Predictive models of distribution and abundance of a threatened mountain species show that impacts of climate change overrule those of land use change

A 37 years [1984-2021] Landsat/Sentinel-2 derived snow cover time-series for Switzerland

Switzerland, renowned for its mountainous landscapes, holds nearly 10% of Europe's water reserves, with 40% of its running waters originating from snowmelt. Snow plays a crucial role in the country's water management, hydroelectric power, and alpine ecosystems. It supports freshwater supply, agriculture, and tourism, making accurate snow monitoring vital for resource management and environmental preservation. Climate change, however, threatens snow cover, impacting water availability, biodiversity, and ecosystem services. Remote sensing technologies have emerged as key tools for monitoring snow cover, providing critical data for climate models, hazard prediction, and resource planning. In Switzerland, snow cover is monitored using ground-based measurements, remote sensing, and climate models, with datasets from satellites like Landsat and Sentinel-2 offering valuable insights despite challenges such as cloud obstruction. Such data are essential for hydrological modelling, agricultural monitoring, and climate studies, contributing to our understanding of global warming and aiding in natural hazard assessment. Hereafter, we present a 37-year monthly time-series of snow cover derived from Landsat and Sentinel-2 data using the Snow Observations from Space algorithm and processed in the Swiss Data Cube that facilitates the analysis, production and reuse of this Essential Climate Variable, enhancing environmental monitoring efforts at national scale.

Adaptive stacked species distribution modelling: Novel approaches to large scale quantification of blue carbon to support marine management

This study introduces a novel concept of 'Adaptively Stacked' Species Distribution Models (AS-SDMs) to predict blue carbon habitat distribution, abundance, carbon stocks, and carbon sequestration potential in Orkney. AS-SDMs are built from Weighted Boosted Regression Trees (WBRTs) that adaptively stack blue carbon sediment thickness, sediment carbon content, and sequestration potential to predicted abundance. A novel method to describe substrate types by relative inputs of mud, sand, and gravel is detailed that better characterises the determining factors of seagrass, maerl, and horse mussel abundance. This study also introduces a novel use of indexes to mitigate double counting issues of mixed species distribution models. Seagrass, maerl, horse mussel, and mixed seagrass and maerl (SGM) habitats are estimated to cover a maximum area of 657 km2 in Orkney, have a total sediment carbon stock of 16 Mt. C, and sequester 6000 t C yr-1. Applying a conservative threshold of 50 % abundance to habitat predictions, six key potential areas of blue carbon offset projects are identified. These areas cover just over 9 km2, have a total carbon stock of 330,000 t C, and sequester 330 t C yr-1. When applied to UK carbon credit value, assuming integration with voluntary markets and compliance with accreditation criteria, the habitats in these areas have a potential value of £24.5 million. If applied as annual values, these areas have carbon stocks with a potential value of £0.93 million yr-1 and a carbon sequestration potential value of £24,000 yr-1.

Predicting the impact of climate change and land use change on the potential distribution of two economic forest trees in Northeastern China

Young shoots of Aralia elata and young leaves of Eleutherococcus senticosus are two major non-timber forest products in northeastern China. However, human activities and climate change have resulted in serious threats to the habitats of two trees, which greatly limits resource conservation and exploitation of economic forest trees. We used the MaxEnt model to predict the suitable habitats of the two economic trees and analyzed the dominant factors affecting their distribution. The results showed that the suitable habitat areas of A. elata and E. senticosus in the current period were 159950 km2 and 123449 km2, respectively, and the suitable habitats of both economic forest trees were located in the eastern part of the northeast region. Climate factors (Annual precipitation, Precipitation Seasonality) and land use factors are important variables influencing changes in suitable habitat for both trees. With the change of climate and land use in the future, the overall trend of suitable habitat for both economic forest trees shows a northward and then a southward migration. These results may provide assistance in developing strategies for resource conservation and sustainable use of A. elata and E. senticosus, and we suggest that stable and suitable habitats should be selected as areas for in situ conservation and breeding of the two economic forest trees.

Demography-environment relationships improve mechanistic understanding of range dynamics under climate change

Species respond to climate change with range and abundance dynamics. To better explain and predict them, we need a mechanistic understanding of how the underlying demographic processes are shaped by climatic conditions. Here, we aim to infer demography-climate relationships from distribution and abundance data. For this, we developed spatially explicit, process-based models for eight Swiss breeding bird populations. These jointly consider dispersal, population dynamics and the climate-dependence of three demographic processes-juvenile survival, adult survival and fecundity. The models were calibrated to 267 nationwide abundance time series in a Bayesian framework. The fitted models showed moderate to excellent goodness-of-fit and discriminatory power. The most influential climatic predictors for population performance were the mean breeding-season temperature and the total winter precipitation. Contemporary climate change benefitted the population trends of typical mountain birds leading to lower population losses or even slight increases, whereas lowland birds were adversely affected. Our results emphasize that generic process-based models embedded in a robust statistical framework can improve our predictions of range dynamics and may allow disentangling of the underlying processes. For future research, we advocate a stronger integration of experimental and empirical studies in order to gain more precise insights into the mechanisms by which climate affects populations. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Ecological barriers mediate spatiotemporal shifts of bird communities at a continental scale

