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Relationships between wetland macroinvertebrates and waterfowl along an agricultural gradient in the Boreal Transition Zone of western Canada.

ABSTRACT--We examined 14 wetlands in the Boreal Transition Zone (BTZ) of western Canada to investigate the effects of agricultural encroachment on aquatic macroinvertebrate communities and the response of waterfowl communities to these changes. The amount of agriculture within a 1.6-km buffer around wetlands was quantified primarily by remote imagery, and a sample of relatively similar wetlands was selected along an encroachment gradient from 0 to 90% agriculture. Species dominance showed temporal shifts during spring and summer. In May, 3 primary macroinvertebrate-dominated community types were present: 1) Amphipoda, 2) Diptera, and 3) Sigara. In August, 3 community types were present: 1) Amphipoda, 2) Notonecta, and 3) Chaoborus-Sigara. Environmental conditions were not distinct in every community type; however Sigara-dominated communities occurred in significantly shallower wetlands with greater concentrations of total inorganic nitrogen, total dissolved solids, and salinity than did Diptera dominated communities. Agricultural intensity was positively associated with phosphorus concentration. Phosphorus was likely an important factor in determining macroinvertebrate community composition with Sigara and Chaoborus-Sigara communities occurring in wetlands with very high concentrations of phosphorus (average >800 [micro]g/L), and Diptera and Notonecta communities occurring in wetlands with lower phosphorus (average <160 [micro]g/L). Amphipoda-dominated communities tended to occur in larger and deeper basins than Sigara-dominated communities. Waterfowl abundance was significantly and positively associated with macroinvertebrate abundance; however, occurrence of most waterfowl species did not correspond well with specific macroinvertebrate community types.

Key words: agricultural encroachment, aquatic macroinvertebrates, boreal transition, indicator species, phosphorus, waterfowl


Aquatic macroinvertebrate communities found in freshwater wetlands are typically diverse and consist of permanently aquatic taxa (for example, Amphipoda and Hirudinae), taxa with a terrestrial adult stage (for example, Diptera and Odonata), and taxa that use both the terrestrial and aquatic environments (for example, adult Coleoptera and Hemiptera) (see Batzer and Wissinger 1996). The macroinvertebrate community present in a given wetland can depend on many factors such as geographic location (Mihuc and Toetz 1996; Nicolet and others 2004), wetland depth (Zimmer and others 2000), turbidity (Anteau and others 2011), fish presence (Cox and others 1998; McParland and Paszkowski 2006), vegetation density and structure (de Szalay and Resh 1997; Gardner and others 2001), human influences (Richards and others 1993; Ometo and others 2000), and wetland permanence (Euliss and others 2002; Lillie 2003). Because so many factors can influence macroinvertebrate communities, even wetlands in close proximity can have very different communities (Lindeman and Clark 1999; Fairchild and others 2000). Furthermore, macroinvertebrate community composition can change within a given wetland throughout the ice-free season (Lahr and others 1999; Culioli and others 2006).

Aquatic macroinvertebrate communities can provide waterfowl (specifically, Anatinae or ducks in this study) with an important source of dietary protein and other nutrients. The amount and type of macroinvertebrates consumed by waterfowl often varies with species, sex, developmental stage, and time of year. Some species, such as Bufflehead (Bucephala albeola), Common Goldeneye (Bucephala clangula), Lesser Scaup (Athya affinis), and Ruddy Duck (Oxyura jamaicensis) have diets that are almost exclusively macroinvertebrates throughout their entire lives (Hoppe and others 1986; Bendell and McNicol 1995; Thompson and Ankney 2002), while others like American Widgeon (Anas americana) consume mostly vegetation during adulthood (Wishart 1983; Knapton and Pauls 1994). In most species, ducklings and females producing eggs tend to consume more macroinvertebrates (for example, gastropods) than adult males or females during the non-breeding seasons (Nummi and Poysa 1993; Bendell and McNicol 1995). With respect to the type of macroinvertebrates consumed by breeding waterfowl, some species such as the filter-feeding Northern Shoveler (Anas clypeata) forage primarily on cladocerans (DuBowy 1985), others like Buffiehead consume a high proportion of Zygoptera larvae (Thompson and Ankney 2002), while Lesser Scaup prefer Amphipoda (Afton and Hier 1991), and Ruddy Duck eat mostly Chironomidae larvae (Woodin and Swanson 1989). For molting waterfowl, site selection is typically very important, especially in terms of food availability. Plumage growth during this period results in additional daily nutrient requirements, and simultaneous remigial molt does not allow waterfowl to forage widely (Salomonsen 1968; Baldassarre and Bolen 1994). Abundance and species composition of macroinvertebrate communities could therefore affect waterfowl communities during both the breeding and molting periods.

When agriculture encroaches on wetlands, the impact on macroinvertebrate and waterfowl communities is complex. In general, agricultural practices can introduce herbicides and insecticides to wetlands (Grue and others 1989), increase levels of phosphorus and nitrogen (Carpenter and others 1998), and decrease the amount of emergent and submerged vegetation (Bue and others 1952; Lauridsen and others 2003; Scrimgeour and Kendall 2003). In areas where intense agriculture is associated with wetlands, the diversity and abundance of macroinvertebrate and waterfowl taxa can decrease below levels found in similar wetlands embedded within remnant tracts of native habitat (Kay and others 2001; Podruzny and others 2002).

