Modelling Distributions of Rove Beetles in Mountainous Areas Using Remote Sensing Data

Mountain ecosystems are biodiversity hotspots that are increasingly threatened by climate and land use/land cover changes. Long-term biodiversity monitoring programs provide unique insights into resulting adverse impacts on plant and animal species distribution. Species distribution models (SDMs) in combination with satellite remote sensing (SRS) data offer the opportunity to analyze shifts of species distributions in response to these changes in a spatially explicit way. Here, we predicted the presence probability of three different rove beetles in a mountainous protected area (Gran Paradiso National Park, GPNP) using environmental variables derived from Landsat and Aster Global Digital Elevation Model data and an ensemble modelling approach based on five different model algorithms (maximum entropy, random forest, generalized boosting models, generalized additive models, and generalized linear models). The objectives of the study were (1) to evaluate the potential of SRS data for predicting the presence of species dependent on local-scale environmental parameters at two different time periods, (2) to analyze shifts in species distributions between the years, and (3) to identify the most important species-specific SRS predictor variables. All ensemble models showed area under curve (AUC) of the receiver operating characteristics values above 0.7 and true skills statistics (TSS) values above 0.4, highlighting the great potential of SRS data. While only a small proportion of the total area was predicted as highly suitable for each species, our results suggest an increase of suitable habitat over time for the species Platydracus stercorarius and Ocypus ophthalmicus, and an opposite trend for Dinothenarus fossor. Vegetation cover was the most important predictor variable in the majority of the SDMs across all three study species. To better account for intra- and inter-annual variability of population dynamics as well as environmental conditions, a continuation of the monitoring program in GPNP as well as the employment of SRS with higher spatial and temporal resolution is recommended

Distribution Drivers of the Alien Butterfly Geranium Bronze (Cacyreus marshalli) in an Alpine Protected Area and Indications for an Effective Management

Cacyreus marshalli is the only alien butterfly in Europe. It has recently spread in the Gran Paradiso National Park (GPNP), where it could potentially compete with native geranium-consuming butterflies. Our study aimed to (1) assess the main drivers of its distribution, (2) evaluate the potential species distribution in GPNP and (3) predict different scenarios to understand the impact of climate warming and the effect of possible mitigations. Considering different sampling designs (opportunistic and standardised) and different statistical approaches (MaxEnt and N-mixture models), we built up models predicting habitat suitability and egg abundance for the alien species, testing covariates as bioclimatic variables, food plant (Pelargonium spp.) distribution and land cover. A standardised approach resulted in more informative data collection due to the survey design adopted. Opportunistic data could be potentially informative but a major investment in citizen science projects would be needed. Both approaches showed that C. marshalli is associated with its host plant distribution and therefore confined in urban areas. Its expansion is controlled by cold temperatures which, even if the host plant is abundant, constrain the number of eggs. Rising temperatures could lead to an increase in the number of eggs laid, but the halving of Pelargonium spp. populations would mostly mitigate the trend, with a slight countertrend at high elevations

Climate Change and Human Disturbance Can Lead to Local Extinction of Alpine Rock Ptarmigan: New Insight from the Western Italian Alps

<div><p>Alpine grouses are particularly vulnerable to climate change due to their adaptation to extreme conditions and to their relict distributions in the Alps where global warming has been particularly marked in the last half century. Grouses are also currently threatened by habitat modification and human disturbance, and an assessment of the impact of multiple stressors is needed to predict the fate of Alpine populations of these birds in the next decades. We estimated the effect of climate change and human disturbance on a rock ptarmigan population living in the western Italian Alps by combining an empirical population modelling approach and stochastic simulations of the population dynamics under the a1B climate scenario and two different disturbance scenarios, represented by the development of a ski resort, through 2050.The early appearance of snow-free ground in the previous spring had a favorable effect on the rock ptarmigan population, probably through a higher reproductive success. On the contrary, delayed snowfall in autumn had a negative effect possibly due to a mismatch in time to molt to white winter plumage which increases predation risk. The regional climate model PROTHEUS does not foresee any significant change in snowmelt date in the study area, while the start date of continuous snow cover is expected to be significantly delayed. The net effect in the stochastic projections is a more or less pronounced (depending on the model used) decline in the studied population. The addition of extra-mortality due to collision with ski-lift wires led the population to fatal consequences in most projections. Should these results be confirmed by larger studies the conservation of Alpine populations would deserve more attention. To counterbalance the effects of climate change, the reduction of all causes of death should be pursued, through a strict preservation of the habitats in the present area of occurrence.</p> </div

Time series of population densities.

<p>Observed spring cock densities in the period 1996-2012 (dots and solid line) and estimated breeding pairs densities from the fitted Gompertz state-space model (triangles and dotted line).</p

Climatic effects on rock ptarmigan population dynamics.

<p>Relationship between the population growth rate and snowmelt date at time <i>t-1</i> (a) (days from 1^st May) and start date of a continuous snow cover at time <i>t-1</i> (b) (days from 1^st October).</p

Population projections of rock ptarmigans for the period 2013-2050.

