The tables and figures below summarize Ecological Monitoring Network (EMN) progress and patterns in the data being collected, as plots are installed and surveyed across Minnesota. Regular resurveys in the future will document long-term change, or stability, in vegetation in the monitoring plots. The patterns highlighted below relate to several of EMN’s basic objectives: for example tracking trends in invasive species and detecting change in measures of forest health. These highlights represent just a small fraction of the information and patterns that can be extracted from data that will be collected over time at EMN plots.
Summary
- EMN has established and surveyed 387 plots, from the beginning of the project in 2017 through the 2023 field season.
- We plan to install and collect data from 500-550 plots in total to monitor change in Minnesota’s native forest, prairie and wetland vegetation.
- 45% of the plots established so far are in upland forests, 23% in open wetlands, 15% in forested wetlands, 12% in upland prairies and 5% in wetland prairies.
- 42% of plots are on land managed by the state of Minnesota (such as wildlife management areas, scientific and natural areas, and state forests), 20% on federally managed lands, 18% on privately owned lands, and 17% on lands managed by local governments (such as county parks, city parks, and tax forfeited land).
Figure 1. Map of 387 installed EMN monitoring plots through 2023.
| Plot ID | Land Manager | County |
| 99003 | FOR | Olmsted |
| 99004 | FOR | Olmsted |
| 99002 | FOR | Olmsted |
| 127 | SNF | St. Louis |
| 3604 | FOR | Houston |
| 2560 | Private | Rock |
| 752 | Private | Lyon |
| 713 | WMA | Kanabec |
| 3271 | WMA | Big Stone |
| 1763 | WPA | Grant |
| 1967 | FOR | Koochiching |
| 1869 | County | Hennepin |
| 1074 | County | St. Louis |
| 1693 | city | Anoka |
| 4436 | Private | Olmsted |
| 3928 | County | Scott |
| 857 | FOR | Pine |
| 673 | SNF | Lake |
| 1172 | Private | Wabasha |
| 994 | SNF | St. Louis |
| 2653 | County | Hennepin |
| 1236 | WMA | Olmsted |
| 3414 | FOR | Cass |
| 59 | SNF | Cook |
| 1015 | FOR | Lake of the Woods |
| 561 | SNF | Lake |
| 585 | Private | Kanabec |
| 870 | County | Cass |
| 473 | Private | Stearns |
| 4968 | Private | Blue Earth |
| 422 | CNF | Cass |
| 319 | County | Koochiching |
| 171 | WMA | Roseau |
| 658 | CNF | Itasca |
| 734 | County | Hubbard |
| 335 | BWCA | Lake |
| 5584 | County | Jackson |
| 166 | County | Cass |
| 378 | WMA | Polk |
| 261 | MN Power | St. Louis |
| 975 | FOR | Koochiching |
| 180 | Private | Fillmore |
| 721 | SNF | St. Louis |
| 799 | FOR | Lake of the Woods |
| 851 | PAT | Douglas |
| 1223 | Private | Big Stone |
| 3290 | TNC | Wilkin |
| 1124 | PAT | Goodhue |
| 387 | WPA | Swift |
| 187 | SNF | Lake |
| 2088 | WMA | Le Sueur |
| 3305 | WPA | Renville |
| 270 | sna | Polk |
| 1003 | SNF | Cook |
| 1511 | nwr | Marshall |
| 1925 | PAT | Carlton |
| 278 | FOR | St. Louis |
| 99 | WPA | Douglas |
| 3107 | Private | Pope |
| 905 | County | Aitkin |
| 956 | Private | Murray |
| 14 | Private | Norman |
| 575 | FOR | Koochiching |
| 324 | FOR | St. Louis |
| 277 | FOR | Pine |
| 2300 | TNC | Lincoln |
| 9524 | FOR | Olmsted |
| 5480 | ama | Faribault |
| 230 | County | Crow Wing |
| 417 | County | Lake |
| 1586 | County | St. Louis |
| 82 | CNF | Cass |
| 704 | Private | Pipestone |
| 1652 | Private | Houston |
| 571 | SNF | Cook |
| 2051 | Private | Kandiyohi |
| 421 | FOR | Morrison |
| 155 | WMA | Pennington |
| 49 | BWCA | Lake |
| 1935 | FOR | Koochiching |
| 8456 | Private | Dodge |
| 429 | County | Aitkin |
| 1574 | County | Hubbard |
| 8124 | WMA | Pipestone |
| 305 | SNF | Lake |
| 1689 | WMA | Chisago |
| 951 | WMA | Marshall |
| 1187 | Private | Pope |
| 650 | County | Hubbard |
| 6925 | sna | Hennepin |
| 1499 | Private | Marshall |
| 949 | PAT | Pine |
| 659 | WMA | Douglas |
| 482 | SNF | St. Louis |
| 625 | SNF | Lake |
| 223 | FOR | Koochiching |
| 198 | FOR | St. Louis |
| 893 | County | St. Louis |
| 2730 | TNC | Clay |
| 2840 | sna | Rice |
| 1041 | County | St. Louis |
| 2068 | sna | Houston |
| 239 | FOR | Koochiching |
| 36 | WMA | Olmsted |
| 4340 | Private | Dodge |
| 1365 | County | Pine |
| 38 | FOR | Hubbard |
| 1591 | WMA | Marshall |
| 136 | WMA | Dakota |
| 1085 | County | Carlton |
| 2509 | County | Washington |
| 2768 | WMA | Cottonwood |
| 1192 | WMA | Blue Earth |
| 2 | FOR | Aitkin |
| 352 | Private | Murray |
| 898 | WMA | Itasca |
| 1246 | County | Beltrami |
| 427 | sna | Kittson |
| 79 | BWCA | Lake |
| 1544 | PAT | Steele |
| 646 | County | Itasca |
| 111 | PAT | Beltrami |
| 1479 | nwr | Otter Tail |
| 1747 | WPA | Stevens |
| 7565 | city | Hennepin |
| 1070 | County | Clearwater |
| 773 | County | St. Louis |
| 1250 | County | Beltrami |
| 3252 | FOR | Fillmore |
| 110 | WPA | Polk |
| 2812 | Private | Pipestone |
| 122 | Private | Polk |
| 1434 | WPA | Otter Tail |
| 536 | WMA | Rice |
| 262 | meriwether | Koochiching |
| 921 | WMA | Kanabec |
| 456 | Private | Goodhue |
| 978 | County | Hubbard |
| 1786 | sna | Norman |
| 685 | County | Itasca |
| 210 | FOR | Cass |
| 57 | WMA | Wright |
| 1133 | WMA | Aitkin |
| 22 | FOR | St. Louis |
| 416 | Private | Redwood |
| 6176 | sna | Jackson |
| 546 | CNF | Cass |
| 1514 | WMA | Clay |
| 637 | FOR | St. Louis |
| 226 | County | Beltrami |
| 358 | County | Cass |
| 302 | Private | Polk |
| 568 | WMA | Martin |
