plant, dry-adapted and fire resistant, enduring the Mediterranean climate, and recently considered as a possibility for afforestation, to intensify forest discontinuity where pines and eucalypts monoculture dominate the region. To improve our knowledge about the species’ spatial distribution we used 318 plots (the centroid of a 1 km2 square grid) measuring the species presence and nine environmental attributes. The seven bioclimatic variables most impacting on the species distribution and two topographic features, slope and altitude, were used. The past, current and future climate data were obtained through WorldClim. Finally, the vulnerability of the strawberry tree to the effects of global climate change was examined in the face of two emission scenarios (RCP 4.5 and 8.5), to predict distribution changes in the years 2050 and 2070, using a species distribution models (MaxEnt). The reduction of suitable habitat for this species is significant in the southern regions, considering the future scenarios of global warming. Central and northern mountainous regions are putative predicted refuges for this species. Forest policy and management should reflect the impact of climate change on the usable areas for forestry, particularly considering species adapted to the Mediterranean regions and wildfires, such as the strawberry tree. The distribution of the species in the Last Glacial Maximum (LGM) and Mid-Holocene (MH) agrees with previous genetic and paleontological studies in the region, which support putative refuges for the species. Two in the southern and coastal-central regions, since the LGM, and one in the east-central mountainous region, considered as cryptic refugia.

Land cover and vegetation data from an ecological survey of "key habitat" landscapes in England, 1992–1993

Abstract. Since 1978, a series of national surveys (Countryside Survey, CS) have been carried out by the Centre for Ecology and Hydrology (CEH) (formerly the Institute of Terrestrial Ecology, ITE) to gather data on the natural environment in Great Britain (GB). As the sampling framework for these surveys is not optimised to yield data on rarer or more localised habitats, a survey was commissioned by the then Department of the Environment (DOE, now the Department for Environment, Food and Rural Affairs, DEFRA) in the 1990s to carry out additional survey work in English landscapes which contained semi-natural habitats that were perceived to be under threat, or which represented areas of concern to the ministry. The landscapes were lowland heath, chalk and limestone (calcareous) grasslands, coasts and uplands. The information recorded allowed an assessment of the extent and quality of a range of habitats defined during the project, which can now be translated into standard UK broad and priority habitat classes. The survey, known as the "Key Habitat Survey", followed a design which was a series of gridded, stratified, randomly selected 1 km squares taken as representative of each of the four landscape types in England, determined from statistical land classification and geological data ("spatial masks"). The definitions of the landscapes are given in the descriptions of the spatial masks, along with definitions of the surveyed habitats. A total of 213 of the 1 km2 square sample sites were surveyed in the summers of 1992 and 1993, with information being collected on vegetation species, land cover, landscape features and land use, applying standardised repeatable methods. The database contributes additional information and value to the long-term monitoring data gathered by the Countryside Survey and provides a valuable baseline against which future ecological changes may be compared, offering the potential for a repeat survey. The data were analysed and described in a series of contract reports and are summarised in the present paper, showing for example that valuable habitats were restricted in all landscapes, with the majority located within protected areas of countryside according to different UK designations. The dataset provides major potential for analyses, beyond those already published, for example in relation to climate change, agri-environment policies and land management. Precise locations of the plots are restricted, largely for reasons of landowner confidentiality. However, the representative nature of the dataset makes it highly valuable for evaluating the status of ecological elements within the associated landscapes surveyed. Both land cover data and vegetation plot data were collected during the surveys in 1992 and 1993 and are available via the following DOI: https://doi.org/10.5285/7aefe6aa-0760-4b6d-9473-fad8b960abd4. The spatial masks are also available from https://doi.org/10.5285/dc583be3-3649-4df6-b67e-b0f40b4ec895.

Evaluation and Aggregation Properties of Thermal Infra-Red-Based Evapotranspiration Algorithms from 100 m to the km Scale over a Semi-Arid Irrigated Agricultural Area