Species' range shifts and local extinctions caused by climate change lead to community composition changes. At large spatial scales, ecological barriers, such as biome boundaries, coastlines, and elevation, can influence a community's ability to shift in response to climate change. Yet, ecological barriers are rarely considered in climate change studies, potentially hindering predictions of biodiversity shifts. We used data from two consecutive European breeding bird atlases to calculate the geographic distance and direction between communities in the 1980s and their compositional best match in the 2010s and modeled their response to barriers. The ecological barriers affected both the distance and direction of bird community composition shifts, with coastlines and elevation having the strongest influence. Our results underscore the relevance of combining ecological barriers and community shift projections for identifying the forces hindering community adjustments under global change. Notably, due to (macro)ecological barriers, communities are not able to track their climatic niches, which may lead to drastic changes, and potential losses, in community compositions in the future.

Identifying climate refugia for high-elevation Alpine birds under current climate warming predictions

Identifying climate refugia is key to effective biodiversity conservation under a changing climate, especially for mountain-specialist species adapted to cold conditions and highly threatened by climate warming. We combined species distribution models (SDMs) with climate forecasts to identify climate refugia for high-elevation bird species (Lagopus muta, Anthus spinoletta, Prunella collaris, Montifringilla nivalis) in the European Alps, where the ecological effects of climate changes are particularly evident and predicted to intensify. We considered future (2041-2070) conditions (SSP585 scenario, four climate models) and identified three types of refugia: (1) in-situ refugia potentially suitable under both current and future climate conditions, ex-situ refugia suitable (2) only in the future according to all future conditions, or (3) under at least three out of four future conditions. SDMs were based on a very large, high-resolution occurrence dataset (2901-12,601 independent records for each species) collected by citizen scientists. SDMs were fitted using different algorithms, balancing statistical accuracy, ecological realism and predictive/extrapolation ability. We selected the most reliable ones based on consistency between training and testing data and extrapolation over distant areas. Future predictions revealed that all species (with the partial exception of A. spinoletta) will undergo a range contraction towards higher elevations, losing 17%-59% of their current range (larger losses in L. muta). We identified ~15,000 km² of the Alpine region as in-situ refugia for at least three species, of which 44% are currently designated as protected areas (PAs; 18%-66% among countries). Our findings highlight the usefulness of spatially accurate data collected by citizen scientists, and the importance of model testing by extrapolating over independent areas. Climate refugia, which are only partly included within the current PAs system, should be priority sites for the conservation of Alpine high-elevation species and habitats, where habitat degradation/alteration by human activities should be prevented to ensure future suitability for alpine species.

The contribution of landscape features, climate and topography in shaping taxonomical and functional diversity of avian communities in a heterogeneous Alpine region

Understanding the effects of landscape composition and configuration, climate, and topography on bird diversity is necessary to identify distribution drivers, potential impacts of land use changes, and future conservation strategies. We surveyed bird communities in a study area located in the Central Alps (Autonomous Province of South Tyrol, northeast Italy), by means of point counts and investigated taxonomic and functional diversity at two spatial scales along gradients of land use/land cover (LULC) intensity and elevation. We also explored how environmental variables influence bird traits and red-list categories. Models combining drivers of different types were highly supported, pointing towards synergetic effects of different types of environmental variables on bird communities. The model containing only LULC compositional variables was the most supported one among the single-group models: LULC composition plays a crucial role in shaping local biodiversity and hence bird communities, even across broad landscape gradients. Particularly relevant were wetlands, open habitats, agricultural mosaics made up of small habitat patches and settlements, ecotonal and structural elements in agricultural settings, and continuous forests. To conserve bird diversity in the Alps, planning and management practices promoting and maintaining small fields, structural elements, and a mosaic of different LULC types should be supported, while preserving continuous forests at the same time. Additionally, pastures, extensively used meadows, and wetlands are key to conservation. These strategies might mitigate the impacts of global change on bird diversity in the Alps and in other European mountain areas.

Variation in Demography and Life-History Strategies Across the Range of a Declining Mountain Bird Species

Species- and population-specific responses to their environment may depend to a large extent on the spatial variation in life-history traits and in demographic processes of local population dynamics. Yet, those parameters and their variability remain largely unknown for many cold-adapted species, which are exposed to particularly rapid rates of environmental change. Here, we compared the demographic traits and dynamics for an emblematic bird species of European mountain ecosystems, the ring ouzel (Turdus torquatus). Using integrated population models fitted in a Bayesian framework, we estimated the survival probability, productivity and immigration of two populations from the Western European Alps, in France (over 11 years) and Switzerland (over 6 years). Juvenile apparent survival was lower and immigration rate higher in the Swiss compared to the French population, with the temporal variation in population growth rate driven by different demographic processes. Yet, when compared to populations in the northwestern part of the range, in Scotland, these two Alpine populations both showed a much lower productivity and higher adult survival, indicating a slower life-history strategy. Our results suggest that demographic characteristics can substantially vary across the discontinuous range of this passerine species, essentially due to contrasted, possibly locally evolved life-history strategies. This study therefore raises the question of whether flexibility in life-history traits is widespread among boreo-alpine species and if it might provide adaptive potential for coping with current environmental change.