| 706 | CNF | Itasca |
| 169 | public wat | Meeker |
| 609 | SNF | St. Louis |
| 877 | CNF | Cass |
| 481 | SNF | Lake |
| 139 | WMA | Marshall |
| 1581 | Private | Chisago |
| 929 | SNF | Cook |
| 109 | FOR | Aitkin |
| 1457 | SNF | Cook |
| 212 | County | Olmsted |
| 69 | FOR | St. Louis |
| 63 | FOR | Koochiching |
| 934 | County | Crow Wing |
| 1706 | nwr | Clay |
| 5004 | Private | Blue Earth |
| 2010 | sna | Clay |
| 2057 | County | Aitkin |
| 2282 | WPA | Becker |
| 955 | SNF | St. Louis |
| 763 | SNF | St. Louis |
| 470 | CNF | Cass |
| 450 | CNF | Itasca |
| 406 | WMA | Cass |
| 4211 | WMA | Lac qui Parle |
| 2567 | sna | Big Stone |
| 400 | Private | Jackson |
| 486 | FOR | Cass |
| 1488 | Private | Jackson |
| 2015 | FOR | Koochiching |
| 3379 | WPA | Otter Tail |
| 55 | Private | Marshall |
| 3301 | FOR | Crow Wing |
| 833 | SNF | Lake |
| 284 | Private | Blue Earth |
| 1820 | WMA | Le Sueur |
| 1140 | Private | Fillmore |
| 1417 | PAT | Mille Lacs |
| 636 | Private | Lincoln |
| 693 | sna | Benton |
| 664 | Private | Carver |
| 85 | County | Pine |
| 4061 | PAT | Chisago |
| 458 | County | Becker |
| 4210 | Private | Waseca |
| 1271 | WMA | Marshall |
| 941 | County | Aitkin |
| 5224 | WMA | Faribault |
| 17 | County | St. Louis |
| 413 | Private | Isanti |
| 33 | PAT | St. Louis |
| 133 | FOR | St. Louis |
| 495 | County | Koochiching |
| 2355 | WPA | Otter Tail |
| 246 | WMA | Becker |
| 3584 | nwr | Rock |
| 11 | FOR | Roseau |
| 338 | FOR | Itasca |
| 1091 | WPA | Pope |
| 113 | Private | Lake |
| 66 | WMA | Aitkin |
| 257 | PAT | Cook |
| 548 | Private | Wabasha |
| 1325 | university | Isanti |
| 423 | FOR | Beltrami |
| 765 | County | St. Louis |
| 1805 | Private | Hennepin |
| 242 | WMA | Itasca |
| 1242 | TNC | Wilkin |
| 1044 | Private | Houston |
| 709 | WMA | Pine |
| 545 | County | St. Louis |
| 2399 | FOR | Lake of the Woods |
| 726 | FOR | Cass |
| 1121 | SNF | Lake |
| 46 | FOR | Clearwater |
| 1442 | CNF | Beltrami |
| 3128 | WMA | Martin |
| 5252 | FOR | Lake of the Woods |
| 434 | FOR | Itasca |
| 159 | FOR | Lake of the Woods |
| 478 | County | Hubbard |
| 1856 | Private | Renville |
| 701 | FOR | Aitkin |
| 466 | FOR | Hubbard |
| 1062 | FOR | Hubbard |
| 494 | Private | Yellow Medicine |
| 731 | Private | Pennington |
| 3587 | Private | Kandiyohi |
| 2371 | WMA | Swift |
| 983 | WMA | Roseau |
| 947 | nwr | Lac qui Parle |
| 1167 | FOR | Koochiching |
| 2144 | WMA | Lyon |
| 591 | SNF | St. Louis |
| 3513 | TNC | McLeod |
| 480 | sna | Brown |
| 401 | SNF | St. Louis |
| 443 | SNF | St. Louis |
| 542 | Private | Mahnomen |
| 1352 | PAT | Rice |
| 847 | FOR | Koochiching |
| 318 | PAT | Chippewa |
| 1562 | PAT | Otter Tail |
| 3652 | WMA | Lake of the Woods |
| 145 | SNF | St. Louis |
| 3888 | Private | Brown |
| 255 | FOR | Koochiching |
| 1161 | FOR | Mille Lacs |
| 2752 | Private | Pipestone |
| 50201 | nwr | Becker |
| 267 | WMA | Lake of the Woods |
| 5132 | PAT | Freeborn |
| 498 | CNF | Itasca |
| 733 | WMA | Anoka |
| 383 | FOR | Koochiching |
| 94 | WMA | Mahnomen |
| 397 | County | Carver |
| 1626 | PAT | Otter Tail |
| 862 | County | Becker |
| 390 | County | St. Louis |
| 273 | County | St. Louis |
| 202 | County | Becker |
| 786 | CNF | Cass |
| 523 | WMA | Roseau |
| 1229 | County | Ramsey |
| 108 | WMA | Brown |
| 550 | FOR | Wadena |
| 497 | County | St. Louis |
| 1411 | WMA | Swift |
| 578 | WMA | Aitkin |
| 177 | SNF | Cook |
| 1988 | Private | Winona |
| 3411 | Private | Otter Tail |
| 753 | County | St. Louis |
| 518 | CNF | Itasca |
| 804 | FOR | Wabasha |
| 50202 | nwr | Becker |
| 820 | Private | Fillmore |
| 2074 | FOR | Becker |
| 7689 | WMA | Kanabec |
| 2951 | Private | Traverse |
| 321 | County | Lake |
| 1137 | County | Lake |
| 514 | County | Aitkin |
| 146 | CNF | Cass |
| 141 | city | Hennepin |
| 612 | Private | Goodhue |
| 3220 | sna | Wabasha |
| 2306 | County | Aitkin |
| 3293 | County | Anoka |
| 3357 | County | Dakota |
| 418 | CNF | Beltrami |
| 1210 | nwr | Polk |
| 678 | FOR | Cass |
| 511 | FOR | Koochiching |
| 939 | WMA | Kittson |
| 2269 | PAT | Washington |
| 3688 | WMA | Faribault |
| 5405 | Private | Dakota |
| 515 | WPA | Kandiyohi |
| 2598 | County | Hubbard |
| 541 | nwr | Sherburne |
| 565 | WMA | Morrison |
| 572 | wmd | Yellow Medicine |
| 1146 | sna | Polk |
| 2841 | WMA | Isanti |
| 689 | SNF | Cook |
| 1249 | SNF | Cook |
| 1026 | FOR | Aitkin |
| 521 | Private | Kanabec |
| 2004 | WMA | Winona |
| 65 | WMA | Cook |
| 926 | County | Clearwater |
| 433 | SNF | Cook |
| 90 | Private | Otter Tail |
| 70 | FOR | Itasca |
| 18 | FOR | Koochiching |
| 558 | sna | Polk |
| 1090 | FOR | Aitkin |
| 2191 | FOR | Koochiching |
| 214 | CNF | Cass |
| 897 | FOR | Lake |
| 4950 | FOR | Wadena |
| 3123 | Private | Otter Tail |
| 990 | FOR | Clearwater |
| 1079 | WMA | Roseau |
| 957 | County | Aitkin |
| 45 | PAT | Chisago |
| 31 | WMA | Lake of the Woods |
| 2425 | Private | Stearns |
| 186 | WMA | Polk |
| 513 | FOR | Cook |
| 850 | FOR | Cass |
| 5917 | FOR | Sherburne |
| 487 | WMA | Marshall |
| 769 | SNF | Cook |
| 2163 | WPA | Lac qui Parle |
| 1186 | CNF | Beltrami |
| 1253 | Private | Morrison |
| 867 | WPA | Pope |
| 30 | WPA | Mahnomen |
| 683 | WMA | Kittson |
| 986 | WPA | Wilkin |
| 172 | Private | Sibley |
| 235 | TNC | Kittson |
| 2748 | Private | Pipestone |
| 895 | FOR | St. Louis |
| 225 | SNF | Cook |
