Forest Understory Moths

We are matching changes in understory plant diversity to changes in forest-specialist moth diversity over a 60-year period to gain insight into the broader ecological effects of deer overabundance.

Dale Schweitzer with a light trap

A nine year survey of moths and butterflies on the Kittatinny Ridge of Northwest New Jersey published in the Journal of Insect Conservation has revealed that we are losing our understory-specialist moths and butterflies.  After compiling a historic list of forest moths and butterflies  that occurred in the area at the turn of the 20th century (based on museum collections and published records), We set out to see what proportion of these we could still find.

A moth light trap, doing its work in the darkness

The good news is that we found nearly 92% of the total species that were expected.  The bad news is that the 8% of species we didn’t find were primarily species whose caterpillars specialize on particular forest understory plants.


While we don’t yet have smoking-gun evidence, we think the cause of the missing moths is deer.  White-tailed deer populations exploded during the mid to late 20th century in our study area and elsewhere.

When deer get too numerous and have few natural predators, they can dramatically shape the appearance of forests.

Deer can only reach so high.  They’d eat the whole tree if they could

For example, at Rutgers’ Hutcheson Memorial Forest, researchers conducted long term experiments to observe the growth of an old field to forest.  One of the experiments was to fence portions of  old fields to exclude deer.

Several years ago I saw these fields, fenced and unfenced, after 20 or so years of growth.  The trees inside the fence were entirely different from those outside the fence.   The subtle work of foraging deer produced a red cedar-dominated forest outside of the fence.  

Inside the fence was entirely deciduous trees dominated by red maple. The deer ate the hardwood seeedlings before they could become trees while avoiding the less-preferred cedars which by default became the dominant vegetation.

As bad as it gets – the scene inside and outside a deer exclosure in British Columbia

Dramatic changes like these are happening throughout deer infested landscapes.  Although numerous studies have documented the impact of deer on plant communities, there have been far fewer studies on how overabundant deer affect other forest animals.

Our work suggests that deer are having an impact on the butterflies and moths that, as caterpillars, eat many of the same forest understory plants that deer prefer.

Many of the food plants of our missing understory moths and butterflies seemed to be scarce during our moth-hunting expeditions, but we wanted hard evidence that plant populations have changed over time.

That’s where the next stage of this research came into play.

We discovered that detailed vegetation surveys of High Point State Park were published in 1950 by WIlliam Niering.  This gave us a way to measure the change in the abundance of some key moth and butterfly food plants since then.  

Data from Niering’s 1950 report. Several key shrubs were far more abundant then such as beaked hazel (Corylus cornuta) and maple leaf viburnum (Viburnum acerifolium).

In order to measure changes in understory vegetation composition, we relocated Niering’s sites and repeated his vegetation surveys.

Vegetation transect at High point state park using the same locations and methods as Niering

In addition, we wanted to assess deer density in the park and test the hypothesis that density varies by habitat.  Our hunch is that there is more browse pressure and higher relative deer density in the “rich forest” along stream valleys that are (or were) home to many of our missing moths and their food plants compared with dry upland oak forest that is the dominant forest type on the Kittatinny Ridge.

The results of these additional ecological components are still in the works.  

See this blog post for a tour of some of the understory host plants that are part of our studies.

Twitter