BIOL 2050, YorkU Keele Campus ecology network: the study of plants, vertebrates and invertebrates in a forest
Creators: name: Munawar, Samina
Publisher: name: figshare
Year: 2016
Subjects: subject: 60207 Population Ecology
subject: FOS: Biological sciences
subject: FOS: Biological sciences

description: The data was collected on the west side of York University’s Keele Campus on October 5, 2016, in a forested area for approximately 2 hours in total. The weather was sunny with a slight breeze (a 1 on the Beaufort scale). The data was collected by Lauren Cunningham, Samina Munawar, Erin O’Connor, Fatima Zia.Dataset 1: Herbaceous Plants<b>Meta-Data:</b>“rep”: Quadrat number, e.g. “1” for the first time it is placed, “2” for the second time it is placed. “abundance.native.plants”: Number of native plants within quadrat and identified by the website www.ontariograsses.com and an image from ontarionature.org; each of them were counted by eye“abundance.exotic.plants”: Number of plants within quadrat that were not identified in the website and image and were thus considered exotic; counted by eye“total.number.flowers (quadrat)”: Number of flower heads as counted within quadrat<b>Meta-Analysis:</b>The grass in the forest was identified as native by the TA and was classified as such throughout the data collection. For other plants, we were to look up an identification guide for native plants of Ontario. Distinctions between native and non-native were made by looking at the leaf shape, whether or not it had flowers, and the height of the plant. Different native plant species had common characteristics among them so it wasn’t too difficult to spot. Only images were used to identify the plants, no other information was sought. Whatever was not found on www.ontariograsses.com or on the table used from ontarionature.org was considered non-native/exotic.As blades of grass are difficult to count individually, extrapolation was used for their counting. The researcher counted some grass blades in one corner of the quadrat, and estimated the number for the rest of the quadrat for multiplying by the number of sections of the same size within that quadrat (one section was about a hand’s length) with the number of grass blades found in the initial section.Such estimates were also sometimes done when there were many flowers present within the quadrat; the flowers on one plant were counted and then multiplied by the number of the same flowering plant within the quadrat. For plant types that had many tiny little flowery buds pressed together in one bundle were counted differently—one bundle was considered to be one flower head.When unable to identify the plant with the identification resources, the plants were categorized by other means. If that plant was very common throughout the forest, then it would be considered native. If it was sparsely located or only seen in that area, then it was likely that it was non-exotic, and was thus considered as such.<b>Methods:</b>Once inside the forest, a random direction to go was chosen (with no apparent method, just at whim), and the quadrat was put down directly to the right of the researcher. After collecting data for that quadrat, the researcher continued 2 meters in the same direction (as if walking along a transect), and then placed the quadrat directly to their left, and collected data. This was continued for a total of 25 quadrat placements, placing them every 2 meters along the straight line the researcher was walking, and alternating it putting on the left and right sides. The researcher would change direction (switch the line of walking either left or right, again at random with no method, just a spur of the moment decision) when there was no room to stand/walk in the direction the researcher was going in (due to dense vegetation). The researcher would walk in the same straight manner when the direction was changed.This data collection took approximately two hours.<b>Hypothesis and Predictions:</b> It was hypothesized that there would be a difference in the number of native plants and non-native plants. It was further predicted that there would be a greater number of native plants than non-native plants since native plants would have been there for a longer amount of time and would have covered more range as a result of that time. Also, it may be to due to the fact that its native area would also have favourable conditions for that plant species to flourish, while that may not always be the case for non-exotic plants, and thus may be less in number. The data shows that the hypothesis and prediction was indeed correct as there was a greater number of native plants.Dataset 2: Woody plants<b>Meta-Data:</b>“rep”: Represents the distances at which the data were collected. For abundance.woody.plants, canopy.cover and ground.cover, data was collected in increments of 2m and the rep values correlate to that. 1 is 2m and 25 is 50m. For total.flower.numbers, distances increased by 5m, with 1 being 5m and 10 being 50m. These distances were measured with a transect, in meters only. It also represents the number of replicates measured. “abundance.woody.plants”: The total number of trees located 0.5m on either side of the transect. This value was measured every 2m, for a total of 50 m. A tree was only counted if it was taller than 1.5 m, its height being visually estimated.