| 789 | County | Pine |
| 801 | SNF | Lake |
| 381 | County | Carlton |
| 852 | Private | Wabasha |
| 661 | FOR | Todd |
| 614 | CNF | Cass |
| 1314 | County | Hubbard |
| 976 | Private | Jackson |
| 1111 | Private | Wilkin |
| 50 | County | Itasca |
| 5512 | WMA | Dakota |
| 48001 | Private | Redwood |
| 584 | Private | Goodhue |
| 1698 | County | Beltrami |
| 405 | Camp Ripely | Morrison |
| 4556 | County | Nicollet |
| 1624 | WMA | Waseca |
| 341 | Private | Pine |
| 1666 | FOR | Itasca |
| 747 | WMA | Kittson |
| 5604 | PAT | Fillmore |
| 913 | SNF | St. Louis |
| 2423 | WMA | Marshall |
| 48002 | Private | Redwood |
| 260 | Meriwether | Koochiching |
| 419 | Private | Pope |
| 3498 | Private | Clay |
| 7958 | FOR | Wadena |
| 99000 | WMA | Freeborn |
| 99001 | WMA | Pope |
Current proportions of EMN monitoring plots
Proportion of plots by system group
| Plant Community System | Number of Plots | |
|---|---|---|
| Forested wetlands (15%) | Acid Peatland (AP) | 15 |
| Floodplain Forest (FF) | 12 | |
| Forested Peatland (FP) | 20 | |
| Wet Forest (WF) | 12 | |
| Open wetlands (27%) | Acid Peatland (AP) | 12 |
| Forested Peatland (FPn73) | 2 | |
| Marsh (MR) | 4 | |
| Open Pealand (OP) | 29 | |
| Wet Meadow (WM) | 41 | |
| Wet Prairies (WP) | 18 | |
| Upland forests (45%) | Fire Dependent Forest (FD) | 52 |
| Mesic Hardwood Forest (MH) | 122 | |
| Upland prairies (12%) | Upland Prairie (UP) | 48 |
Proportion of plots by land ownership
| Land Manager(s) | Number of Plots | |
|---|---|---|
| Federal (20%) | Boundary Waters Wilderness | 3 |
| Chippewa National Forest | 17 | |
| National Wildlife Refuge | 9 | |
| Superior National Forest | 32 | |
| Wetland Management District | 1 | |
| Waterfowl Production Area | 16 | |
| Local (17%) | City | 3 |
| County (Parks and Tax Forfeit) | 64 | |
| Other (3%) | Private Companies, Universities, The Nature Conservancy, and others | 12 |
| Private (18%) | Privately Owned by Individuals | 69 |
| State (42%) (DNR Managed) |
Aquatic Mangement Area | 1 |
| State Forest | 67 | |
| Parks and Trails | 18 | |
| Scientific and Natural Area | 14 | |
| Wildlife Management Area | 61 |
Objective: Track effects of browsing on vegetation
Heavy browsing by herbivores such as white-tailed deer can negatively impact forest vegetation. Deer eat tree seedlings and saplings and can suppress regeneration of the species that would otherwise form the future tree canopy. This can lead to shifts in forest composition and structure. Over-browsing of forests can also lead to reduced deer populations long-term and reduce other ecosystem benefits provided by healthy forests.
- EMN evaluates the effect of deer browsing on woody vegetation less than two meters from the forest floor.
- Browse pressure is measured as a ratio of browsed to total branches of all woody species in the plot.
- EMN forest plots in southern Minnesota appear to be experiencing consistently higher browse pressure than plots in northern Minnesota.
Figure 4. Levels of browse pressure within individual EMN plots (ratio of browsed:total branches). Larger dot size represents higher browse pressure by deer.
| Plot ID | Plot Percent Browsed | Land Manager | NPC | System Groups | |
|---|---|---|---|---|---|
| 11 | 30.1 | for | FPn63 | wetland forests | |
| 18 | 58.3 | for | MHn44 | upland forests | |
| 22 | 2.9 | for | APn80 | wetland forests | |
| 33 | 38.7 | pat | FDn43 | upland forests | |
| 36 | 17.5 | wma | MHs38 | upland forests | |
| 38 | 33 | for | FDc34 | upland forests | |
| 38 | 33 | for | FDc34 | upland forests | |
| 45 | 13.5 | pat | MHc36 | upland forests | |
| 49 | 0 | bwca | FDn43 | upland forests | |
| 50 | 37.6 | county | MHn44 | upland forests | |
| 57 | 34.7 | wma | MHc36 | upland forests | |
| 59 | 67.3 | snf | FDn32 | upland forests | |
| 63 | 28.6 | for | MHn44 | upland forests | |
| 65 | 24.8 | wma | FPn63 | wetland forests | |
| 69 | 42.7 | for | MHn44 | upland forests | |
| 79 | 12.6 | bwca | FDn22 | upland forests | |
| 82 | 26.5 | cnf | FDc34 | upland forests | |
| 85 | 30.9 | county | MHc26 | upland forests | |
| 90 | 38.3 | private | FDs36 | upland forests | |
| 109 | 5.5 | for | APn81 | wetland forests | |
| 110 | 25 | wpa | MHc36 | upland forests | |
| 113 | 48.7 | private | WFn53 | wetland forests | |
| 127 | 30.7 | snf | FDn43 | upland forests | |
| 127 | 30.7 | snf | FDn43 | upland forests | |
| 133 | 48.4 | for | MHn44 | upland forests | |
| 136 | 55.9 | wma | MHs38 | upland forests | |
| 139 | 28.8 | wma | WFn55 | wetland forests | |
| 141 | 58.5 | city | MHs38 | upland forests | |
| 145 | 3.3 | snf | APn81 | wetland forests | |
| 146 | 39.7 | cnf | MHn44 | upland forests | |
| 172 | 27.6 | private | MHs39 | upland forests | |
| 177 | 42.9 | snf | FDn43 | upland forests | |
| 180 | 31.2 | private | MHs37 | upland forests | |
| 187 | 16.2 | snf | FDn43 | upland forests | |
| 198 | 20.8 | for | MHn35 | upland forests | |
| 202 | 45.7 | county | FDc24 | upland forests | |
| 212 | 43.4 | county | MHs37 | upland forests | |
| 212 | 43.4 | county | MHs37 | upland forests | |
| 214 | 37.5 | cnf | MHc26 | upland forests | |
| 225 | 48.4 | snf | MHn45 | upland forests | |
| 226 | 52.3 | county | MHc26 | upland forests | |
| 230 | 77.4 | county | WFn55 | wetland forests | |
| 242 | 31.2 | wma | FDn33 | upland forests | |
| 255 | 0 | for | APn80 | wetland forests | |
| 257 | 39.1 | pat | MHn45 | upland forests | |