Evapotranspiration (ET) estimates are particularly needed for monitoring the available water of arid lands. Remote sensing data offer the ideal spatial and temporal coverage needed by irrigation water management institutions to deal with increasing pressure on available water. Low spatial resolution (LR) products present strong advantages. They cover larger zones and are acquired more frequently than high spatial resolution (HR) products. Current sensors such as Moderate-Resolution Imaging Spectroradiometer (MODIS) offer a long record history. However, validation of ET products at LR remains a difficult task. In this context, the objective of this study is to evaluate scaling properties of ET fluxes obtained at high and low resolution by two commonly used Energy Balance models, the Surface Energy Balance System (SEBS) and the Two-Source Energy Balance model (TSEB). Both are forced by local meteorological observations and remote sensing data in Visible, Near Infra-Red and Thermal Infra-Red spectral domains. Remotely sensed data stem from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and MODIS sensors, respectively, resampled at 100 m and 1000 m resolutions. The study zone is a square area of 4 by 4 km2 located in a semi-arid irrigated agricultural zone in the northwest of Mexico. Wheat is the dominant crop, followed by maize and vegetables. The HR ASTER dataset includes seven dates between the 30 December 2007 and 13 May 2008 and the LR MODIS products were retrieved for the same overpasses. ET retrievals from HR ASTER products provided reference ET maps at LR once linearly aggregated at the km scale. The quality of this retrieval was assessed using eddy covariance data at seven locations within the 4 by 4 km2 square. To investigate the impact of input aggregation, we first compared to the reference dataset all fluxes obtained by running TSEB and SEBS models using ASTER reflectances and radiances previously aggregated at the km scale. Second, we compared to the same reference dataset all fluxes obtained with SEBS and TSEB models using MODIS data. LR fluxes obtained by both models driven by aggregated ASTER input data compared well with the reference simulations and illustrated the relatively good accuracy achieved using aggregated inputs (relative bias of about 3.5% for SEBS and decreased to less than 1% for TSEB). Results also showed that MODIS ET estimates compared well with the reference simulation (relative bias was down to about 2% for SEBS and 3% for TSEB). Discrepancies were mainly related to fraction cover mapping for TSEB and to surface roughness length mapping for SEBS. This was consistent with the sensitivity analysis of those parameters previously published. To improve accuracy from LR estimates obtained using the 1 km surface temperature product provided by MODIS, we tested three statistical and one deterministic aggregation rules for the most sensible input parameter, the surface roughness length. The harmonic and geometric averages appeared to be the most accurate.

Space–Time Characterization of Rainfall Field in Tuscany

Precipitation during the period 2001–2016 over the northern and central part of Tuscany was studied in order to characterize the rainfall regime. The dataset consisted of hourly cumulative rainfall series recorded by a network of 801 rain gauges. The territory was divided into 30 × 30 km2 square areas where the annual and seasonal Average Cumulative Rainfall (ACR) and its uncertainty were estimated using the Non-Parametric Ordinary Block Kriging (NPOBK) technique. The choice of area size was a compromise that allows a satisfactory spatial resolution and an acceptable uncertainty of ACR estimates. The daily ACR was estimated using a less computationally expensive technique, averaging the cumulative rainfall measurements in the area. The trend analysis of annual and seasonal ACR time series was performed by means of the Mann–Kendall test. Four climatic zones were identified: the north-western was the rainiest, followed by the north-eastern, northcentral and south-central. An overall increase in precipitation was identified, more intense in the north-west, and determined mostly by the increase in winter precipitation. On the entire territory, the number of rainy days, mean precipitation intensity and sum of daily ACR in four intensity groups were evaluated at annual and seasonal scale. The main result was a magnitude of the ACR trend evaluated as 35 mm/year, due mainly to an increase in light and extreme precipitations. This result is in contrast with the decreasing rainfall detected in the past decades.

Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure

AbstractAimTo investigate the performance and relative importance of abiotic and biotic predictors of species richness of three taxa in forest‐dominated landscapes across an environmentally heterogeneous mountain region.LocationSwitzerland (central Europe).MethodsWe used a broad set of nationally available environmental predictors grouped into (1) climate, (2) topography and soil and (3) 3‐D vegetation structure derived from airborne Light Detection and Ranging (LiDAR) data to spatially predict the forest species richness of vascular plants, butterflies and breeding birds. We used presence data of 212 plant, 157 butterfly and 92 bird species from multiple transect samples in > 220 1 km2 squares at elevations between 261 and 2123 m a.s.l. across 41,248 km2. We applied an ensemble modelling approach consisting of five modelling techniques and evaluated their predictive performance using the cross‐validated percentage of explained variance of each predictor group separately and the combinations thereof. We investigated the relative importance and response of each predictor and partitioned the variation into independent and shared components per variable group.ResultsClimate performed best in predicting forest species richness across taxa. Vegetation structure particularly improved the predictions of butterfly and bird species richness, while soil pH was an important predictor for forest plant species richness. Climate appeared to be mainly indirectly related to butterfly species richness, via correlations with habitat type and structure. The strength and direction of the relationships between the predictors and species richness were taxon‐specific with low cross‐taxon congruence.Main conclusionsThe growing availability of LiDAR data offers powerful new tools for describing vegetation structure and associated animal habitat quality across large areas. This will further our understanding of niche‐driven assembly processes in forest landscapes. Although climate was the dominant factor controlling species richness across taxa from different trophic levels, the taxon‐specific distributional pattern and response to environmental conditions emphasize the difficulty of accounting for a range of taxa in prioritising biodiversity conservation measures.