The Boreal Transition Zone (BTZ) of western Canada encompasses the southern tier of ecoregions in the Boreal Plains ecozone (Ecological Stratification Working Group 1995), most of which have experienced substantial agricultural encroachment in recent decades (Fitzsimmons 2002; Hobson and others 2002). This region of the Boreal Plains historically included some native grassland and shrubland, but was predominantly covered by mixed deciduous and coniferous forest interspersed with an abundance of wetlands and shallow lakes. Since the mid-20th century, the BTZ has experienced a rapid increase in agricultural land use (Hobson and others 2002). In recent decades, the annual rate of deforestation in the BTZ has increased from 0.87 to 1.3%, while the world-wide average remained at approximately 0.3%/y (Cumming and others 2001; Hobson and others 2002). Unfortunately, as part of the conversion of forest to agriculture, numerous wetlands have been drained or heavily modified (Cumming and others 2001) resulting in significant loss of wildlife habitat.

Information on how agricultural expansion in boreal ecosystems affects aquatic macroinvertebrates or waterfowl is scarce. In one of the few studies on impacts of agriculture on birds in the Boreal Plains, Cumming and others (2001) found that some waterfowl and other bird species decreased as the amount of agriculture increased. The loss of wetland habitat from draining and cultivation was identified as one of the main causes for bird population declines in the Boreal Plains (Cumming and others 2001). Wetland loss also affects macroinvertebrate communities by eliminating habitat that many taxa use for all or part of their life cycle (Gleason and others 2004).

The macroinvertebrate communities of BTZ wetlands have not been characterized, nor has the effect of increased agriculture on these communities. Our primary objective was to describe aquatic macroinvertebrate communities in BTZ wetlands and to determine whether species composition at the wetland-basin scale was related to the extent of surrounding agricultural encroachment. We also sought to determine whether macroinvertebrate communities were related to waterfowl communities during the breeding and molting seasons. We predicted that: 1) BTZ wetlands would have rich and diverse macroinvertebrate communities that were sensitive to the scale of surrounding agriculture; and 2) breeding and molting waterfowl communities would correspond with macroinvertebrate communities found in wetlands due to increased nutritional demands for reproduction and feather growth.


Study Site

The BTZ wetlands we studied (n =14) were located in the Lakeland and Athabasca regions near Lac La Biche, Alberta, Canada (UTM: Zone 12U, 437803E, 6069387N, NAD83/WGS84). The BTZ is characterized by a mosaic of mixed conifer and deciduous forest and agricultural lands (primarily pasture and hay production, although the amount of annually cultivated land is rapidly increasing). The study wetlands were distributed along a gradient of agricultural impact with the amount of agriculture within 1.6-km radius of the wetland varying between 0 and 90%. Wetlands were generally shallow, alkaline, naturally eutrophic, and relatively small (average = 16.5 ha). A fringe of emergent vegetation (primarily Typha spp. and Carex spp.) surrounds most of the wetlands, and many contained abundant submerged aquatic vegetation. The total amount of precipitation for this region in 2006 was 482.3 mm, which is very close to the 30 y average of 503.7 mm (Environment Canada 2007). A total of 310.6 mm of rain fell between May and August 2006, which is again very similar to the 30 y average of 306.1 mm (Environment Canada 2007).

Data Collection

Macroinvertebrates were collected from the study wetlands during May 2006 (corresponding with the waterfowl breeding season) and in August 2006 (corresponding with the waterfowl molting season). Macroinvertebrates were collected using a D-sweep net (500-[micro]m mesh size with an opening of 650 [cm.sup.2]) from 5 randomly selected locations within the emergent zone of each wetland. From a kayak, the net was lowered vertically into the water to the benthicpelagic boundary and then returned to the surface with a small arching motion. Water depth recorded at each site (averaging 39.8 cm in May and 31.7 cm in August) allowed raw macroinvertebrate counts to be transformed into density data. Macroinvertebrate samples were stored in 70% ethanol until they could be identified to genus or family using Clifford (1991). Genus-level identification in particular provides good resolution of macroinvertebrate communities, while still allowing samples to be processed in a timely manner (O'Leary and others 2004; Waite and others 2004). For simplicity, the macroinvertebrate family or sub-family designations will be referred to as taxa throughout this paper.

Aerial, wetland-specific waterfowl surveys were conducted in 2006 by Ducks Unlimited Canada (DUC) as part of a larger waterfowl survey program in the BTZ. In May and early June 2006, each wetland was surveyed 3 times by helicopter to identify and count the number of breeding waterfowl. Each survey was separated by a period of 7 to 10 d to account for interspecific variation in breeding chronology of waterfowl. Helicopter-derived counts were subsequently corrected for visibility bias using species-specific correction factors generated from ground-based waterfowl surveys conducted within a day of the aerial surveys. Data are reported in terms of indicated breeding pairs (IBP) for each species, which in most cases is the number of pairs, lone males, and males in groups of 2 to 5 observed on each wetland (Dzubin 1969).

In late July and August 2006, we conducted 3 rounds of molting waterfowl surveys from fixed-wing aircraft. Each survey was separated by a period of 7 to 10 d to account for interspecific variation in molting chronology of waterfowl. Molting-season waterfowl counts were reported as individuals/species. The maximum count for each species across the 3 rounds was used to account for temporal variation in peak abundance of species, as was done with the breeding-season surveys.