| 260 | 31.4 | meriwether | FFn57 | wetland forests | |
| 261 | 27.3 | MN Power | FDn43 | upland forests | |
| 262 | 44 | meriwether | FFn57 | wetland forests | |
| 267 | 2.6 | wma | FPn71 | wetland forests | |
| 273 | 31 | county | MHn44 | upland forests | |
| 277 | 73.4 | for | MHc36 | upland forests | |
| 278 | 3.3 | for | APn81 | wetland forests | |
| 284 | 56.3 | private | MHs38 | upland forests | |
| 305 | 2.7 | snf | APn80 | wetland forests | |
| 319 | 37.2 | county | FDn43 | upland forests | |
| 321 | 57.1 | county | FDn43 | upland forests | |
| 324 | 34.1 | for | MHn44 | upland forests | |
| 335 | 23.6 | bwca | FDn32 | upland forests | |
| 338 | 0 | for | APn80 | wetland forests | |
| 341 | 45.5 | private | MHc26 | upland forests | |
| 383 | 5.7 | for | WFn74 | wetland forests | |
| 401 | 20.3 | snf | FPn63 | wetland forests | |
| 405 | 68.4 | camp ripely | MHc26 | upland forests | |
| 406 | 39.4 | wma | MHc26 | upland forests | |
| 413 | 55 | private | FDs37 | upland forests | |
| 417 | 37.7 | county | MHn47 | upland forests | |
| 422 | 43.8 | cnf | FDn33 | upland forests | |
| 422 | 43.8 | cnf | MHn44 | upland forests | |
| 429 | 37.7 | county | FFn57 | wetland forests | |
| 433 | 10.9 | snf | FDn43 | upland forests | |
| 434 | 29.2 | for | FDn43 | upland forests | |
| 443 | 16.3 | snf | FDn43 | upland forests | |
| 450 | 24.1 | cnf | FPn63 | wetland forests | |
| 456 | 59.6 | private | MHs38 | upland forests | |
| 458 | 48.6 | county | MHc37 | upland forests | |
| 466 | 37 | for | MHc26 | upland forests | |
| 470 | 51.6 | cnf | MHc26 | upland forests | |
| 473 | 46.5 | private | MHc36 | upland forests | |
| 478 | 40.4 | county | MHc26 | upland forests | |
| 481 | 29 | snf | MHn45 | upland forests | |
| 482 | 25.6 | snf | MHn44 | upland forests | |
| 486 | 44.6 | for | MHn35 | upland forests | |
| 487 | 31.4 | wma | FFn57 | wetland forests | |
| 495 | 23.3 | county | MHn44 | upland forests | |
| 497 | 40.6 | county | FDn43 | upland forests | |
| 498 | 45.4 | cnf | MHn35 | upland forests | |
| 511 | 0 | for | APn80 | wetland forests | |
| 513 | 0 | for | FPn63 | wetland forests | |
| 514 | 41.2 | county | MHn35 | upland forests | |
| 518 | 43.1 | cnf | WFn64 | wetland forests | |
| 521 | 25.4 | private | MHn44 | upland forests | |
| 542 | 55.5 | private | MHc37 | upland forests | |
| 545 | 27 | county | FDn43 | upland forests | |
| 546 | 43 | cnf | MHc26 | upland forests | |
| 548 | 50.2 | private | MHc37 | upland forests | |
| 558 | 23.3 | sna | FPw63 | wetland forests | |
| 561 | 8 | snf | FDn32 | upland forests | |
| 571 | 8.3 | snf | FDn43 | upland forests | |
| 575 | 0 | for | APn80 | wetland forests | |
| 584 | 58.4 | private | MHs38 | upland forests | |
| 585 | 29.7 | private | MHc36 | upland forests | |
| 591 | 48.7 | snf | FDn32 | upland forests | |
| 609 | 51.2 | snf | FDn43 | upland forests | |
| 612 | 44.3 | private | MHs37 | upland forests | |
| 614 | 25.4 | cnf | FDc34 | upland forests | |
| 637 | 70.4 | for | FFn57 | wetland forests | |
| 646 | 68.8 | county | MHn35 | upland forests | |
| 650 | 52.2 | county | FDc34 | upland forests | |
| 661 | 29.3 | for | FDc34 | upland forests | |
| 673 | 20.5 | snf | FDn43 | upland forests | |
| 685 | 55.2 | county | MHn35 | upland forests | |
| 689 | 39.7 | snf | FDn43 | upland forests | |
| 693 | 53.8 | sna | FDs37 | upland forests | |
| 701 | 48.3 | for | MHn35 | upland forests | |
| 706 | 53.8 | cnf | MHn35 | upland forests | |
| 713 | 55.6 | wma | MHc36 | upland forests | |
| 721 | 32.6 | snf | FDn32 | upland forests | |
| 726 | 26.5 | for | MHc26 | upland forests | |
| 734 | 23.8 | county | MHc26 | upland forests | |
| 753 | 40.7 | county | MHn44 | upland forests | |
| 763 | 18.1 | snf | FDn32 | upland forests | |
| 765 | 21.4 | county | WFn55 | wetland forests | |
| 769 | 23.5 | snf | FDn43 | upland forests | |
| 773 | 25.5 | county | MHn44 | upland forests | |
| 786 | 6.4 | cnf | FPn82 | wetland forests | |
| 789 | 33.1 | county | MHc26 | upland forests | |
| 799 | 4.2 | for | FPn71 | wetland forests | |
| 801 | 16.7 | snf | MHn45 | upland forests | |
| 804 | 41.2 | for | MHs49 | upland forests | |
| 820 | 52.7 | private | MHs37 | upland forests | |
| 833 | 17.9 | snf | FDn32 | upland forests | |
| 847 | 10.3 | for | FPn63 | wetland forests | |
| 850 | 1.9 | for | FPn81 | wetland forests | |
| 852 | 31.7 | private | MHs39 | upland forests | |
| 862 | 17.1 | county | MHn46 | upland forests | |
| 870 | 48.9 | county | MHn35 | upland forests | |
| 877 | 44.3 | cnf | MHn35 | upland forests | |
| 893 | 1.2 | county | APn80 | wetland forests | |
| 895 | 39.8 | for | FDn33 | upland forests | |
| 897 | 0 | for | WFn53 | wetland forests | |
| 913 | 0 | snf | APn80 | wetland forests | |
| 926 | 33.6 | county | MHc26 | upland forests | |
| 929 | 29.6 | snf | FDn43 | upland forests | |
| 941 | 23.3 | county | MHn44 | upland forests | |
| 949 | 32.8 | pat | MHc26 | upland forests | |
| 955 | 19.7 | snf | FDn43 | upland forests | |
| 975 | 44.5 | for | MHn35 | upland forests | |
| 990 | 22.2 | for | MHn35 | upland forests | |
| 994 | 39.2 | snf | MHn44 | upland forests | |
| 1003 | 46.1 | snf | FDn43 | upland forests | |
| 1015 | 4 | for | FPn81 | wetland forests | |
| 1044 | 45.4 | private | MHs37 | upland forests | |
| 1062 | 13.6 | for | MHc26 | upland forests | |
| 1070 | 54.8 | county | MHc37 | upland forests | |
| 1074 | 10.8 | county | FPn63 | wetland forests | |
