Comparison of the Effects of Growing-Season Burns and Dormant-Season Burns on Vegetation Structure and Grassland Bird Diversity in East-Central Illinois Prairies
Notice bibliographique
Résumé
For managed grasslands, prescribed burns are a method to manage species composition by preventing crowding by bunch grasses and woody encroachment. While dormant-season (spring) burns are routinely performed, managers have recently introduced growing-season (late summer/fall) burns to prairies in east-central Illinois. The purpose of this study was to compare the effects of dormant-season and growingseason burns on vegetation structure and associated avian diversity. Specifically, objectives were to determine if: (1) Growing-season burns increase bird diversity or density of rare/declining species relative to dormant season burns; (2) Growing-season burns cause more bare ground to open and reduce litter and woody species relative to dormant-season burns; and (3) Growing-season burns improve vegetative diversity or habitat quality relative to dormant season burns. In four managed grasslands, paired plots were designated for seasonal prescribed burns during 2016 such that one of each of the paired plots was scheduled to be burned in the spring (dormant season) and one was scheduled to be burned in the late summer/fall (growing season). Composition was determined by point count surveys for birds and randomly placed one m2 plots for vegetation. Vegetation was assessed by species present, percent coverage, and estimated height. The bird census included birds flushed and birds present in the plot as well as birds that entered the plot during each survey. As a result of unperformed burns and alternative management methods like spraying on some research plots, I performed a restricted analysis on four paired plots that were subjected to planned dormant- and growing-season burns. In order to determine the effects of growing-season burns, I also performed a restricted analysis using all plots that received this type of burn. I used analysis of variance (ANOVA) on plant cover, plant species richness, and bird species richness for both analyses. I expected the vegetation in plots subjected to growing-season burns to have i greater species diversity but expected plots experiencing dormant-season burns to have greater percent cover and height because of the reduction of bunch grasses in the plots receiving growing-season burns. I also anticipated bird diversity to vary between the two types of plots. When comparing pre-burn (2016) to post-burn (2017) bird densities for plots burned during the growing season, I found statistically nonsignificant increases in certain desirable bird species like bobolinks (Dolichonyx oryzivorus), field sparrows (Spizella pusilla), eastern meadowlarks (Sturnella magna), and dickcissels (Spiza americana), but a decrease in northern bobwhites (Colinus virginianus). When comparing dormant- to growing-season burns (2017), growing-season plots had non-significantly higher densities of bobolinks, field sparrows and grasshopper sparrows but lower densities of bobwhite, dickcissels, and meadowlarks. Both dormantand growing-season burns showed an increase in bare ground opening and a decrease in litter and shrubby species, but growing-season burns had a larger overall increase in bare ground. Graminoids generally increased after the dormant-season burns. While graminoids did not decline in cover as a result of the growing-season burn, species like Canada wild rye (Elymus canadensis), timothy (Phleum pratense), and various sedge species (Carex spp.) did decrease. The plant communities tended to shift toward disturbance-tolerant species like Canada goldenrod (Solidago canadensis), annual ragweed (Ambrosia artemisiifolia), and sweet clover (Melilotus spp.) with a more diverse community in the 2017 season after both dormant- and growing-season burns. Thus, growing-season fires are useful for satisfying certain management objectives, and tend to vary only slightly from dormant-season fires, at least in the immediate aftermath of the burns (i.e., the first year or two after the burns). Also, growing-season burns offer advantages such as better weather for prescribed burns and logistic flexibility. Thus, growing-season prescribed burns can be used as a tool alongside dormant-season burns and mixed-management models. Further research would be desirable to determine more applications with a focus on longer-term post-burn monitoring
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».