Water samples were collected from the center of each of the wetlands in late May and mid-August 2006. Water samples were collected from just below the water surface directly into acid washed bottles. Samples were put on ice, filtered within 24 h and analyzed for total phosphorus (TP), total dissolved phosphorus (TDP), soluble reactive phosphorus (SRP), total nitrogen (TN), total dissolved nitrogen (TDN), ammonia (N[H.sub.4.sup.+]-N), nitrate (N[O.sub.3].sup.2-]-N), nitrite (N[O.sub.2.sup.-]-N), chloride ([Cl.sup.-]), sulphate (S[O.sub.4.sup.2-]), sodium ([Na.sup.+]), potassium ([K.sup.+]), calcium ([Ca.sup.2+]), magnesium ([Mg.sup.2+]), silica ([Si.sup.4+]), carbonate (C[O.sub.3.sup.2-]), bicarbonate (HC[O.sub.3.sup.-]), total dissolved solids (TDS), and chlorophyll a. All water sample analyses were performed using techniques described in Bayley and Prather (2003).

Field measurements of pH were measured in situ using a Hydrolab Quanta field probe. Estimated abundance of submerged aquatic vegetation (SAV) was made visually for each basin and ranked on an ordinal scale of <5%, 5 to 25%, 25 to 75% and >75% coverage of the wetland (Bayley and Prather 2003). This method provided a quick and reliable way of estimating SAV in each basin.

Additionally, both Secchi depth and maximum depth of each wetland was recorded. Maximum depth was estimated by measuring depth in 3 random locations in each wetland using a calibrated weighted rope, with the deepest measurement obtained considered to be the maximum depth.

The percent of agriculture (crops, pasture, and hayland) within a 1.6-km buffer of the wetland was determined from Prairie Farm Rehabilitation Administration (PFRA) data collected in 1995 (Agriculture and Agri-Food Canada 1995). Estimates derived from this GIS database were verified using aerial photographs taken during waterfowl surveys in 2006 and 2007 and corrected for agricultural development that occurred after the PFRA database was created. Wetland area was estimated for each basin using digital versions of the National Topographic Survey Maps (NTS) (1:50,000 scale) and DUC's Landsat-based habitat inventory for sites that did not appear on the NTS maps.

Data Analyses

Macroinvertebrate community patterns were characterized using a combination of cluster, indicator species, and ordination analyses. Data collected during May and August were analyzed separately due to high variability between the 2 sampling periods. Furthermore, many environmental factors that can influence macroinvertebrate communities can change considerably during the growing season in small, shallow wetlands (Dufrene and Legendre 1997; Bennion and Smith 2000).

All statistical analyses were conducted in R (R Development Core Team 2007) using the 'vegan' (Oksanen and others 2011) and 'labdsv' (Roberts 2006) packages. To simplify both the analysis and interpretation of environmental variables, salinity (mg/L) was calculated by summing the concentrations of the 9 major ions ([Ca.sup.2+], [Mg.sup.2+], [Na.sup.+], [K.sup.+], [Si.sup.4+], HC[O.sub.3.sup.-], C[O.sub.3.sup.2-], S[O.sub.4.sup.2] and [Cl.sup.-]) (Wetzel 2001). Water visibility was calculated by dividing Secchi depth by maximum depth to give percent light penetration into the water column. Total amount of biologically available nitrogen (total inorganic nitrogen; TIN) was calculated by summing the concentrations of forms of biologically available nitrogen (N[H.sub.4.sup.+]-N+ N[O.sub.3.sup.2-]-N + N[O.sub.2.sup.-]-N). The ratio of TIN to biologically available phosphorus (SRP) and the ratio of TN:TP were calculated to estimate nutrient limitation for algae in the pelagic zone (Redfield 1934; Bayley and Prather 2003). The environmental variables used in our analysis were open water area, pH, maximum depth, water visibility, TN, TP, salinity, TDS, chlorophyll a, percent agriculture, and the estimated amount of SAV. Environmental variables were relativized by column maximum for each sampling period (Oksanen and others 2011).

To identify and describe patterns in the macroinvertebrate community, cluster analyses were performed using Ward's cluster method with Bray-Curtis (or Sorensen) distance measures (McCune and Grace 2002). Indicator species analysis (Dufrene and Legendre 1997) was also applied to help determine the level at which clustering should stop (McCune and Grace 2002). A Monte Carlo simulation (1000 permutations) was used to assess the significance of each macroinvertebrate taxon as an indicator (Dufrene and Legendre 1997). The presence of indicator taxa for each cluster indicates that the cluster comprises a valid group of wetlands with a distinct macroinvertebrate community. These analyses were used to identify and characterize macroinvertebrate community types in the BTZ.

Any taxa occurring in <2 wetlands for the sampling period of interest were removed prior to analysis, but all taxa sampled are reflected in Appendix 1 regardless of the frequency of occurrence. This prevented rare species from having a disproportionate effect on the outcome of the analyses. As well, prior to analysis, all macroinvertebrate and waterfowl data were transformed using log(x+1) to prevent extreme values from excessively influencing the results (McCune and Grace 2002).

Multi-response permutation procedure (MRPP) was used to confirm whether groups resulting from cluster analysis were significantly different based on macroinvertebrate and waterfowl community abundance data (McCune and Grace 2002). The Bray-Curtis distance metric was used along with 1000 permutations to assess significance between groups. Nonmetric Multidimensional Scaling (NMDS) ordinations, which arrange response variables in strictly species space with no assumed relation to environmental variables, were used to compare environmental variables (physical, limnological, and agricultural intensity) to the macroinvertebrate community.