| 1079 | 28.8 | wma | FPn63 | wetland forests | |
| 1085 | 14.8 | county | MHn47 | upland forests | |
| 1090 | 13.3 | for | MHc36 | upland forests | |
| 1111 | 28.6 | private | FFn57 | wetland forests | |
| 1121 | 3.8 | snf | FDn32 | upland forests | |
| 1124 | 63.3 | pat | FFs68 | wetland forests | |
| 1133 | 23.9 | wma | FPn63 | wetland forests | |
| 1137 | 26 | county | FDn43 | upland forests | |
| 1140 | 43.9 | private | MHs38 | upland forests | |
| 1161 | 38.5 | for | MHc36 | upland forests | |
| 1167 | 9.5 | for | FPn63 | wetland forests | |
| 1172 | 54.3 | private | MHs37 | upland forests | |
| 1186 | 19.7 | cnf | WFn53 | wetland forests | |
| 1192 | 29 | wma | FFs59 | wetland forests | |
| 1236 | 66.7 | wma | MHs39 | upland forests | |
| 1249 | 40.5 | snf | MHn45 | upland forests | |
| 1250 | 26.1 | county | MHn35 | upland forests | |
| 1253 | 61.5 | private | FDs37 | upland forests | |
| 1314 | 0.7 | county | FPn82 | wetland forests | |
| 1325 | 34.8 | university | FDs37 | upland forests | |
| 1352 | 49.4 | pat | MHs38 | upland forests | |
| 1365 | 53.3 | county | WFn55 | wetland forests | |
| 1417 | 40 | pat | MHc36 | upland forests | |
| 1442 | 16.7 | cnf | MHn47 | upland forests | |
| 1457 | 0.8 | snf | APn81 | wetland forests | |
| 1544 | 55 | pat | MHs49 | upland forests | |
| 1574 | 20.5 | county | FDc34 | upland forests | |
| 1581 | 36.7 | private | MHc26 | upland forests | |
| 1626 | 49.2 | pat | MHc37 | upland forests | |
| 1652 | 64.4 | private | MHs37 | upland forests | |
| 1698 | 38.5 | county | MHn35 | upland forests | |
| 1869 | 66 | county | MHs37 | upland forests | |
| 1925 | 51.4 | pat | MHn35 | upland forests | |
| 1935 | 5.6 | for | FPn82 | wetland forests | |
| 1967 | 18.5 | for | WFn55 | wetland forests | |
| 1988 | 65.6 | private | MHs37 | upland forests | |
| 2004 | 13.1 | wma | MHs38 | upland forests | |
| 2015 | 7.1 | for | APn81 | wetland forests | |
| 2051 | 48.1 | private | MHs38 | upland forests | |
| 2057 | 30.5 | county | WFn55 | wetland forests | |
| 2074 | 47.6 | for | MHn35 | upland forests | |
| 2269 | 44.8 | pat | FDs37 | upland forests | |
| 2306 | 32.8 | county | MHn35 | upland forests | |
| 2423 | 39.3 | wma | WFw54 | wetland forests | |
| 2425 | 34.9 | private | FDs37 | upland forests | |
| 2509 | 47.1 | county | FDs38 | upland forests | |
| 2598 | 5 | county | FPn81 | wetland forests | |
| 2653 | 30 | county | MHs38 | upland forests | |
| 2840 | 58.6 | sna | MHs39 | upland forests | |
| 2841 | 28.2 | wma | MHs38 | upland forests | |
| 3220 | 56.6 | sna | MHs37 | upland forests | |
| 3252 | 55.6 | for | MHs38 | upland forests | |
| 3301 | 42.7 | for | MHc26 | upland forests | |
| 3357 | 51.7 | county | MHs38 | upland forests | |
| 3379 | 20.1 | wpa | FDs37 | upland forests | |
| 3411 | 23 | private | FDs37 | upland forests | |
| 3414 | 19.7 | for | MHc26 | upland forests | |
| 3513 | 71.3 | tnc | FFs59 | wetland forests | |
| 3604 | 32.3 | for | MHs37 | upland forests | |
| 3928 | 44.1 | county | MHs38 | upland forests | |
| 4061 | 59.2 | pat | MHc36 | upland forests | |
| 4210 | 70.2 | private | MHs39 | upland forests | |
| 4340 | 62.4 | private | MHs37 | upland forests | |
| 4436 | 51 | private | MHs38 | upland forests | |
| 4556 | 55.6 | county | MHs38 | upland forests | |
| 4968 | 33.8 | private | FFs68 | wetland forests | |
| 5004 | 29.6 | private | FFs59 | wetland forests | |
| 5132 | 52.4 | pat | MHs39 | upland forests | |
| 5405 | 53.8 | private | MHs37 | upland forests | |
| 5480 | 31.1 | ama | MHs38 | upland forests | |
| 5512 | 44.4 | wma | MHs37 | upland forests | |
| 5584 | 32.3 | county | FFs59 | wetland forests | |
| 5604 | 3.8 | pat | MHs38 | upland forests | |
| 5917 | 50.6 | for | FDs37 | upland forests | |
| 6925 | 43.6 | sna | MHs38 | upland forests | |
| 7689 | 43.5 | wma | MHc26 | upland forests | |
| 7958 | 48.9 | for | FDc23 | upland forests | |
| 8456 | 63.8 | private | MHs38 | upland forests | |
| 9524 | 46.5 | for | MHs39 | upland forests | |
| 9524 | 46.5 | for | MHs39 | upland forests | |
| 50201 | 58.3 | nwr | FPn82 | wetland forests | |
| 99002 | 50.4 | for | MHs38 | upland forests | |
| 99003 | 35.2 | for | MHs38 | upland forests | |
| 99004 | 34.2 | for | MHs38 | upland forests | |
Relative browse pressure on canopy tree species for all forested EMN plots
Relative Browse Pressure (RBP) is the ratio of browse pressure on a single woody species in a plot (such as sugar maple) to the total browse pressure on all woody species in the plot. A RBP value greater than 1 indicates higher browse pressure on that species relative to the collective pressure of all other woody species in the plot.
| Species | Minimum | First quartile | Median | Third quartile | Maximum |
|---|---|---|---|---|---|
| Big-toothed aspen Populus grandidentata |
1.1 | 1.7 | 1.8 | 2 | 3.1 |
| Blue beech Carpinus caroliniana |
0.3 | 1.0 | 1.3 | 1.75 | 2.5 |
| Quaking aspen Populus tremuloides |
0 | 0.9 | 1.2 | 1.7 | 3.8 |
| Red elm Ulmus rubra |
0 | 0.8 | 1.1 | 1.5 | 2.9 |
| Sugar maple Acer saccharum |
0 | 0.6 | 1.1 | 1.4 | 2.4 |
| Black ash Fraxinus nigra |
0 | 0.6 | 1 | 1.4 | 2 |
| Green ash Fraxinus pennsylvanica |
0 | 0.7 | 1 | 1.3 | 2.6 |
| Hackberry Celtis occidentalis |
0 | 0.8 | 1 | 1.4 | 1.9 |
| Box elder Acer negundo |
0 | 0.5 | 0.9 | 1.2 | 3.5 |
| Bur oak Quercus macrocarpa |
0 | 0.6 | 0.9 | 1.3 | 1.7 |
| Paper birch Betula papyrifera |
