Geology topics

Timothy Duclos

Publications and source records attributed to Timothy Duclos.

3 recordsLinked to original sources

USGS2025

Does habitat or climate change drive species range shifts?

A primary prediction of climate change ecology is that species will track their climate niche poleward and upslope. However, studies have shown species responding in surprising ways. In this study, we aim to understand the impact of global change on species ranges by considering both climate and habitat changes. Using occupancy analysis of acoustic survey data in the mountains of the northeastern United States, we tested specific predictions of range responses to warming (shifting upslope), precipitation change (shifting downslope), and forest composition change (shifting downslope). We found that American red squirrels Tamiasciurus hudsonicus , key nodes in northern North American food webs, are not tracking increasing temperatures upslope, despite substantial warming in recent decades. Structural equation modeling indicates that red squirrel abundance is primarily influenced by red-spruce forest cover, which has shifted downslope with recovery from historical logging and acid deposition. Accounting for the multiple dimensions of global change will enable better predictions and more effective conservation strategies.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2024

Boom and bust: The effects of masting on seed predator range dynamics and trophic cascades

Aim Spatiotemporal variation in resource availability is a strong driver of animal distributions. In the northern hardwood and boreal forests of the northeastern United States, tree mast events provide resource pulses that drive the population dynamics of small mammals, including the American red squirrel ( Tamiasciurus hudsonicus ), a primary songbird nest predator. This study sought to determine whether mast availability ameliorates their abiotic limits, enabling red squirrel elevational distributions to temporarily expand and negatively impact high-elevation songbirds. Location Northeastern United States. Methods We used two independent datasets to evaluate our hypotheses. First, we fit a dynamic occupancy model using data from camera trap surveys to evaluate red squirrel distributional responses to pulses in the tree mast. We also assessed population responses using systematic auditory surveys analysed with an open-population binomial mixture model. Further, we used modelled red squirrel abundance in nest-survival models to evaluate whether their abundance is correlated with the daily nest survival of three songbird species. Results The tree mast provided a critical resource pulse that resulted in a two-fold increase in the annual elevational distribution of red squirrels. The elevational distribution of red squirrels ranged from a minimum of ~450 m (range: 663–1145 m asl) following two consecutive years without a masting event to a maximum of over 1000 m (range: 443–1545 m asl) after a large mast event. The daily nest survival of three songbird species tended to decline with an increase in the abundance of red squirrels. Main Conclusions Tree mast is a central biological phenomenon in many temperate and boreal forests. This study reveals how this resource pulse results in range changes in a small mammal that is both a seed and bird predator, as well as prey for many carnivores. Thus, understanding this phenomenon can inform the conservation and management of northern forests, including breeding songbirds.

Connecticut, Maine, Massachusetts, New Hampshire, ↗

USGS2018

Looking beyond wildlife: Using remote cameras to evaluate accuracy of gridded snow data

The use of remote cameras is widespread in wildlife ecology, yet few examples exist of their utility for collecting environmental data. We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS ) gridded predictions using data from three winters (2014–2016). Snow depth observations were correlated with SNODAS predictions for sites ( R 2 = 0.20) and regions ( R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer‐dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km 2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species’ responses to climate change.

New Hampshire, Vermont↗