NMDS and MRPP analyses were used to confirm that the clusters identified by cluster analysis were distinct macroinvertebrate community types, as well as to identify which environmental variables were associated with the different community types and species distributions. All NMDS ordinations were performed using the Bray-Curtis (or Sorensen) distance measure. The NMDS ordinates were started from a random position and the number of dimensions in the final NMDS was determined by examining how much stress (%) each additional dimension accounted for. Dimensionality was determined based on the point of diminishing returns with respect to how much the addition of another dimension decreased the overall stress value. Environmental vectors were added to the ordination to help define the environmental context of the wetland distribution. The length of the environmental vector is proportional to the correlation between the environmental variable and the ordination. Correlation between the distance in the ordination space and the original space was calculated (McCune and Grace 2002).

Macroinvertebrate groups identified in cluster and indicator species analyses were identified on the final NMDS ordinations of the macroinvertebrate abundance data to determine whether community types could be distinguished along environmental gradients. To compare the influence of the macroinvertebrate community on the composition of the waterfowl community, the macroinvertebrate clusters were overlaid onto the NMDS ordinations of the waterfowl data. The separation seen for the macroinvertebrate clusters when wetlands are plotted by waterfowl composition should indicate how waterfowl are responding to macroinvertebrate communities. Environmental variables were again overlaid as vectors to help determine which factors were important in influencing waterfowl distribution on BTZ wetlands. An additional vector representing macroinvertebrate abundance was also overlaid to determine whether waterfowl species were opportunistically responding to abundance of available food items rather than community types. Linear regression was also performed to determine the direct relationship between overall waterfowl and macroinvertebrate abundance in each month.

Environmental conditions (physical and limnological), macroinvertebrate and waterfowl density, and the species richness of each macroinvertebrate group that was identified from cluster analysis were compared to determine how the macroinvertebrate groups differed in each time period. The macroinvertebrate groups were compared using Kruskal-Wallis (K-W) analyses with post-hoc pairwise Wilcoxon rank sum tests and Bonferonni P-corrections at a significance level of [alpha] = 0.10. We acknowledge that our wetland sample size was small (n = 14), therefore it is difficult to discern true differences among groups. By relaxing the [alpha]-level to 0.10, we can compare groups on an initial and descriptive basis. May and August data were also compared using Kruskal-Wallis analyses to determine seasonal variation of environmental conditions, and the abundance and species richness of macroinvertebrates and waterfowl. Seasonal variation (May vs. August) of macroinvertebrate groups was not compared because macroinvertebrate community composition can change within a given wetland throughout the ice-free season.


Macroinvertebrates and Breeding Waterfowl Communities in May

A total of 64 macroinvertebrate taxa were collected from the 14 wetlands in May 2006 (see Appendix 1 for the complete list). Hyalella and Gammarus amphipods were dominant, accounting for 41 and 15% of all macroinvertebrates respectively. Chironomidae (subfamilies Chironominae and Tanypodinae) accounted for a further 17%. A total of 26 taxa were represented by a single individual and the number of taxa present in a single wetland ranged from 6 to 24. No single taxon was present in all 14 wetlands, but Hyalella and Chironominae were collected from 11 wetlands each. For subsequent analyses, 38 taxa present in more than 2 wetlands, with a cumulative average density of 1629 macroinvertebrates/[m.sup.3]/wetland were used (Table 1).

An average of 40 IBP of ducks/wetland were observed on the 14 wetlands in May. Ducks included 14 different species (7 dabbling ducks and 7 diving ducks), with diving ducks being more abundant ([bar.x] = 23.1 IBP/wetland) than dabbling ducks ([bar.x] = 17.2 IBP/wetland; Appendix 2). Mallards (Anas platyrhynchos) were the only species observed on all 14 wetlands.

Cluster Analysis--May

Cluster analysis, in conjunction with indicator species analysis and MRPP, identified 3 distinct wetland clusters based on macroinvertebrate abundance during the May sampling period (Fig. 1, Table 2). The 3 main community types were distinguished by the following dominant indicator species: Amphipoda (MC1), Diptera (MC2) and Sigara (MC3).

May Cluster 1 (MC1)--Amphipoda-dominated Wetlands.--MC1 (n = 5 wetlands) had the highest density of macroinvertebrates compared to MC2 (K-W test, [chi square] = 6.35, df = 2, P = 0.042, Table 1). MC1 was characterized by high densities of both Hyalella and Gammarus (indicators for the cluster, P = 0.001) and high densities of 3 Hirudinae taxa (Placobdella, Erpobdella, and Nephelopsis), 2 Coleoptera taxa (Dytiscus and Haliplus), Chaoborus, Enallagma, and Notonecta. Additionally, this community tended to have a low density of Gastropoda. MC1 also had the highest abundance of breeding Lesser Scaup and was the only cluster to lack Northern Shoveler during the breeding period (Table 3). Overall, these wetlands had 4 times more diving ducks than dabbling ducks, but this relationship was driven principally by abundance of Lesser Scaup (Table 1). However, abundance of total waterfowl, dabbling and diving ducks were not significantly different among the May macroinvertebrate clusters (Tables 1 and 2).

