Geology topics

Alexej Sirén

Publications and source records attributed to Alexej Sirén.

3 recordsLinked to original sources

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, ↗

USGS2023

A Great Escape: Resource availability and density-dependence shape population dynamics along trailing range edges

Populations along geographical range limits are often exposed to unsuitable climate and low resource availability relative to core populations. As such, there has been a renewed focus on understanding the factors that determine range limits to better predict how species will respond to global change. Using recent theory on range limits and classical understanding of density dependence, we evaluated the influence of resource availability on the snowshoe hare Lepus americanus along its trailing range edge. We estimated variation in population density, habitat use, survival, and parasite loads to test the Great Escape Hypothesis (GEH), i.e. that density dependence determines, in part, a species' persistence along trailing edges. We found that variability in resource availability affected density and population fluctuations and led to trade-offs in survival for snowshoe hare populations in the northeastern USA. Hares living in resource-limited environments had lower and less variable population density, yet higher survival and lower parasitism compared to populations living in resource-rich environments. We suggest that density-dependent dynamics, elicited by resource availability, provide hares a unique survival advantage and partly explain persistence along their trailing edge. We hypothesize that this low-density escape from predation and parasitism occurs for other prey species along trailing edges, but the extent to which it occurs is likely conditional on the quality of matrix habitat. Our work indicates that biotic factors play an important role in shaping species' trailing edges and more detailed examination of non-climatic factors is warranted to better inform conservation and management decisions.

New Hampshire, Vermont↗

USGS2022

Forecasting species distributions: Correlation does not equal causation

Aim Identifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects. Location New Hampshire and Vermont, USA. Methods Using causal and correlational models and new theory on range limits, we compared current (2014–2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high-emission scenario (RCP8.5) of projected snow and forest biomass change. Results Our hypothesis that causal models of climate-mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well-supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx ( Lynx canadensis ) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat ( Lynx rufus ). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high-elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx. Main conclusions Our comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change.

New Hampshire, Vermont↗