Anna K. Schweiger

Small-scale habitat use of black grouse ( Tetrao tetrix L.) and rock ptarmigan ( Lagopus muta helvetica Thienemann) in the Austrian Alps

We investigated the small-scale habitat use of two grouse species, black grouse (Tetrao tetrix L.) and rock ptarmigan (Lagopus muta helvetica Thienemann) in a study area in the Austrian Central Alps in summer. To build habitat suitability models, we applied multiple logistic regression using presence–absence data from fieldwork as the response variable and a set of habitat characteristics as explanatory variables, respectively. To gain a better understanding of the mechanisms that drive habitat selection, we tested for two-way interaction terms before excluding any variables from the initial variable set. Four explanatory variables significantly contributed to the black grouse model: dwarf shrub cover, dwarf shrub height, patchiness and ant hills. The final model for rock ptarmigan contained three explanatory variables: dwarf shrub cover, rock cover and dwarf shrub height. Most notably, the interaction terms dwarf shrub cover × patchiness in the black grouse model and dwarf shrub cover × dwarf shrub height, rock cover × dwarf shrub height in the rock ptarmigan model point out trade-off mechanisms between food, cover and overview providing features. Thus, our models do not only identify the parameters that mainly drive habitat selection, but also deepen our understanding about the causal relationships between these factors. Therefore, the information gained in this study allows for a deduction of appropriate habitat management strategies and supports conservation efforts of local stakeholders.

ISS observations offer insights into plant function

In 2018 technologies on the International Space Station will provide ~1 year of synchronous observations of ecosystem composition, structure and function. We discuss these instruments and how they can be used to constrain global models and improve our understanding of the current state of terrestrial ecosystems.

How to predict plant functional types using imaging spectroscopy: linking vegetation community traits, plant functional types and spectral response

1.The comparable and integrated nature of plant functional types and advances in high spectral resolution remote sensing techniques (i.e., imaging spectroscopy) make their combination highly interesting for spatially continuous and repeatable large-scale ecosystem monitoring. Depending on physical environment and stress, plants invest in co-varying biochemical and structural traits, influencing spectral characteristics of vegetation. These traits are assumed to bear a more direct causal relationship to plant functional types than to plant life/growth forms. However, the connection between a vegetation communitys functional and spectral response remains to be established. 2.We assessed the correlation structure between i) biochemical and structural vegetation traits (biomass, dry matter content, nitrogen content, neutral detergent fibre content), ii) plant life/growth forms, and iii) seven plant functional types of two categories (strategy types, indicator values) collected in heterogeneous alpine grassland. We then used airborne imaging spectroscopy data from the same area to model and predict plant life/growth forms and plant functional types at the vegetation community level using partial least squares regression (PLSR), and validated our models based on an independent dataset. 3.We found high correlations between many of the biochemical and structural vegetation traits, plant life/growth forms and plant functional types tested. Using airborne imaging spectroscopy data, we successfully modelled and predicted most plant life/growth forms (R2 max. = 0.56) and all plant functional types (R2 max. = 0.62). However, model performance for plant life/growth forms decreased substantially during external validation and overall model consistency was low (average change in R2 = 72%), while plant functional type models were much more consistent (average change in R2 = 20%). Based on our findings, we developed a conceptual framework using the theory and methodology of vegetation ecology and imaging spectroscopy to link the vegetation communitys functional to its spectral signature. 4.Our results encourage the use of plant functional types in imaging spectroscopy in order to aid the large-scale monitoring of ecosystems, which is particularly important given the increased availability of airborne data and the prospective launches of spaceborne instruments in the near future. This article is protected by copyright. All rights reserved.