May Cluster 2 (MC2)--Diptera-dominated Wetlands.--MC2 (n = 5 wetlands) was characterized by high densities of Diptera (Tanypodinae [indicator for the cluster, P = 0.011], Ceratopogoninae [indicator for the cluster, P = 0.049], Chironominae, Prionocera, and Dixella), and Gastropoda (Armiger, Heliosoma, Valvat, Gyraulus, Promenetus, and Stagnicola). These wetlands also had high densities of Anisoptera (Anax, Somatochlora), Trichoptera (Trianenodes, Ptilostomis), and Caenis. MC2 lacked Coleoptera and Sigara. Though abundance of total waterfowl, dabbling and diving ducks, did not differ significantly among the macroinvertebrate communities (Table 1 and 2), MC2 wetlands were used by fewer diving ducks compared to other clusters. This relationship was driven by low numbers of Lesser Scaup, Ring-necked Duck (Athya collaris), and Ruddy Duck in MC2 (Table 3). The presence of Northern Pintail (Anas acuta) also characterized MC2 wetlands (Table 3).

May Cluster 3 (MC3)--Sigara-dominated Wetlands.--MC3 (n = 4 wetlands) was characterized by high densities of Sigara (indicator for the cluster, P = 0.008), Ilybius, Physa, and Phyrrhalta. Low densities or a complete lack of Coleoptera (Acilius and Dytiscus), Hirudinae (Erpobdella, Glossiphonia, and Nephelopsis), Trichoptera (Triaenodes, and Limnephilus), Notonecta, Somatochlora, Hyalella and Pisidium also helped define this community. Overall, MC3 had a significantly lower macroinvertebrate density than MC1 (K-W test, [chi square] = 6.35, df = 2, P = 0.042; Table 1). MC3 had the highest numbers of Mallard, Gadwall (Arias strepera), Blue-winged Teal (Anas discors), Northern Shoveler (indicator for the cluster, P = 0.022), Redhead (Aythya americana; indicator for the cluster, P = 0.048), Canvasback (Aythya valisineria), Bufflehead, and Ruddy Duck (Table 3).

Environmental Determinates of Wetland Communities in May

Sigara-dominated wetland basins (MC3) were significantly shallower (K-W test, [chi square] = 5.11, df = 2, P = 0.078; Table 1) than those in MC1 and MC2. Concentration of TIN, salinity, and TDS were significantly greater in MC3 wetlands than MC2 wetlands (TIN: K-W, [chi square] - 4.89, df = 2, P = 0.087; salinity: [chi square] = 7.77, df = 2, P = 0.021; TDS: [chi square] = 5.13, df = 2, P = 0.077; Table 1).


The final NMDS of the May macroinvertebrate community had 3 dimensions with a final stress of 11.02% (Fig. 2A). Maximum depth was a significant (P = 0.053) vector separating the macroinvertebrate community types. Maximum depth separated wetlands along axis 1, with shallower basins on the left and deeper basins on the right of the plot (Fig. 2A). MC1 wetlands were quite distinct from the other 2 clusters, suggesting that Amphipoda-dominated communities occurred in relatively deeper basins, while Diptera and Sigara communities were more prevalent in shallower basins (Fig. 2A).

The NMDS of breeding waterfowl communities had 2 dimensions, with a final stress of 9.60% (Fig. 2B). Environmental vectors were weak, with only the agriculture vector being marginally significant (P = 0.09). There was poor separation of waterfowl species among macroinvertebrate community types (Fig. 2B). No vector was found to adequately separate waterfowl species and macroinvertebrate community types along axis 1. Wetlands with low levels of agriculture and TP were found on the bottom of the plot, and those with higher levels were located on the top of the plot (Fig. 2B). Axis 2 also separated wetlands based on the amount of open water area ([R.sup.2] = 0.35, P = 0.12). Wetlands with more open water occurred toward the bottom of the plot, while wetlands with less open water were found toward the top of the plot (Fig. 2B). Results suggest that breeding Common Goldeneyes were most sensitive to high intensities of agriculture because they tended to occur on basins with more open water area and less agricultural impact. Conversely, breeding Canvasbacks were more abundant on small, productive basins surrounded by higher levels of agricultural activity (Fig. 2B). There was a positive association between TP and agriculture vectors because most agricultural land uses are a major source of TP enrichment in wetlands. Individual waterfowl species did not track macroinvertebrate abundance (NMDS vector, [R.sup.2] = 0.18, P = 0.36) at the scale of sampling in this study, nor did waterfowl species track macroinvertebrate community types based on poor separation of the clusters (Fig. 2B). This result is also supported by MRPP analyses that suggested waterfowl abundance did not differ based on macroinvertebrate community types (Table 2). However, overall breeding waterfowl abundance was significantly and positively associated with macroinvertebrate abundance ([R.sup.2]=0.62, P < 0.0001).

Macroinvertebrate and Molting Waterfowl Communities in August

During the molting period in August 2006, a total of 37 macroinvertebrate taxa were collected from the study wetlands (see Appendix 1 for a full list). Amphipoda continued to dominate the macroinvertebrate communities of BTZ wetlands, with Hyalella and Gammarus accounting for 45 and 25% of all macroinvertebrates collected, respectively. A further 14% of collected individuals were Chaoborus. Sigara and Hyalella were the most frequently occurring taxa and were found in 11 of the 14 surveyed wetlands. The number of taxa present in a single wetland ranged from 4 to 18. For subsequent analyses, 28 taxa sampled from more than 2 wetlands representing an average density of 2704.8 macroinvertebrates/[m.sup.3]/wetland were included (Table 1).