0 | 0.4 | 0.9 | 1.2 | 1.5 |
| Ironwood Ostrya virginiana |
0 | 0.4 | 0.9 | 1.2 | 2.6 |
| White ash Fraxinus americana |
0.6 | 0.6 | 0.9 | 1.1 | 1.5 |
| Basswood Tilia americana |
0 | 0.5 | 0.8 | 1.3 | 1.9 |
| American elm Ulmus americana |
0 | 0.5 | 0.7 | 1.1 | 2.8 |
| Bitternut hickory Carya cordiformis |
0 | 0.2 | 0.6 | 1 | 1.8 |
| Northern red oak Quercus rubra |
0 | 0.1 | 0.6 | 1.0 | 2.2 |
| Red maple Acer rubrum |
0 | 0.4 | 0.6 | 1.1 | 3 |
| White pine Pinus strobus |
0.3 | 0.5 | 0.6 | 0.6 | 0.7 |
| Balsam fir Abies balsamea |
0 | 0 | 0.2 | 0.6 | 1.2 |
Relative browse pressure on woody understory species for all forested EMN plots
| Species | Minimum | First quartile | Median | Third quartile | Maximum |
|---|---|---|---|---|---|
| Round-leaved dogwood Cornus rugosa |
1.7 | 1.7 | 2 | 2.2 | 2.7 |
| Downy arrowwood Viburnum rafinesquianum |
0 | 0.9 | 1.5 | 1.7 | 2.3 |
| Chokecherry Prunus virginiana |
0 | 0.9 | 1.5 | 1.7 | 3 |
| Gray dogwood Cornus racemosa |
0.8 | 1.3 | 1.5 | 2 | 2.5 |
| Missouri gooseberry Ribes missouriense |
0 | 1.2 | 1.5 | 1.8 | 2.9 |
| Mountain maple Acer spicatum |
0.5 | 1.1 | 1.5 | 1.6 | 3.9 |
| American hazelnut Corylus americana |
0.4 | 1.0 | 1.4 | 1.6 | 2.2 |
| Common buckthorn Rhamnus cathartica |
0 | 1.3 | 1.4 | 1.7 | 2.3 |
| Fly honeysuckle Lonicera canadensis |
0 | 0.9 | 1.4 | 1.8 | 3 |
| Beaked hazelnut Corylus cornuta |
0 | 1 | 1.4 | 1.7 | 2.8 |
| Red-berried elder Sambucus racemosa |
0.4 | 0.7 | 1.4 | 2.0 | 3.8 |
| Nannyberry Viburnum lentago |
0.8 | 1.1 | 1.3 | 1.9 | 3.1 |
| Pagoda dogwood Cornus alternifolia |
0.6 | 0.8 | 1.2 | 1.6 | 2.2 |
| Prickly gooseberry Ribes cynosbati |
0 | 0.9 | 1.2 | 1.6 | 3.2 |
| Juneberry Amelanchier sanguinea/spicata |
0 | 0.8 | 1.1 | 1.7 | 2.5 |
| Juneberry Amelanchier laevis/interior |
0 | 0.6 | 1.0 | 1.4 | 2.6 |
| Bush Honeysuckle Diervilla lonicera |
0 | 0.4 | 1.0 | 1.3 | 2.1 |
| Black cherry Prunus serotina |
0 | 0.6 | 0.9 | 1.4 | 2.7 |
| Morrow's honeysuckle Lonicera morrowii |
0 | 0.4 | 0.9 | 1.4 | 1.5 |
| Prickly rose Rosa acicularis |
0 | 0.7 | 0.9 | 1.5 | 1.6 |
| Thimbleberry Rubus parviflorus |
0.5 | 0.6 | 0.7 | 1.05 | 1.8 |
| Velvet-leaved blueberry Vaccinium myrtilloides |
0 | 0.4 | 0.7 | 0.9 | 2.1 |
| Canada moonseed Menispermum canadense |
0.4 | 0.7 | 0.8 | 1.0 | 1.3 |
| Lowbush blueberry Vaccinium angustifolium |
0 | 0.2 | 0.5 | 0.8 | 2.3 |
| Prickly ash Zanthoxylum americanum |
0 | 0.3 | 0.5 | 1.1 | 1.6 |
| Wild grape Vitis riparia |
0 | 0.3 | 0.5 | 0.6 | 1.7 |
| Tall blackberry Rubus (Blackberry) |
0.3 | 0.4 | 0.5 | 0.7 | 0.8 |
| Wild red raspberry Rubus idaeus |
0 | 0 | 0.4 | 0.9 | 1.6 |
| Greenbrier Smilax tamnoides |
0 | 0.2 | 0.3 | 0.9 | 1.8 |
| Woodbine Parthenocissus vitacea |
0 | 0 | 0.3 | 0.4 | 1.1 |
| Black raspberry Rubus occidentalis |
0 | 0 | 0.2 | 0.3 | 0.9 |
| Eastern poison ivy Toxicodendron radicans |
0 | 0 | 0 | 0.1 | 0.3 |
| Leatherwood Dirca palustris |
0 | 0 | 0 | 0 | 1.8 |
| Snowberry Symphoricarpos albus |
0 | 0 | 0 | 0.3 | 1.8 |
| Western poison ivy Toxicodendron rydbergii |
0 | 0 | 0 | 0 | 0.4 |
Objective: Document status and trends in non-native invasive plant species
Initial Work and Observations
- Non-native species cover is the ratio between the sum of non-native species cover compared to total species cover in a plot.
- EMN plots installed in prairies have higher relative non-native species cover than plots installed in forests. This difference is likely driven by two invasive grasses, Kentucky bluegrass (Poa pratensis) and smooth brome (Bromus inermis), that occur largely in non-forested habitats.
- EMN plots installed in southern communities have higher relative non-native species cover than plots installed in northern communities.
Ratios of non-native species cover to total species cover in northern vs. southern floristic regions in four Ecological Systems
| Percent Non-native | |||||
|---|---|---|---|---|---|
| Ecological Systems | median | max | min | q25 | q75 |
| Northern Fire Dependent Forest (FDn) | 0.00 | 0.46 | 0.00 | 0.00 | 0.00 |
| Southern Fire Dependent Forest (SDn) | 3.61 | 26.89 | 0.00 | 2.00 | 6.98 |
| Northern Mesic Hardwood Forest (MHn) | 0.00 | 1.54 | 0.00 | 0.00 | 0.03 |
| Southern Mesic Hardwood Forest (SHn) | 1.35 | 64.58 | 0.00 | 0.22 | 13.37 |
| Northern Upland Prairie (Upn) | 16.86 | 43.44 | 5.14 | 12.33 | 29.33 |
| Southern Upland Prairie (Ups) | 29.40 | 85.54 | 0.00 | 13.52 | 53.11 |
| Northern Wet Prairie (WPn) | 8.88 | 28.96 | 1.77 | 3.93 | 13.70 |
| Southern Wet Prairie (WPs) | 11.96 | 42.30 | 1.60 | 4.17 | 31.20 |
Ratios of non-native species cover to total species cover in northern vs. southern floristic regions in four Ecological Systems. Overall, plots in the southern floristic regions of each system appear to have higher cover of non-native species compared to their northern counterparts. The prairie systems have noticeably larger invasive species cover than the forest systems.
Objective: Determine status and trends in volume of coarse woody debris
Coarse woody debris (CWD) is the large dead wood present in the forest. CWD includes both snags (standing dead trees) and fallen logs. CWD plays a major role in natural forest processes, including providing habitat (e.g., small mammals, invertebrates), cycling nutrients, and storing carbon.
Course woody debris volume in Minnesota forests. Larger dot size represents higher volume of CWD in a full hectare.