Foraging ecology of three sympatric ungulate species - behavioural and resource maps indicate differences between chamois, ibex and red deer

BackgroundThe spatial distribution of forage resources is a major driver of animal movement patterns. Understanding where animals forage is important for the conservation of multi-species communities, since interspecific competition can emerge if different species use the same depletable resources. However, determining forage resources in a spatially continuous fashion in alpine grasslands at high spatial resolution was challenging up to now, because terrain heterogeneity causes vegetation characteristics to vary at small spatial scales, and methods for detection of behavioural phases in animal movement patterns were not widely available. We delineated areas coupled to the foraging behaviour of three sympatric ungulate species (chamois, ibex, red deer) using Time Local Convex Hull (T-LoCoH), a non-parametric utilisation distribution method incorporating spatial and temporal autocorrelation structure of GPS data. We used resource maps of plant biomass and plant nitrogen content derived from high-resolution airborne imaging spectroscopy data, and multinomial logistic regression to compare the foraging areas of the three ungulate species.ResultsWe found significant differences in plant biomass and plant nitrogen content between the core foraging areas of chamois, ibex and red deer. Core foraging areas of chamois were characterised by low plant biomass and low to medium plant nitrogen content. Core foraging areas of ibex were, in contrast, characterised by high plant nitrogen content, but varied in plant biomass, and core foraging areas of red deer had high plant biomass, but varied in plant nitrogen content.ConclusionsPrevious studies carried out in the same study area found no difference in forage consumed by chamois, ibex and red deer. Methodologically, those studies were based on micro-histological analysis of plant fragments identifying them to plant family or functional type level. However, vegetation properties such as productivity (biomass) or plant nutrient content can vary within vegetation communities, especially in highly heterogeneous landscapes. Thus, the combination of high spatial resolution resource maps with a utilisation distribution method allowing to generate behavioural maps (T-LoCoH) provides new insights into the foraging ecology of the three sympatric species, important for their conservation and to monitor expected future changes.

Influence of migratory ungulate management on competitive interactions with resident species in a protected area

Migratory animals can represent links between protected and unprotected parts of their home ranges. Management of such species outside a conservation area can influence species interactions inside the protected zone. This may result in unintended effects on populations of conservation concern even if they spend their entire life cycle within the protected area. We examined interspecific interactions between three species of large herbivores in the absence of mammalian predators in the Swiss National Park, and assessed whether the population size of the migratory red deer (Cervus elaphus) that is harvested outside the park in autumn and winter affected the two resident species, chamois (Rupicapra rupicapra) and ibex (Capra ibex). Dietary overlap was high between the three species while they co-occurred in the park, suggesting potential for interspecific resource competition. Particularly the habitat use of chamois was affected by red deer population size, with decreased use of meadows and forest with increasing red deer numbers, and increased use of areas covered by scree. Ibex habitat use was affected by the population sizes of all three species, but effects differed between species and season. Moreover, horn growth in young chamois and the population growth rate of ibex were negatively related to red deer numbers. The results suggest that high population size of red deer negatively affects ibex and chamois through the migratory behavior of red deer between protected and non-protected areas. Effective management of a migratory ungulate species outside the protected part of its range, taking account of its ecology and natural behavior, can thus have positive effects on populations within a protected area by alleviating interspecific competition. However, this requires co-operation between policy makers and hunters, acceptance by local people, as well as flexibility to deviate from traditional management regimes such as supplementary feeding to tie animals to certain areas.

Harnessing plant spectra to integrate the biodiversity sciences across biological and spatial scales

Plants provide the productive basis for all other life, and their diversity is critical for the Earth’s life support systems. Many plant species are at risk for extinction due to global change factors, including drought stress, exotic species invasions, pathogens, land-use change combined with altered disturbance regimes (e.g., fi re), application of chemicals, and overexploitation. One in fi ve species within the Plant Kingdom is thought to be threatened with extinction ( Kew Royal Botanic Gardens, 2016 ). Given the multifaceted consequences of plant biodiversity for providing the ecosystem services on which humans depend, including the food we grow, the regulating services that maintain our fresh water supply and provision the multitude of organisms we care about, plant biodiversity is important to understand and to monitor across scales from genetic variation at local scales to the entire plant tree of life. Here we argue that deeper understanding and wider application of plant electromagnetic spectra—the patterns of light absorbed, transmitted, and refl ected at diff erent wavelengths from plants—can integrate previously disparate sectors of biodiversity science and the remote sensing community at multiple biological and spatial scales.