Molting waterfowl surveys identified 14 duck species using BTZ wetlands (7 dabbling ducks and 7 diving ducks) with an average of 81.6 ducks/wetland (Table 1). Dabbling ducks were 4 times more numerous than diving ducks during molt (62.1 waterfowl/wetland and 15.4 waterfowl/wetland, respectively; Table 1) with Mallards, Blue-winged Teal, and American Widgeon accounting for a total of 50% of the individuals observed (17, 17 and 16%, respectively). No single species was observed on all wetlands, but Mallards were present on 13 of the 14 wetlands.

Cluster Analysis--August

Cluster analysis, in conjunction with indicator species analysis and MRPP, identified 3 distinct wetland clusters based on macroinvertebrate abundances during the molting period (Fig. 3, Table 2). The 3 main community types were distinguished by dominant indicator species: Amphipoda (AC1), Notonecta (AC2), and Chaoborus-Sigara (AC3) dominated wetlands. Peak abundance of macroinvertebrate species varied between May and August in each wetland, therefore group membership to a specific aquatic macroinvertebrate community for individual wetlands was not consistent between May and August (Figs. 1 and 3).

August Cluster 1 (AC1)--Amphipoda-dominated Wetlands.--AC1 (n = 5 wetlands) was characterized by high densities of Amphipoda (Hyallela [indicator for the cluster, P = 0.022] and Gammarus), Hirudinae (Erpobdella, Nephelopsis and Mooreobdella), Ephemeroptera (Caenis and Cloeon), Gastropoda (Physa, Promenetus, and Gyraulus), Coleoptera (Brychius, and Ilybius), and Enallagma; but lacked Agabus and Chaoborus. There were no significant differences in waterfowl abundance among macroinvertebrate clusters for overall waterfowl (K-W test, [chi square] = 1.22, df = 2, P = 0.54), dabbling ducks (K-W test, [chi square] = 1.28, df = 2, P = 0.53), and diving ducks (K-W test, [chi square] = 0.35, df = 2, P = 0.84; Table 1). However, AC1 wetlands supported particularly high numbers of Blue-winged Teal, Buffiehead, and Common Goldeneye. These wetlands lacked American Green-winged Teal (Anas crecca), and had very low numbers of Ring-necked Duck (Table 3).

August Cluster 2 (AC2)--Notonecta-dominated Wetlands.--AC2 (n = 2 wetlands) was characterized by high densities of Notonecta (indicator for the cluster, P = 0.021) and Agabus. Additionally, the presence of Physa and Chaoborus, coupled with low densities of Enallagma and Sigara, and the absence of Ephemeroptera (Caenis and Cloeon), Hirudinae (Eropbdella, Helobdella, and Mooreobdella), Trichoptera (Nemotaulius and Triaenodes), Hyalella, Ilybius, and Somatochlora further defined this cluster. With only 2 wetlands representing this macroinvertebrate community, there was very high variability in overall waterfowl abundance (4 to 74 birds/wetland), dabbling ducks (0 to 45 birds/wetland), and diving ducks (2 to 27 birds/wetland). It was the only cluster to support Canvasback (Table 3).

August Cluster 3 (AC3)--Chaoborus-Sigara-dominated Wetlands.--AC3 (n = 7 wetlands) were characterized by the presence of Anax, Cymatia, and Glossiphonia. Additionally, high densities of Sigara, Chironominae, Chaoborus (indicator for the cluster, P = 0.001), Tanypodinae, Helobdella, Hyallela, and Somatochlora combined with the absence of Gammarus were indicative of AC3 wetlands. Green-winged Teal were unique to these wetlands, but AC3 wetlands were also characterized by the relatively high abundance of molting Mallard, Ring-necked Duck, and Ruddy Duck (Table 3).

Environmental Determinates of Wetland Communities in August

Due to low sample sizes and unequal cluster sizes (ACI: n = 5; AC2: n = 2; AC3: n = 7), differences among wetland communities were difficult to detect. There was little temporal stability in macroinvertebrate communities within the BTZ wetlands that we sampled. No environmental variable significantly distinguished the August macroinvertebrate community types (Table 1).

During the molting period, the final NMDS for macroinvertebrate abundance had 2 dimensions with a final stress of 13.63%. Macroinvertebrate community types, particularly Amphipod-dominated (AC1) and Chaoborus-Sigara-dominated communities (AC3), were separated along several environmental gradients (Fig. 4A). Wetlands were separated based on TDS ([R.sup.2] = 0.37, P = 0.084) along axis 1, and a TP ([R.sup.2] = 0.72, P = 0.001) and open water area gradient ([R.sup.2] = 0.45, P = 0.046) along axis 2 (Fig. 4A). Relatively low salinity and TDS wetlands occurred toward the left on Axis 1, and more saline and higher TDS wetlands occurred to the right (Fig. 4A). Along Axis 2, wetlands with more open water and lower concentrations of TP were located toward the top, and more eutrophic wetlands with less open water near the bottom (Fig. 4A). AC1 communities occurred primarily in wetlands with more open water; AC2 communities occurred in wetlands with lower TDS and salinity; AC3 communities occurred in wetlands with less open water, increased concentrations of TP, salinity, and TDS, and increased agricultural intensity (Fig. 4A).



The NMDS of molting duck abundance had 2 dimensions with a final stress of 7.78% (Fig. 4B). There was no clear separation among clusters indicating that individual species of molting waterfowl were not specifically tracking macroinvertebrate community types nor tracking macroinvertebrate abundance ([R.sup.2] = 0.10, P = 0.57, vector not shown; Fig 4B). Axis 2 represents a salinity gradient with basins with greater salinity occurring toward the bottom of the plot. Diving ducks, such as Bufflehead and Common Goldeneye, appeared to occur primarily in less saline basins. Chaoborus--Sigara-dominated communities (AC3) occurred in relatively more saline conditions, while Notonecta-dominated communities (AC2) occurred in relatively freshwater conditions (Fig. 4B). As was observed during the breeding period, macroinvertebrate community types were not good predictors of individual waterfowl species on BTZ wetlands, but there was a significantly positive relationship between overall molting waterfowl abundance and macroinvertebrate abundance ([R.sup.2] = 0.99, P < 0.0001).