| Plot ID | Land Manager | m3/ha |
|---|---|---|
| 18 | Forestry | 21.87 |
| 33 | Parks and Trails | 64.16 |
| 36 | Wildlife Management Area | 62.58 |
| 38 | Forestry | 21.66 |
| 45 | Parks and Trails | 46.8 |
| 49 | BWCA | 170.04 |
| 50 | County | 31.53 |
| 57 | Wildlife Management Area | 92.15 |
| 59 | SNF | 61.23 |
| 63 | Forestry | 6.07 |
| 69 | Forestry | 9.89 |
| 79 | BWCA | 14.36 |
| 82 | CNF | 23.58 |
| 85 | County | 44.7 |
| 90 | Private | 16.33 |
| 110 | WPA | 42.51 |
| 127 | SNF | 25.06 |
| 133 | Forestry | 53.42 |
| 136 | Wildlife Mangement Area | 62.89 |
| 141 | City | 11 |
| 146 | CNF | 62.44 |
| 172 | Private | 9.61 |
| 177 | SNF | 59.84 |
| 180 | Private | 49.53 |
| 187 | SNF | 206.8 |
| 198 | Forestry | 40.84 |
| 202 | County | 16.85 |
| 212 | County | 33.61 |
| 214 | CNF | 32.87 |
| 225 | SNF | 44.17 |
| 226 | County | 148.88 |
| 242 | Wildlife Mangement Area | 32.42 |
| 257 | Parks and Trails | 24.45 |
| 261 | MN Power | 82.26 |
| 273 | County | 64.59 |
| 277 | Forestry | 42.22 |
| 284 | Private | 60.92 |
| 319 | County | 117.07 |
| 321 | County | 37.04 |
| 324 | Forestry | 61.04 |
| 335 | BWCA | 24.84 |
| 341 | Private | 61.56 |
| 405 | Camp Ripely | 81.24 |
| 406 | WMA | 98.16 |
| 413 | Private | 71.92 |
| 417 | County | 34.47 |
| 422 | CNF | 353.43 |
| 433 | SNF | 35.74 |
| 434 | Forestry | 6.13 |
| 443 | SNF | 22.69 |
| 456 | Private | 19.96 |
| 458 | County | 62.49 |
| 466 | Forestry | 33.13 |
| 470 | CNF | 46.21 |
| 473 | Private | 27.92 |
| 478 | County | 56.29 |
| 481 | SNF | 59.47 |
| 482 | SNF | 28.72 |
| 486 | Forestry | 53.93 |
| 495 | County | 30.77 |
| 497 | County | 29.67 |
| 498 | CNF | 197.2 |
| 514 | County | 23.45 |
| 521 | Private | 50.03 |
| 542 | Private | 14.95 |
| 545 | County | 55.25 |
| 546 | CNF | 48.35 |
| 548 | Private | 39.52 |
| 561 | SNF | 87.36 |
| 571 | SNF | 48.06 |
| 584 | Private | 65.84 |
| 585 | Private | 6.43 |
| 591 | SNF | 27.27 |
| 609 | SNF | 53.07 |
| 612 | Private | 62.82 |
| 614 | CNF | 24.14 |
| 646 | County | 37.25 |
| 650 | County | 143.38 |
| 661 | Forestry | 39.73 |
| 673 | SNF | 86.85 |
| 685 | County | 73.55 |
| 689 | SNF | 69.44 |
| 693 | SNA | 74.08 |
| 701 | Forestry | 39.58 |
| 706 | CNF | 58.15 |
| 713 | WMA | 44.16 |
| 721 | SNF | 96.77 |
| 726 | Forestry | 38.68 |
| 734 | County | 117.39 |
| 753 | County | 61.94 |
| 763 | SNF | 179.38 |
| 769 | SNF | 153.33 |
| 773 | County | 47.76 |
| 789 | County | 49.41 |
| 801 | SNF | 17.55 |
| 804 | Forestry | 46.52 |
| 820 | Private | 32.57 |
| 833 | SNF | 49.93 |
| 852 | Private | 57.66 |
| 862 | County | 189.12 |
| 870 | County | 68.85 |
| 877 | CNF | 68.38 |
| 895 | Forestry | 24.24 |
| 926 | County | 10.48 |
| 929 | SNF | 78.77 |
| 941 | County | 30.06 |
| 949 | Parks and Trails | 52.55 |
| 955 | SNF | 58.03 |
| 975 | Forestry | 54.6 |
| 990 | Forestry | 132.8 |
| 994 | SNF | 65.67 |
| 1003 | SNF | 46.83 |
| 1044 | Private | 33.21 |
| 1062 | Forestry | 10.34 |
| 1070 | County | 28.28 |
| 1085 | County | 16.87 |
| 1090 | Forestry | 262.55 |
| 1121 | SNF | 24.91 |
| 1137 | County | 78.24 |
| 1140 | Private | 41.77 |
| 1161 | Forestry | 10.46 |
| 1172 | Private | 17.07 |
| 1236 | WMA | 34.46 |
| 1249 | SNF | 47.81 |
| 1250 | County | 15.04 |
| 1253 | Private | 52.31 |
| 1325 | University | 126.5 |
| 1352 | Parks and Trails | 24.72 |
| 1417 | Parks and Trails | 47.5 |
| 1442 | CNF | 40.01 |
| 1544 | Parks and Trails | 118.76 |
| 1574 | County | 2.63 |
| 1581 | Private | 27.45 |
| 1626 | Parks and Trails | 66.58 |
| 1652 | Private | 50.3 |
| 1698 | County | 56.58 |
| 1869 | County | 24.25 |
| 1925 | Parks and Trails | 35.36 |
| 1988 | Private | 24.39 |
| 2004 | WMA | 40.18 |
| 2051 | Private | 134.96 |
| 2074 | Forestry | 138.46 |
| 2269 | Parks and Trails | 20.62 |
| 2306 | County | 30.95 |
| 2425 | Private | 93.94 |
| 2509 | County | 11.32 |
| 2653 | County | 56.35 |
| 2840 | SNA | 69.67 |
| 2841 | Wildlife Management Area | 32.6 |
| 3220 | SNA | 52.88 |
| 3252 | Forestry | 48.9 |
| 3301 | Forestry | 24.54 |
| 3357 | County | 13.9 |
| 3379 | WPA | 96.78 |
| 3411 | Private | 36.12 |
| 3414 | Forestry | 15.78 |
| 3604 | Forestry | 9.58 |
| 3928 | County | 53.13 |
| 4061 | Parks and Trails | 48.08 |
| 4210 | Private | 77.32 |
| 4340 | Private | 10.26 |
| 4436 | Private | 49.01 |
| 4556 | County | 102.74 |
| 5132 | Parks and Trails | 45.38 |
| 5405 | Private | 35.42 |
| 5480 | AMA | 19.47 |
| 5512 | Wildlife Management Area | 131.04 |
| 5604 | Parks and Trails | 22.83 |
| 5917 | Forestry | 19.5 |
| 6925 | SNA | 47.18 |
| 7689 | Wildlife Management Area | 39.29 |
| 7958 | Forestry | 13.59 |
| 8456 | Private | 53.24 |
| 9524 | Forestry | 84.53 |
| 99002 | Forestry | 63.53 |
| 99003 | Forestry | 44.76 |
| 99004 | Forestry | 85.38 |
Initial Work and Observations
- EMN staff measure the diameter of all downed woody debris (and strongly leaning snags) ≥ 7.5cm in diameter that intersects the 45-meter-long center lines of EMN plot transects.
- From these measurements, volume is estimated for the amount of CWD that would occur in a full hectare ( m^3/ha )
Objective: Assess multiple factors impacting forest floor conditions
Under natural conditions in forests, leaf litter breaks down slowly leaving the forest floor layered with organic matter in various stages of decomposition, from intact leaves to finely decomposed particles. Several native forest plant species are adapted to this slow layering process, requiring finely decomposed leaf litter, called duff and humus, to survive. Invasive earthworms, transported into Minnesota by human activity since the 1700s, are rapidly removing duff and humus layers in forests throughout many parts of Minnesota. Measurements of leaf litter and humus are collected in forested EMN plots to assess the presence and impact of invasive earthworms.