“canopy.cover”: The percent of sky that could be seen, recorded on a scale from 0-1, with 0 being no sky seen and 1 being only sky seen. This was visually estimated by looking near the top of the tree while making a square with the hands and estimating how much sky was visible in the square. This value was measured every 2m, alternating with ground.cover. It was measured for 50m total.“ground.cover”: The percent of plants covering the ground, listed on a scale from 0-1 with 0 being no plants and 1 being only plants seen. This was visually estimated by looking at a square patch of ground, similar to how the canopy cover was measured, directly by the transect. This value was observed every 2m, alternating with canopy.cover. 50m total were measured.“total.flower.numbers (transect)”: The total number of flowers within 1m of the transect, measured every 5m, for a total of 50m.<b>Methods:</b>From the centre of the woodlot in which the data was collected, a random direction and location was picked by the researcher. That location was marked as 0m and from there, the researcher walked forward in a straight line, measuring the distance with a transect, in meters.Each two meters, the researcher recorded the number of trees within 0.5m of the transect on either side. Each odd meter, the researcher recorded the canopy cover and every even meter, the researcher recorded the ground cover. Every 5m, the researcher recorded the number of flowers within a meter of the transect.For each, since a 30m transect was used, first 25m were measured out and then, using the 25m position as a new 0m, the transect was reused for a second 25m, starting at the new 0m. A total of 50m was measured for each value. All distances from the transect, canopy cover and ground cover were estimated with the eye.<b>Hypothesis and Predictions:</b> It was hypothesized that the canopy cover would vary with the number of trees in the area. It was predicted that in areas where there were more trees, there would be greater canopy cover since there would be more trees to provide canopy. This prediction was found to be incorrect. There was no significant difference between the average canopy cover with 0 trees 0.5m from the transect and or when there was 1 tree. So, from the data, it can be extrapolated that the amount of canopy coverage is consistent in a wooded area.Dataset 3: Vertebrates &amp; Invertebrates<b>Meta-Data:</b>“abundance.vertebrates”: The total number of vertebrates observed in a 50 meter radius within the forest for 15 minutes; used 50 meters of transect as a guide. (Ex. birds, squirrels, etc.)“vertebrate.species”: The list of different vertebrate species observed in a 50 meter radius within the forest for 15 minutes. These species included the American robin, seagull, and squirrel.“abundance.human”: The total number of people observed in a 50 meter radius within the forest for 15 minutes that did not belong to the laboratory group; used 50 meters of transect as a guide.“abundance.invertebrates.observed”: The total number of invertebrates observed in a 5 meter radius within the forest for 15 minutes; used 5 meters of transect as a guide. (Ex. snails, flies, insects etc.).<b>Specific Vertebrate Data</b>- 8 American Robins- 2 seagulls- 1 squirrelTotal: 11<b>Specific Invertebrate Data</b>- 27 garden snails- 6 flies- 5 mosquitos- 4 ants- 2 pill bugs- 1 waspTotal: 45<b>Methods:</b>Two 25 meter transects were placed in the forest in order to survey a 50 meter radius for vertebrates and humans. The point at which the two 25 meter transects met was considered to be the centre point; the 50 meter radius was based 360 degrees around this point. A timer was then set for 15 minutes. The transect line was used as a guide to scale up, down and around the target area. Listening for animal calls/noises or rustling also helped guide with direction to locate and identify animals. The same process was used for invertebrates except only 5 meters of one transect was used. All measured variables were counted and observed using the naked eye. Species were observed for two 15 minute intervals, therefore data was collected over a total of 30 minutes.