<p>(a) Projections performed using populations models M1, M2, and M6 (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081598#pone-0081598-t001" target="_blank">Table 1</a>) or a simple Gompertz density dependence model (DD) and the meteorological variables generated by the PROTHEUS model for the A1B scenario; (b) simulations of the joint effect of climate change and human disturbance using the same models as before and an extra-mortality term due to wire collision in a highly developed ski resort (0.16 <i>N</i>_<i>t-1</i> + 0.02 individuals/km² per year). Thick line: estimated breeding pairs densities (cocks/km²); thin line: 50% percentile, shaded area: 5–95% percentiles of the 1000 runs; the red line represents one random realization.</p

Modelling Distributions of Rove Beetles in Mountainous Areas Using Remote Sensing Data

Mountain ecosystems are biodiversity hotspots that are increasingly threatened by climate and land use/land cover changes. Long-term biodiversity monitoring programs provide unique insights into resulting adverse impacts on plant and animal species distribution. Species distribution models (SDMs) in combination with satellite remote sensing (SRS) data offer the opportunity to analyze shifts of species distributions in response to these changes in a spatially explicit way. Here, we predicted the presence probability of three different rove beetles in a mountainous protected area (Gran Paradiso National Park, GPNP) using environmental variables derived from Landsat and Aster Global Digital Elevation Model data and an ensemble modelling approach based on five different model algorithms (maximum entropy, random forest, generalized boosting models, generalized additive models, and generalized linear models). The objectives of the study were (1) to evaluate the potential of SRS data for predicting the presence of species dependent on local-scale environmental parameters at two different time periods, (2) to analyze shifts in species distributions between the years, and (3) to identify the most important species-specific SRS predictor variables. All ensemble models showed area under curve (AUC) of the receiver operating characteristics values above 0.7 and true skills statistics (TSS) values above 0.4, highlighting the great potential of SRS data. While only a small proportion of the total area was predicted as highly suitable for each species, our results suggest an increase of suitable habitat over time for the species Platydracus stercorarius and Ocypus ophthalmicus, and an opposite trend for Dinothenarus fossor. Vegetation cover was the most important predictor variable in the majority of the SDMs across all three study species. To better account for intra- and inter-annual variability of population dynamics as well as environmental conditions, a continuation of the monitoring program in GPNP as well as the employment of SRS with higher spatial and temporal resolution is recommended

Butterfly distribution along altitudinal gradients: temporal changes over a short time period

Mountain ecosystems are particularly sensitive to changes in climate and land cover, but at the same time, they can offer important refuges for species on the opposite of the more altered lowlands. To explore the potential role of mountain ecosystems in butterfly conservation and to assess the vulnerability of the alpine species, we analyzed the short-term changes (2006–2008 vs. 2012–2013) of butterflies’ distribution along altitudinal gradients in the NW Italian Alps. We sampled butterfly communities once a month (62 sampling stations, 3 seasonal replicates per year, from June to August) by semi-quantitative sampling techniques. The monitored gradient ranges from the montane to the alpine belt (600–2700 m a.s.l.) within three protected areas: Gran Paradiso National Park (LTER, Sitecode: LTER_EU_IT_109), Orsiera Rocciavrè Natural Park and Veglia Devero Natural Park. We investigated butterflies’ temporal changes in accordance with a hierarchical approach to assess potential relationships between species and community level. As a first step, we characterized each species in terms of habitat requirements, elevational range and temperature preferences and we compared plot occupancy and altitudinal range changes between time periods (2006–2008 vs. 2012–2013). Secondly, we focused on community level, analyzing species richness and community composition temporal changes. The species level analysis highlighted a general increase in mean occupancy level and significant changes at both altitudinal boundaries. Looking at the ecological groups, we observed an increase of generalist and highly mobile species at the expense of the specialist and less mobile ones. For the community level, we noticed a significant increase in species richness, in the community temperature index and a tendency towards homogenization within communities. Besides the short time period considered, butterflies species distribution and communities changed considerably. In light of these results, it is fundamental to continue monitoring activities to understand if we are facing transient changes or first signals of an imminent trend

Patterns of biodiversity in the northwestern Italian Alps: a multi-taxa approach

The current loss of biodiversity requires long-term monitoring of the distribution of living organisms, particularly in regions, such as mountains, which are highly sensitive to climatic and environmental changes. In 2007, three alpine parks in N-W Italy started a field program to determine the factors which influence animal biodiversity and identify the most appropriate methods for periodically repeatable monitoring. Twelve altitudinal transects (from montane to alpine belt) were chosen, each composed of 4-7 sampling units, for a total of 69 monitored plots. In each station, five taxonomic groups (carabids, butterflies, spiders, staphylinids, birds) were systematically sampled and topographic, environmental and micro-climatic variables were recorded. The aim was to assess the distribution of different taxa along altitudinal gradients and the relative influence of geographical, environmental and climatic factors. The data showed that species richness and community composition of invertebrates are mainly determined by altitude and microclimatic conditions, whereas birds are more sensitive to habitat structure. For invertebrates, the strong relationship with temperature suggests their potential sensitivity to climatic variations. The analysis of biodiversity patterns across vegetation belts indicated that the alpine belt hosts few species but a high percentage of endemic and vulnerable species, highlighting its importance for conservation purposes. This work offers a representative sample of the northwestern Italian Alps and it is a first step of a monitoring effort that will be repeated every five years to highlight the response of alpine biodiversity to climate and land-use changes