Earthworm levels in Minnesota forests. Larger dot size represents higher earthworm effects on soil.
| Plot ID | Land Manager | IERAT Stage |
|---|---|---|
| 18 | Forestry | 4 |
| 33 | Parks and Trails | 2 |
| 36 | WMA | 5 |
| 38 | Forestry | 1.25 |
| 38 | Forestry | 3 |
| 45 | Parks and Trails | 3.5 |
| 49 | BWCA | 1 |
| 50 | County | 4 |
| 57 | WMA | 2 |
| 59 | SNF | 1 |
| 63 | Forestry | 3 |
| 69 | Forestry | 4.5 |
| 79 | BWCA | 1 |
| 82 | CNF | 2 |
| 85 | County | 3 |
| 90 | Private | 3.5 |
| 110 | WPA | 3 |
| 113 | Private | 2 |
| 127 | SNF | 3 |
| 127 | SNF | 3 |
| 133 | Forestry | 4 |
| 136 | WMA | 5 |
| 139 | WMA | 2 |
| 141 | City | 5 |
| 146 | CNF | 3 |
| 172 | Private | 5 |
| 177 | SNF | 1 |
| 180 | Private | 5 |
| 187 | SNF | 1 |
| 198 | Forestry | 5 |
| 202 | County | 3 |
| 212 | County | 5 |
| 212 | County | 5 |
| 214 | CNF | 1 |
| 225 | SNF | 1 |
| 226 | County | 1.75 |
| 242 | WMA | 4 |
| 257 | Parks and Trails | 3 |
| 260 | Meriwether | 4 |
| 261 | MN Power | 1 |
| 262 | Meriwether | 4 |
| 273 | County | 4 |
| 277 | Forestry | 1 |
| 284 | Private | 4 |
| 321 | County | 1.25 |
| 324 | Forestry | 4 |
| 335 | BWCA | 1 |
| 341 | Private | 2.5 |
| 405 | Camp Ripely | 1 |
| 406 | WMA | 2.5 |
| 413 | Private | 2 |
| 417 | County | 4 |
| 422 | CNF | 2 |
| 429 | County | 5 |
| 433 | SNF | 1 |
| 434 | Forestry | 3 |
| 443 | SNF | 2 |
| 456 | Private | 5 |
| 458 | County | 1 |
| 466 | Forestry | 3 |
| 470 | CNF | 1.666666667 |
| 473 | Private | 5 |
| 478 | County | 1 |
| 481 | SNF | 3 |
| 482 | SNF | 3 |
| 486 | Forestry | 2 |
| 487 | WMA | 4 |
| 495 | County | 2.5 |
| 497 | County | 4 |
| 498 | CNF | 5 |
| 514 | County | 1 |
| 518 | CNF | 1 |
| 521 | Private | 3 |
| 542 | Private | 5 |
| 545 | County | 3.333333333 |
| 546 | CNF | 1 |
| 548 | Private | 4 |
| 561 | SNF | 1 |
| 571 | SNF | 1 |
| 584 | Private | 4 |
| 585 | Private | 3 |
| 591 | SNF | 1 |
| 609 | SNF | 1.5 |
| 612 | Private | 5 |
| 614 | CNF | 1 |
| 637 | Forestry | 5 |
| 646 | County | 5 |
| 650 | County | 1 |
| 661 | Forestry | 1 |
| 673 | SNF | 1 |
| 685 | County | 4 |
| 689 | SNF | 1 |
| 693 | SNA | 3 |
| 701 | Forestry | 2 |
| 706 | CNF | 4 |
| 713 | WMA | 5 |
| 721 | SNF | 1 |
| 726 | Forestry | 1 |
| 734 | County | 1.5 |
| 753 | County | 4 |
| 763 | SNF | 1 |
| 765 | County | 2.25 |
| 769 | SNF | 1 |
| 773 | County | 3 |
| 789 | County | 2 |
| 801 | SNF | 1 |
| 804 | Forestry | 3.5 |
| 820 | Private | 5 |
| 833 | snf | 1 |
| 852 | Private | 5 |
| 862 | County | 2.5 |
| 870 | County | 5 |
| 877 | CNF | 1 |
| 895 | Forestry | 2 |
| 926 | County | 1 |
| 929 | SNF | 1 |
| 941 | County | 1.5 |
| 949 | Parks and Trails | 5 |
| 955 | SNF | 1 |
| 975 | Forestry | 4.666666667 |
| 990 | Forestry | 1 |
| 994 | SNF | 3 |
| 1003 | SNF | 1 |
| 1044 | Private | 4 |
| 1062 | Forestry | 1 |
| 1070 | County | 2 |
| 1085 | County | 1 |
| 1090 | Forestry | 3 |
| 1121 | SNF | 1 |
| 1124 | Parks and Trails | 2 |
| 1137 | County | 4 |
| 1140 | Private | 5 |
| 1161 | Forestry | 3 |
| 1172 | Private | 4 |
| 1192 | WMA | 5 |
| 1236 | WMA | 5 |
| 1249 | SNF | 3 |
| 1250 | County | 5 |
| 1253 | Private | 5 |
| 1325 | University | 2 |
| 1352 | Parks and Trails | 5 |
| 1365 | County | 2 |
| 1417 | Parks and Trails | 4 |
| 1442 | CNF | 3.666666667 |
| 1544 | Parks and Trails | 5 |
| 1574 | County | 1 |
| 1581 | Private | 3.5 |
| 1626 | Parks and Trails | 4.666666667 |
| 1652 | Private | 3 |
| 1698 | County | 3 |
| 1869 | County | 5 |
| 1925 | Parks and Trails | 5 |
| 1967 | Forestry | 3 |
| 1988 | Private | 5 |
| 2004 | WMA | 5 |
| 2051 | Private | 5 |
| 2074 | Forestry | 1 |
| 2269 | Parks and Trails | 5 |
| 2306 | County | 2.5 |
| 2423 | WMA | 4 |
| 2425 | Private | 5 |
| 2509 | County | 4 |
| 2653 | County | 5 |
| 2840 | SNA | 5 |
| 2841 | WMA | 4 |
| 3220 | SNA | 5 |
| 3252 | Forestry | 4.5 |
| 3301 | Forestry | 2 |
| 3357 | County | 5 |
| 3379 | WPA | 5 |
| 3411 | Private | 3 |
| 3414 | Forestry | 1 |
| 3513 | TNC | 5 |
| 3604 | Forestry | 4 |
| 3928 | County | 4.5 |
| 4061 | Parks and Trails | 3 |
| 4210 | Private | 5 |
| 4340 | Private | 4 |
| 4436 | Private | 5 |
| 4556 | County | 5 |
| 4968 | Private | 4 |
| 5004 | Private | 4 |
| 5132 | Parks and Trails | 4.5 |
| 5405 | Private | 5 |
| 5480 | AMA | 4.5 |
| 5512 | WMA | 4 |
| 5584 | County | 5 |
| 5604 | Parks and Trails | 5 |
| 5917 | Forestry | 2.5 |
| 6925 | SNA | 4.5 |
| 7689 | WMA | 4.666666667 |
| 7958 | Forestry | 1 |
| 8456 | Private | 5 |
| 9524 | Forestry | 5 |
| 9524 | Forestry | 5 |
| 99002 | Forestry | 5 |
| 99003 | Forestry | 5 |
| 99004 | Forestry | 3 |
Initial Work and Observations
- EMN uses the Invasive Earthworm Rapid Assessment Tool (IERAT) to evaluate depletion of leaf litter on forest floors by earthworms. IERAT scores range from 1 in plots with intact, unfragmented litter, duff, and humus layers (i.e., no worm effects), to 5 in plots characterized by bare mineral soil with abundant earthworm casts and middens (i.e., high worm effects).
- IERAT was developed for mesic hardwood forest systems, like sugar maple and basswood dominated communities.
- EMN plots show higher levels of invasive earthworm impacts in mesic forests in the southern half of the state relative to the northern half.
