Loading…
Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach
Macrophytes are an integral component of lake communities; therefore, understanding the factors that affect macrophyte community structure is important for conservation and management of lakes. In Sibley County, Minnesota, USA, five of the largest and most recreationally important lakes were surveye...
Saved in:
Published in: | Aquatic ecology 2022-12, Vol.56 (4), p.917-935 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503 |
---|---|
cites | cdi_FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503 |
container_end_page | 935 |
container_issue | 4 |
container_start_page | 917 |
container_title | Aquatic ecology |
container_volume | 56 |
creator | Schmid, Samuel A. Wersal, Ryan M. Fleming, Jonathan P. |
description | Macrophytes are an integral component of lake communities; therefore, understanding the factors that affect macrophyte community structure is important for conservation and management of lakes. In Sibley County, Minnesota, USA, five of the largest and most recreationally important lakes were surveyed using the point-intercept method. At each point the presence of macrophytes were recorded, water depth was measured, and a sediment sample was collected. Sediment samples were partitioned by determining sand, silt, clay, and organic matter fractions. The richness of macrophytes in all lakes were modeled via generalized linear regression with six explanatory variables: water depth, distance from shore, percent sand, percent silt, percent clay, and percent sediment organic matter. If model residuals were spatially autocorrelated, then a geographically weighted regression was used. Mean species richness (N point
−1
) was negatively related to depth and distance from shore and either positively or negatively related to silt depending on the lake and which macrophytes were present. All species richness models had
pseudo
-
R
2
values between 0.25 and 0.40. Curlyleaf pondweed (
Potamogeton crispus
) was found at 44% of all sampling points in one lake, and its presence was related to water depth, percent silt, and percent sediment organic matter during early season surveys. Results from this study exhibit the inhibitory relationship between water depth and macrophyte growth. The results from these models suggest interactions are complex between macrophytes, environmental factors, and sediment texture; and that these interactions are species and site specific. A single landscape scale model would not be appropriate to capture the in-lake processes driving macrophyte distribution and abundance; and management strategies will need to be developed on a lake-by-lake basis. |
doi_str_mv | 10.1007/s10452-022-09969-3 |
format | article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_2849883840</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A724645562</galeid><sourcerecordid>A724645562</sourcerecordid><originalsourceid>FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503</originalsourceid><addsrcrecordid>eNp9kU2L1TAUhosoOI7-AVcBN246k6RNmri7DH7BiBtdh9Pck9uMbdJJUmR-g3_aXCsIs5AQcjg87_nI2zSvGb1ilA7XmdFe8JbyerWWuu2eNBdMDF0rGBdPa9wp2XKh1PPmRc53lFJNB37R_DqMPhZviQNbYsqkTFAIOIe21BjJ0eeS_LgVHwOJjsD9Bmd-AZviOj0UzMQHkieY5_iThJjKRAouKyYoSL74EDDHAmSGH5jfESB5rQVgJks84uzDicC6pgh2etk8czBnfPX3vWy-f3j_7eZTe_v14-ebw21rO85K65QSXDgutUTrpHVAtZPUCTkINcpxANS0rk4dKqsGq0QnxFj3p4NiTtDusnm7161t7zfMxSw-W5xnCBi3bLjqtVKd6s_om0foXdxSqNMZXjuwQWl9pq526gQzGh9cLAlsPUdcvI0Bna_5w8B72QsheRXwXVD_MOeEzqzJL5AeDKPmbKjZDTXVUPPHUNNVUbeLcoXDCdO_Wf6j-g2dbaTJ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2730178990</pqid></control><display><type>article</type><title>Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach</title><source>Springer Nature</source><creator>Schmid, Samuel A. ; Wersal, Ryan M. ; Fleming, Jonathan P.</creator><creatorcontrib>Schmid, Samuel A. ; Wersal, Ryan M. ; Fleming, Jonathan P.</creatorcontrib><description>Macrophytes are an integral component of lake communities; therefore, understanding the factors that affect macrophyte community structure is important for conservation and management of lakes. In Sibley County, Minnesota, USA, five of the largest and most recreationally important lakes were surveyed using the point-intercept method. At each point the presence of macrophytes were recorded, water depth was measured, and a sediment sample was collected. Sediment samples were partitioned by determining sand, silt, clay, and organic matter fractions. The richness of macrophytes in all lakes were modeled via generalized linear regression with six explanatory variables: water depth, distance from shore, percent sand, percent silt, percent clay, and percent sediment organic matter. If model residuals were spatially autocorrelated, then a geographically weighted regression was used. Mean species richness (N point
