Results of the Minnesota Loon Monitoring Program (MLMP) 1994 - 2002

Introduction

Close up of a loon on a lake

The Minnesota Loon Monitoring Program (MLMP) is a long-term project of the Minnesota Department of Natural Resources' Nongame Wildlife Program. Since 1994, nearly 1000 volunteer observers have annually gathered information about common loons in six 100-lake regions, or "index areas" of the state. The data these generous citizens collect provide the Nongame Wildlife Program with an early warning system for detecting changes in the numbers of these birds and the health of their lake habitats in Minnesota. In addition to reporting information about loons and habitat quality, observers also report on the presence of Canada geese on the lakes they survey.

An analysis of eight years of MLMP data indicates that Minnesota's common loon population remains healthy in both number of adults and number of juveniles observed within the index areas. Indeed, data from the Becker index area continues to support a slight, but significant increase in that area's loon population. The abundance of loons varies greatly across the state, and continues to be lowest in the southwestern (Kandiyohi) index area, and highest in the north central (Itasca) index area. The number of juveniles per two adults seen, a measure of reproductive success, also varies among index area and year with no trend evident. Finally, data on Canada goose abundance illustrates a dramatic increase in the southwestern (Kandiyohi and Otter Tail) index areas, but stable populations elsewhere.

These results are for the period of the MLMP survey, 1994-2002.

Methods and Results

Map of the six Index Areas in Minnesota

Because it would be far too difficult to collect loon data from all 12,000 of Minnesota's lakes each year, the MLMP is designed to measure the health of loon populations within six 100-lake "index areas" (see the map to the right). The Nongame Wildlife Program does not have enough staff to collect data at 600 lakes each year. Instead, hundreds of generous volunteer visit their assigned lakes on one morning during a ten-day period in early July. Depending on the size of the lake they survey, the volunteers' survey styles vary widely, with some using boats or canoes, and others surveying from the shore. Similarly, some use binoculars or spotting scopes, and others don't. However, Nongame Wildlife Program staff standardizes methods by providing survey guidelines to all volunteers. In addition to the numbers of loons and geese seen, observers are asked to report on such things as weather and shoreline conditions. Once the survey is completed, data forms are returned to the Nongame Wildlife Program for compilation and analysis.

LOON ABUNDANCE:

Adult Loons Seen per 100 Acres of Lake Surface within an Index Area
Within an index area, abundance measures such as total number of loons seen or average number of loons seen per lake can be compared from year to year. However, since average lake size varies among index areas, we have converted these to the average number of adult loons seen per 100 acres of lake surface so that we can also make comparisons among index areas. During the eight years studied, the only index area demonstrating a significant change in adult loon abundance is the Becker Index area, which increased. The remaining five index areas showed no significant change in abundance. Although slight differences between years can be seen in the figures on pages 5 - 10, these are probably due to normal fluctuations that occur in all natural populations.

Loon abundance ranged from 0.5 - 0.8 in the Kandiyohi index area to 3.3 - 4.0 in the Itasca index area. These differences among index areas confirm previous observations that in Minnesota, loons are most abundant in the central lakes region, and least abundant in the southwest agricultural region, where the species is at the very southern edge of its distributional range in North America.

LOON OCCUPANCY:

Percent of Lakes in an Index Area with Any Adult Loons
Occupancy can be thought of as the likelihood of seeing a loon on a lake. There are no statistically significant changes in occupancy within the six index areas. Occupancy remained stable during the eight years, but fluctuations up to 27% were observed in several areas. Occupancy was calculated as 70% - 77% in the Aitkin/Crow Wing index area, 62% - 84% in the Becker index area, 43% - 61% in the Cook/Lake index area, 76% - 85% in the Itasca index area, 28% - 37% in the Kandiyohi index area, and 42% - 69% in the Otter Tail index area, again consistent with previous observations regarding the distribution of loons within Minnesota.

LOON REPRODUCTIVE SUCCESS:

Juvenile Loons for Every Two Adult Loons on a Lake
Measures of reproductive success are particularly important in monitoring the health of wildlife populations. Especially with long-lived species like the loon, focusing only on adult abundance or occupancy might cause biologists to miss less obvious problems. For example, adults might be present on a lake every year, but fail to raise young year after year. Eventually, this could result in the disappearance of loons from the lake (unless other adults moved in), although this might not occur for many years. Because it is the young of a species that keeps the population going after the adults die, it is critical that a population reproduce successfully.

In this analysis, we calculated the average number of juvenile loons seen for every two adult loons seen. Since a healthy pair of loons typically produce a two-egg clutch each year, this ratio would equal 1 in the ideal world. However, rarely in any wildlife population do all young survive. To maintain a population, each pair of adults need to raise only two young to breeding age during the course of their lives. Although species that only reproduce in one year must raise their young in that one year, loons may nest for many years, and so can afford to be less successful in any one year. Consequently, a low reproductive success in a single year is not necessarily a concern.

During the study period, no statistically significant changes in reproductive success were observed within any of the six index areas. This ratio fluctuates between years in all index areas, but given the smaller sample size than was used for other measures (since lakes with fewer than 2 loons were dropped from the analysis) and the fact that juvenile loons are more likely than adults to be missed by observers, this measure may be less precise than those using only adult data.

Among index areas, reproductive success was calculated as 0.29 - 0.44 in the Aitkin/Crow Wing index area, 0.35 - 0.63 in the Becker index area, 0.07 - 0.41 in the Cook/Lake index area, 0.28 - 0.54 in the Itasca index area, 0.46 - 0.82 in the Kandiyohi index area, and 0.32 - 0.61 in the Otter Tail index area. These surprising results indicate that although the Kandiyohi index area has the lowest abundance and occupancy, the adults living there are the most successful of any index area at raising young. The reason for this is unclear. The relatively poor reproductive success observed in the Cook/Lake index area may be due to the generally low productivity of lakes in that region of the state, or to heavy metal contamination in some of its waters. Further research would be needed to determine the causes of these patterns.

GOOSE ABUNDANCE:

Adult Geese Seen per 100 Acres of Lake Surface within an Index Area
Although the MLMP was designed to monitor the health of the state's loon population, our colleagues in the DNR suggested to us early on that with little additional effort, we could gather data on an unrelated, but important wildlife concern. In recent years, Canada geese have become more widely distributed in the state, and especially in some urban and agricultural areas have reached nuisance levels. During the study period, the Kandiyohi and Otter Tail index areas both exhibit statistically significant increases in goose abundance. Fortunately, since geese are herbivores and nest further from the lakeshore than do loons, these growing goose populations are unlikely to impact loon populations.

Results for individual index areas:

A loon on a lake

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