Macroinvertebrate Communities in May and August

We documented 5 distinct aquatic macroinvertebrate communities in the BTZ wetlands sampled in this study including: Amphipoda-dominated communities (MC1 and AC1); Diptera-dominated communities (MC2); Notonecta-dominated communities (AC2); Sigara-dominated communities (MC3); and Chaoborus-Sigara-dominated communities (AC3). However, given the diversity of wetland types in the BTZ and geographic scale of this ecoregion in western Canada, as well as relatively low sample sizes in this study, it is likely that future and larger scale studies will document additional aquatic invertebrate communities that may serve as better predictors of the waterfowl or other vertebrate communities using these systems. It was also apparent that aquatic invertebrate communities were dynamic and could show temporal shifts in species dominance resulting in wetlands differing in their community affiliation between the May and August sampling periods. Our results provide additional support that macroinvertebrate community composition can change within a given wetland throughout the ice-free season (Lahr and others 1999; Culioli and others 2006). Because specific macroinvertebrate populations peak at different times during the open-water period, it would be more difficult for waterfowl to track macroinvertebrate communities, particularly during molt when ducks undergo simultaneous remigial molt rendering them flightless.

In addition to the diversity of wetland types in this region, sweep-net sampling for macroinvertebrates in wetlands, especially in highly vegetated habitats, can underestimate abundance and diversity (Meyer and others 2011). Because aquatic macroinvertebrate communities have never previously been described in the BTZ of western Canada, our main objective was to provide an initial description of these communities along a gradient in agricultural encroachment. The sweep-net method was the preferred method given limited sampling and post-processing time in this study. More detailed sampling that combines sweep-net and additional sampling techniques such as coring or drop trapping is recommended for future research to achieve more accurate data on macroinvertebrate abundance, biomass, and diversity (Meyer and others 2011).

Macroinvertebrate communities were not clearly related to environmental conditions at the scale of sampling in this study. Our initial results suggest Sigara-dominated communities in May occur in shallow, more saline basins with relatively greater concentrations of TIN and phosphorus (TP and SRP), TDS, and agricultural intensity. However, visibility in the water column of Sigara-dominated wetlands was also the highest at 80%, which is in direct contrast to levels of phosphorus. These Sigara-dominated wetlands were extremely shallow, with maximum depth ranging from 0.6 to 1.1 m, whereas the maximum depth in wetlands inhabited by the other 2 macroinvertebrate communities was generally >1 m and up to 6 m deep. Depending on various factors such as water color, amount of detritus and other factors, visibility in the water column could be obscured in deeper basins, whereas visibility in very shallow wetlands was usually close to 100%.

Phosphorus in its various forms can be an important factor determining the composition of aquatic macroinvertebrate communities (McCormick and others 2004). It is important to recognize that shallow open-water wetlands in Alberta can have naturally high levels of phosphorus in their surface waters, even in the absence of agricultural runoff (Bayley and others 2007). Sigara and Chaoborus-Sigara communities were found in wetlands with very high levels of TP ([bar.x] = 993.7 and 819 [micro]g/L in May and August, respectively), whereas Amphipoda-dominated communities occurred in wetlands with moderate levels of TP ([bar.x] = 240.8 and 140.7 [micro]g/L in May and August, respectively). Diptera- and Notonecta-dominated communities occurred in wetlands with lower TP ([bar.x] = 158.4 and 112.9 [micro]g/L in May and August, respectively; Table 1). Typically wetlands surrounded by a higher percentage of agriculture also have higher phosphorus concentrations (Flanagan and Richardson 2010). Recent research has shown that Sigara can be an indicator species for burned swamp sites with elevated phosphorus levels and dense algal blooms (Beganyi and Batzer 2011). Highly mobile Sigara often use anoxic or otherwise-inhospitable wetlands as hunting grounds because they bring an air bubble into the water with them and therefore do not require oxygen from the wetland itself. Sigara also have shown a preference for wetlands that are saline, anoxic, and have limited vegetation because wetlands with these characteristics tend to contain few parasites (Murkin and Ross 2000). However, further research is required to determine whether Sigara-dominated communities can be consistently used as indicators of enriched and agriculturally impacted wetlands in the BTZ.


Effect of Macroinvertebrate Community on Waterfowl Community Composition

We expected the waterfowl community to show some distinct relationships to aquatic macroinvertebrate communities, especially in May when macroinvertebrates typically represent a larger proportion of the diets for breeding waterfowl. However, based on our scale of sampling, the waterfowl species on BTZ wetlands were not closely correlated with macroinvertebrate communities. In general, it appeared that waterfowl communities were responding more to physical features of wetland basins, such as water depth, rather than macroinvertebrate communities. The lack of correspondence between waterfowl and macroinvertebrate communities may be explained by the high mobility of ducks in the breeding season and their ability to easily forage on several wetlands in a day (Rotella and Ratti 1992; Haig and others 1998) to meet their daily nutrient demands. Movement between basins is further facilitated by the rather high density of wetlands in many parts of the BTZ. Additionally, many species of waterfowl consume plant material, such as seeds or tubers, as part of their diet (Noyes and Jarvis 1985; Swanson and others 1985; DuBowy 1988; Knapton and Pauls 1994), so they may be responding to a combination of the macroinvertebrate and plant communities found in and around each wetland. Alternatively, protein and mineral demands of waterfowl, which are often met by consumption of macroinvertebrates, may be satisfied simply by consuming a wide variety of taxa.