Continuous Fields From Imaging Spectrometer Data for Ecosystem Parameter Mapping and Their Potential for Animal Habitat Assessment in Alpine Regions

Remote sensing offers an objective and efficient way to monitor ecosystem properties including their spatial variability across different land cover types. Especially, the representation of gradients of biochemical and structural properties of ecosystems using continuous fields (CF) approaches bears advantages compared to discrete land cover classification schemes. This paper presents a concept to synergistically generate CF maps of an alpine ecosystem parameter, i.e., total surface water content, from imaging spectrometer (IS) data. Further, the potential of linking such maps to ecological patterns, i.e., the spatial distribution of large ungulates is being assessed. In vegetated areas, total surface water content is considered as a surrogate of plant physiological status. Water is, besides temperature, light, or nutrients, an important limiting growth factor determining biomass production and therefore potential animal forage quantity in alpine grasslands. Resource ecology interested in trophic interactions between large ungulates and their forage requires spatial and temporal information on ecosystem properties and processes. The study area is located in the upper Trupchun Valley (Val Trupchun) in the Swiss National Park (SNP). The valley is famous for its high densities of chamois (Rupicapra rupicapra L.), ibex (Capra ibex L.), and red deer (Cervus elaphus L.). CF maps of total surface water content were derived from Airborne Prism EXperiment (APEX) IS data collected over the SNP in June 2010 and 2011. Abundance maps of predominant land cover classes were derived from linear spectral mixture analysis (SMA). They were then combined with water content information of the respective land cover originating from either empirically or physically based approaches. The resulting CF maps depicted a spatially continuous representation of relative total surface water content. APEX IS data from two consecutive seasons revealed differences in total surface water content in June 2010 and 2011, predominantly related to an advanced phenological development in spring 2011 and to considerable differences in snow cover between the 2 years. Linking total surface water content of grasslands to observed ungulates spatial distributions did not reveal any statistically significant patterns of habitat use. We conclude that water availability in Val Trupchun may not be the dominant limiting factor for potential forage quantity (biomass), or that ungulates choose their grazing sites based on other criteria, i.e., high nutritious quality (P, N). Nevertheless, multitemporal CF maps derived from APEX IS data were found to provide spatially explicit and fine-scaled information for analyses of an ecosystems total surface water content. The combination of multitemporal CF maps of a wide range of ecosystem parameters and more accurate and extensive observations of animal habitat use will contribute to ongoing and future vegetation-ungulates research in the SNP.

Mapping Alpine Aboveground Biomass From Imaging Spectrometer Data: A Comparison of Two Approaches

Aboveground biomass (AGB) of terrestrial ecosystems is an important constraint of global change and productivity models and used to assess carbon stocks and thus the contribution of vegetated ecosystems to the global carbon cycle. Although an indispensable and important requirement for decision makers, coherent and accurate estimates of grassland and forest AGB especially in complex environments are still lacking. In this study, we aim to assess the capability of two strategies to map grassland and forest AGB in a complex alpine ecosystem, i.e., using a discrete as well as a continuous field (CF) mapping approach based on imaging spectroscopy (IS) data. In situ measurements of grassland and forest AGB were acquired in the Swiss National Park (SNP) to calibrate empirical models and to validate AGB retrievals. The selection of robust empirical models considered all potential two narrow-band combinations of the simple ratio (SR) and the normalized difference vegetation index (NDVI) generated from Airborne Prism Experiment (APEX) IS data and in situ measurements. We found a narrow-band SR including spectral bands from the short-wave infrared (SWIR) (1689 nm) and near infrared (NIR) (851 nm) as the best regression model to estimate grassland AGB. Forest AGB showed highest correlation with an SR generated from two spectral bands in the SWIR (1498, 2112 nm). The applied accuracy assessment revealed good results for estimated grassland AGB using the discrete mapping approach [R2 of 0.65, mean RMSE (mRMSE) of 0.91 t · ha-1, and mean relative RMSE (mrRMSE) of 26%]. The CF mapping approach produced a higher R2 (R2 = 0.94 ), and decreased the mRMSE and the mrRMSE to 0.55 t · ha-1 and 15%, respectively. For forest, the discrete approach predicted AGB with an R2 value of 0.64, an mRMSE of 67.8 t · ha-1 , and an mrRMSE of 25%. The CF mapping approach improved the accuracy of forest AGB estimation with R2 = 0.85 , mean RMSE = 55.85 t · ha-1, and mean relative RMSE = 21%. Our results indicate that, in general, both mapping approaches are capable of accurately mapping grassland and forest AGB in complex environments using IS data, whereas the CF-based approach yielded higher accuracies due to its capability to incorporate subpixel information (abundances) of different land cover types.