−1
) was negatively related to depth and distance from shore and either positively or negatively related to silt depending on the lake and which macrophytes were present. All species richness models had
pseudo
-
R
2
values between 0.25 and 0.40. Curlyleaf pondweed (
Potamogeton crispus
) was found at 44% of all sampling points in one lake, and its presence was related to water depth, percent silt, and percent sediment organic matter during early season surveys. Results from this study exhibit the inhibitory relationship between water depth and macrophyte growth. The results from these models suggest interactions are complex between macrophytes, environmental factors, and sediment texture; and that these interactions are species and site specific. A single landscape scale model would not be appropriate to capture the in-lake processes driving macrophyte distribution and abundance; and management strategies will need to be developed on a lake-by-lake basis.</description><identifier>ISSN: 1386-2588</identifier><identifier>EISSN: 1573-5125</identifier><identifier>DOI: 10.1007/s10452-022-09969-3</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Abiotic factors ; Aquatic plants ; autocorrelation ; Biomedical and Life Sciences ; Clay ; Community structure ; Distance ; Distribution ; Ecosystem components ; Ecosystems ; Environmental factors ; Freshwater & Marine Ecology ; Freshwater plants ; Lakes ; landscapes ; Life Sciences ; Macrophytes ; Minnesota ; Organic matter ; Potamogeton crispus ; regression analysis ; Sand ; Scale models ; Sediment ; Sediment samplers ; Sediment samples ; Sediment texture ; Sediments ; Sediments (Geology) ; Silt ; Species richness ; Surveys ; Water depth</subject><ispartof>Aquatic ecology, 2022-12, Vol.56 (4), p.917-935</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022</rights><rights>COPYRIGHT 2022 Springer</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503</citedby><cites>FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503</cites><orcidid>0000-0002-4014-5138</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Schmid, Samuel A.</creatorcontrib><creatorcontrib>Wersal, Ryan M.</creatorcontrib><creatorcontrib>Fleming, Jonathan P.</creatorcontrib><title>Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach</title><title>Aquatic ecology</title><addtitle>Aquat Ecol</addtitle><description>Macrophytes are an integral component of lake communities; therefore, understanding the factors that affect macrophyte community structure is important for conservation and management of lakes. In Sibley County, Minnesota, USA, five of the largest and most recreationally important lakes were surveyed using the point-intercept method. At each point the presence of macrophytes were recorded, water depth was measured, and a sediment sample was collected. Sediment samples were partitioned by determining sand, silt, clay, and organic matter fractions. The richness of macrophytes in all lakes were modeled via generalized linear regression with six explanatory variables: water depth, distance from shore, percent sand, percent silt, percent clay, and percent sediment organic matter. If model residuals were spatially autocorrelated, then a geographically weighted regression was used. Mean species richness (N point
−1
) was negatively related to depth and distance from shore and either positively or negatively related to silt depending on the lake and which macrophytes were present. All species richness models had
pseudo
-
R
2
values between 0.25 and 0.40. Curlyleaf pondweed (
Potamogeton crispus