Soil fauna through the landscape window: factors shaping surface-and soil-dwelling communities across spatial scales in cork-oak mosaics

The role of ecological processes governing community structure are dependent on the spatial distances among local communities and the degree of habitat heterogeneity at a given spatial scale. Also, they depend on the dispersal ability of the targeted organisms collected throughout a landscape window. We assessed the relative importance of spatial and environmental factors shaping edaphic (Collembola) and epigeous (Carabidae) communities at different scales. The sampling sites were four different landscape windows (1 km2 square each) in a Mediterranean cork-oak landscape in Portugal. Variance partitioning methods were used to disentangle the relative effects of spatial variables and environmental variables (habitat: data on % of vegetation cover types; management: data on forestry and pasture interventions; landscape: data on landscape metrics e.g., patch size, shape and configuration) across different spatial scales. The relative effects of environmental and spatial factors at different scales varied between Collembola and Carabidae. The pure effect of the environmental component was only significant for carabid beetles and explained a higher percentage of their community variance compared to collembolan communities. The pure effects of the spatial component were generally higher than the environmental component for both groups of soil fauna. Carabid communities responded to landscape features related to the patch connectivity of open areas (grasslands) as well as the shape of cork-oak habitat patches integrating the agro-forest mosaic. Community patterns of surface-dwelling soil fauna may be partly predicted by some features of the landscape, while soil-dwelling communities require ecological assessments at finer spatial scales.

Environmental gradients explain species richness and community composition of coastal breeding birds in the Baltic Sea.

Scientifically-based systematic conservation planning for reserve design requires knowledge of species richness patterns and how these are related to environmental gradients. In this study, we explore a large inventory of coastal breeding birds, in total 48 species, sampled in 4646 1 km2 squares which covered a large archipelago in the Baltic Sea on the east coast of Sweden. We analysed how species richness (α diversity) and community composition (β diversity) of two groups of coastal breeding birds (specialists, i.e. obligate coastal breeders; generalists, i.e. facultative coastal breeders) were affected by distance to open sea, land area, shoreline length and archipelago width. The total number of species per square increased with increasing shoreline length, but increasing land area counteracted this effect in specialists. The number of specialist bird species per square increased with decreasing distance to open sea, while the opposite was true for the generalists. Differences in community composition between squares were associated with differences in land area and distance to open sea, both when considering all species pooled and each group separately. Fourteen species were nationally red-listed, and showed similar relationships to the environmental gradients as did all species, specialists and generalists. We suggest that availability of suitable breeding habitats, and probably also proximity to feeding areas, explain much of the observed spatial distributions of coastal birds in this study. Our findings have important implications for systematic conservation planning of coastal breeding birds. In particular, we provide information on where coastal breeding birds occur and which environments they seem to prefer. Small land areas with long shorelines are highly valuable both in general and for red-listed species. Thus, such areas should be prioritized for protection against human disturbance and used by management in reserve selection.

New data on the distribution of barbastelle bat (Barbastella barbastellus) in Western Hungary

Acoustic bat surveys have been carried out between end of April and mid-September of 2013 in several Natura 2000 sites of Vas and Somogy counties. As a result occurrences of barbastelle bat (Barbastella barbastellus) were detected in 9 out of the 12 surveyed Natura 2000 sites. The species was recorded in various riverine and floodland forest communities, such as ash-alder forests, willow-poplar forests and oak-elm-ash forests, as well, as in lowland pedunculate oak-hornbeam woodlands. A total of 17 new UTM 10x10 km2 squares with barbastelle bat occurrence have been added to the 10 formerly known squares in Vas and Somogy counties. The results show a possible expansion of this species in lowland woodland areas, which requires appropriate guidelines for forest management in the affected sites.