Genetic, morphological, and spectral characterization of relictual Niobrara River hybrid aspens (Populus × smithii)

PREMISE OF THE STUDY Aspen groves along the Niobrara River in Nebraska have long been a biogeographic curiosity due to morphological differences from nearby remnant Populus tremuloides populations. Pleistocene hybridization between P. tremuloides and P. grandidentata has been proposed, but the nearest P. grandidentata populations are currently several hundred kilometers east. We tested the hybrid-origin hypothesis using genetic data and characterized putative hybrids phenotypically. METHODS We compared nuclear microsatellite loci and chloroplast sequences of Niobrara River aspens to their putative parental species. Parental species and putative hybrids were also grown in a common garden for phenotypic comparison. On the common garden plants, we measured leaf morphological traits and leaf-level spectral reflectance profiles, from which chemical traits were derived. KEY RESULTS The genetic composition of the three unique Niobrara aspen genotypes is consistent with the hybridization hypothesis and with maternal chloroplast inheritance from P. grandidentata. Leaf margin dentition and abaxial pubescence differentiated taxa, with the hybrids showing intermediate values. Spectral profiles allowed statistical separation of taxa in short-wave infrared wavelengths, with hybrids showing intermediate values, indicating that traits associated with internal structure of leaves and water absorption may vary among taxa. However, reflectance values in the visible region did not differentiate taxa, indicating that traits related to pigments are not differentiated. CONCLUSIONS Both genetic and phenotypic results support the hypothesis of a hybrid origin for these genetically unique aspens. However, low genetic diversity and ongoing ecological and climatic threats to the hybrid taxon present a challenge for conservation of these relictual boreal communities.

Ecosystem parameter mapping in Swiss National Park based on a continuous fields approach

Adequate assessment and management of landscape patterns and processes need proper representation and quantification of gradients of ecosystem biochemical and structural properties. Discrete land cover mapping approaches represent landscapes as classified entities with “hard” boundaries. On the other hand, continuous field representations of land cover or ecosystem parameters offer the potential to overcome the limitations of classified entities that can often not reproduce the full range and variability of land surface properties. This paper presents a concept to generate continuous fields (CF) maps of ecosystem parameters in an alpine environment. The concept is exemplarily presented on a high mountain ecosystems total (above ground) water content and is performed in the upper Trupchun valley (Val Trupchun) in the Swiss National Park (SNP). It is applicable to further parameters. Airborne Prism EXperiment (APEX) imaging spectrometer (IS) data collected over the SNP in June 2010 and 2011 are used for CF mapping of water content. Abundance maps of predominant land cover classes are derived from linear spectral mixture analysis (SMA). They are then combined with individual thematic water content information of the respective land cover originating from either spectral indices or a physically based approach. The resulting product depicts a spatially continuous representation of total water content. The availability of APEX IS data from two consecutive seasons allows studying differences in ecosystem water content over time. CF maps can be generated for a wide range of ecosystem parameters. If multi-temporally available, such products can be useful for explaining ecological patterns such as animal grazing patterns in SNP.