) was found at 44% of all sampling points in one lake, and its presence was related to water depth, percent silt, and percent sediment organic matter during early season surveys. Results from this study exhibit the inhibitory relationship between water depth and macrophyte growth. The results from these models suggest interactions are complex between macrophytes, environmental factors, and sediment texture; and that these interactions are species and site specific. A single landscape scale model would not be appropriate to capture the in-lake processes driving macrophyte distribution and abundance; and management strategies will need to be developed on a lake-by-lake basis.</description><subject>Abiotic factors</subject><subject>Aquatic plants</subject><subject>autocorrelation</subject><subject>Biomedical and Life Sciences</subject><subject>Clay</subject><subject>Community structure</subject><subject>Distance</subject><subject>Distribution</subject><subject>Ecosystem components</subject><subject>Ecosystems</subject><subject>Environmental factors</subject><subject>Freshwater & Marine Ecology</subject><subject>Freshwater plants</subject><subject>Lakes</subject><subject>landscapes</subject><subject>Life Sciences</subject><subject>Macrophytes</subject><subject>Minnesota</subject><subject>Organic matter</subject><subject>Potamogeton crispus</subject><subject>regression analysis</subject><subject>Sand</subject><subject>Scale models</subject><subject>Sediment</subject><subject>Sediment samplers</subject><subject>Sediment samples</subject><subject>Sediment texture</subject><subject>Sediments</subject><subject>Sediments (Geology)</subject><subject>Silt</subject><subject>Species richness</subject><subject>Surveys</subject><subject>Water depth</subject><issn>1386-2588</issn><issn>1573-5125</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kU2L1TAUhosoOI7-AVcBN246k6RNmri7DH7BiBtdh9Pck9uMbdJJUmR-g3_aXCsIs5AQcjg87_nI2zSvGb1ilA7XmdFe8JbyerWWuu2eNBdMDF0rGBdPa9wp2XKh1PPmRc53lFJNB37R_DqMPhZviQNbYsqkTFAIOIe21BjJ0eeS_LgVHwOJjsD9Bmd-AZviOj0UzMQHkieY5_iThJjKRAouKyYoSL74EDDHAmSGH5jfESB5rQVgJks84uzDicC6pgh2etk8czBnfPX3vWy-f3j_7eZTe_v14-ebw21rO85K65QSXDgutUTrpHVAtZPUCTkINcpxANS0rk4dKqsGq0QnxFj3p4NiTtDusnm7161t7zfMxSw-W5xnCBi3bLjqtVKd6s_om0foXdxSqNMZXjuwQWl9pq526gQzGh9cLAlsPUdcvI0Bna_5w8B72QsheRXwXVD_MOeEzqzJL5AeDKPmbKjZDTXVUPPHUNNVUbeLcoXDCdO_Wf6j-g2dbaTJ</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Schmid, Samuel A.</creator><creator>Wersal, Ryan M.</creator><creator>Fleming, Jonathan P.</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7QL</scope><scope>7SN</scope><scope>7T7</scope><scope>7TN</scope><scope>7U9</scope><scope>7UA</scope><scope>88A</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H94</scope><scope>H95</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>LK8</scope><scope>M7N</scope><scope>M7P</scope><scope>P64</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PHGZM</scope><scope>PHGZT</scope><scope>PKEHL</scope><scope>PQEST</scope><scope>PQGLB</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>7S9</scope><scope>L.6</scope><orcidid>https://orcid.org/0000-0002-4014-5138</orcidid></search><sort><creationdate>20221201</creationdate><title>Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach</title><author>Schmid, Samuel A. ; Wersal, Ryan M. ; Fleming, Jonathan P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Abiotic factors</topic><topic>Aquatic plants</topic><topic>autocorrelation</topic><topic>Biomedical and Life Sciences</topic><topic>Clay</topic><topic>Community structure</topic><topic>Distance</topic><topic>Distribution</topic><topic>Ecosystem components</topic><topic>Ecosystems</topic><topic>Environmental factors</topic><topic>Freshwater & Marine Ecology</topic><topic>Freshwater plants</topic><topic>Lakes</topic><topic>landscapes</topic><topic>Life Sciences</topic><topic>Macrophytes</topic><topic>Minnesota</topic><topic>Organic matter</topic><topic>Potamogeton crispus</topic><topic>regression analysis</topic><topic>Sand</topic><topic>Scale models</topic><topic>Sediment</topic><topic>Sediment samplers</topic><topic>Sediment samples</topic><topic>Sediment texture</topic><topic>Sediments</topic><topic>Sediments (Geology)</topic><topic>Silt</topic><topic>Species richness</topic><topic>Surveys</topic><topic>Water depth</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Schmid, Samuel A.</creatorcontrib><creatorcontrib>Wersal, Ryan M.</creatorcontrib><creatorcontrib>Fleming, Jonathan P.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Oceanic Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Biology Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Biological Sciences</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>ProQuest Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Applied & Life Sciences</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Aquatic ecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Schmid, Samuel A.</au><au>Wersal, Ryan M.</au><au>Fleming, Jonathan P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach</atitle><jtitle>Aquatic ecology</jtitle><stitle>Aquat Ecol</stitle><date>2022-12-01</date><risdate>2022</risdate><volume>56</volume><issue>4</issue><spage>917</spage><epage>935</epage><pages>917-935</pages><issn>1386-2588</issn><eissn>1573-5125</eissn><abstract>Macrophytes are an integral component of lake communities; therefore, understanding the factors that affect macrophyte community structure is important for conservation and management of lakes. In Sibley County, Minnesota, USA, five of the largest and most recreationally important lakes were surveyed using the point-intercept method. At each point the presence of macrophytes were recorded, water depth was measured, and a sediment sample was collected. Sediment samples were partitioned by determining sand, silt, clay, and organic matter fractions. The richness of macrophytes in all lakes were modeled via generalized linear regression with six explanatory variables: water depth, distance from shore, percent sand, percent silt, percent clay, and percent sediment organic matter. If model residuals were spatially autocorrelated, then a geographically weighted regression was used. Mean species richness (N point
−1
) was negatively related to depth and distance from shore and either positively or negatively related to silt depending on the lake and which macrophytes were present. All species richness models had
pseudo
-
R
2
values between 0.25 and 0.40. Curlyleaf pondweed (
Potamogeton crispus
) was found at 44% of all sampling points in one lake, and its presence was related to water depth, percent silt, and percent sediment organic matter during early season surveys. Results from this study exhibit the inhibitory relationship between water depth and macrophyte growth. The results from these models suggest interactions are complex between macrophytes, environmental factors, and sediment texture; and that these interactions are species and site specific. A single landscape scale model would not be appropriate to capture the in-lake processes driving macrophyte distribution and abundance; and management strategies will need to be developed on a lake-by-lake basis.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10452-022-09969-3</doi><tpages>19</tpages><orcidid>https://orcid.org/0000-0002-4014-5138</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1386-2588 |
ispartof | Aquatic ecology, 2022-12, Vol.56 (4), p.917-935 |
issn | 1386-2588 1573-5125 |
language | eng |
recordid | cdi_proquest_miscellaneous_2849883840 |
source | Springer Nature |
subjects | Abiotic factors Aquatic plants autocorrelation Biomedical and Life Sciences Clay Community structure Distance Distribution Ecosystem components Ecosystems Environmental factors Freshwater & Marine Ecology Freshwater plants Lakes landscapes Life Sciences Macrophytes Minnesota Organic matter Potamogeton crispus regression analysis Sand Scale models Sediment Sediment samplers Sediment samples Sediment texture Sediments Sediments (Geology) Silt Species richness Surveys Water depth |
title | Abiotic factors that affect the distribution of aquatic macrophytes in shallow north temperate Minnesota lakes: a spatial modeling approach |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-23T18%3A02%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Abiotic%20factors%20that%20affect%20the%20distribution%20of%20aquatic%20macrophytes%20in%20shallow%20north%20temperate%20Minnesota%20lakes:%20a%20spatial%20modeling%20approach&rft.jtitle=Aquatic%20ecology&rft.au=Schmid,%20Samuel%20A.&rft.date=2022-12-01&rft.volume=56&rft.issue=4&rft.spage=917&rft.epage=935&rft.pages=917-935&rft.issn=1386-2588&rft.eissn=1573-5125&rft_id=info:doi/10.1007/s10452-022-09969-3&rft_dat=%3Cgale_proqu%3EA724645562%3C/gale_proqu%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c321t-f88525f2696ecf6cfa09f60f56758b6b7ae905730fe8c87c85355b3860781f503%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2730178990&rft_id=info:pmid/&rft_galeid=A724645562&rfr_iscdi=true |