Another confounding effect pertains to the important roles of water depth, wetland area, and habitat diversity in structuring macroinvertebrate communities and diversity (Zimmer and others 2000; Stenert and others 2008). Macroinvertebrate abundance is highly correlated with shallow depths and high SAV abundance, while species richness is highly correlated with increasing depth, wetland area, and habitat diversity (Ricklefs and Lovette 1999; Stenert and others 2008). Habitat diversity and structural complexity can also influence foraging efficiency of waterfowl. For example, extensive emergent vegetation could decrease the area of open water required for efficient foraging by some species of diving ducks (Anteau and Afton 2009), while abundant emergent vegetation is often a positive predictor of dabbling duck abundance (Webb and others 2010).

Waterfowl tend to be very opportunistic feeders; however, NMDS showed only a very weak association between individual waterfowl species and macroinvertebrates, while overall waterfowl abundance was highly associated with macroinvertebrate abundance. Fish presence often has a negative impact on waterfowl abundance because of competition for macroinvertebrate food resources (Zimmer and others 2002), particularly in BTZ wetlands with large-bodied fish (Epners and others 2010). Consequently, waterfowl abundance was highest in highly productive, shallow, fishless lakes in the BTZ (Epners and others 2010). This observation is further supported by our study, which indicates that waterfowl abundance was highest on wetlands with higher macroinvertebrate densities, and sites with the highest macroinvertebrate abundance in the BTZ are nearly always fishless.

Although waterfowl communities as a whole were not closely linked with macroinvertebrate communities, some individual waterfowl species could be closely associated with the abundance of specific macroinvertebrates in BTZ wetlands. For example, during the breeding and molting periods, Lesser Scaup often feed extensively on Amphipoda (Afton and Hier 1991), and this was supported by the high numbers of Lesser Scaup we found on Amphipoda-dominated wetlands in May and August. Additionally, Ring-necked Ducks whose diet is composed primarily of Chironomidae and Pelecoptera (Hohman 1985) were associated with BTZ wetlands containing higher densities of those groups in both May and August.

Influence of Agriculture

The amount of agricultural land immediately surrounding BTZ wetlands (1.6-km radius) was related to the composition of the macroinvertebrate community. However, it is important to recognize that increased agriculture was closely correlated with increased TP levels. Increased concentrations of phosphorus in wetlands occurring within agriculturally dominated landscapes likely originates from wind-blown soil deposition into the wetlands (Skagen and others 2008), and land clearing and fertilization that increases nutrient loading (Heathwaite and others 1996; Carpenter and others 1998). Changes in the levels of phosphorus and the ratio of nitrogen to phosphorus appear to be the primary parameters altered in wetlands associated with increased agricultural encroachment.

Increased phosphorous levels can alter emergent wetland vegetation communities by changing the dominant vegetation from grasses to cattail (Typha spp.) (Craft and others 1995; McCormick and others 2004). Similarly, increased phosphorus levels alter SAV communities through trophic cascade effects due to eutrophication and direct competition with algae for available light (Lacoul and Freedman 2006; Sondergaard and others 2010). Changes in the emergent and SAV communities modify the available structure, habitat complexity, and available detritus used by aquatic macroinvertebrates. While some taxa, such as Amphipoda and Gastropoda, respond negatively to increased phosphorus availability (McCormick and others 2004), other taxa such as Corixidae tend to increase in abundance (Batzer and Resh 1992). Additionally, increased phosphorus tends to shift the phytoplankton community toward green and blue-green algae-dominated systems, while decreasing the amount of diatoms (Tilman and others 1986). Many macroinvertebrate taxa consume diatoms, but very few are able to use green or blue-green algae as a food source (Rader and Richardson 1992). Changes in the phytoplankton and SAV communities associated with increasing phosphorus likely led to shifts from more herbivorous and fully aquatic taxa such as Amphipoda, Gastropoda and Diptera larvae to more predatory and terrestrially mobile taxa such as Sigara and Notonecta. However, wetlands in the BTZ region are exceptionally nutrient-rich even in the absence of agricultural encroachment (Bayley and others, unpubl, data). It is possible for these naturally eutrophic to hypereutrophic, shallow wetlands to respond with increased phytoplankton production while maintaining relatively high water quality and abundant SAV, whereas nutrient enrichment in most wetlands can trigger more dramatic changes in vegetation communities thus potentially affecting other trophic levels (Verhoeven and others 2006). With continued agricultural expansion in the BTZ, it is likely that some wetlands may reach a critical nutrient load that could trigger abrupt changes throughout these aquatic communities. Future research should try to determine if such thresholds exist and if so, the consequences of reaching and exceeding them on the macroinvertebrate and waterfowl communities of BTZ wetlands.

There was no evidence at our scale of sampling that agricultural intensity negatively affected settling patterns for breeding and molting waterfowl. Despite agricultural activities within the BTZ, these wetlands continue to attract many waterfowl during the breeding and postbreeding periods. However, we did not examine key vital rates such as nest success or survival of nesting females and broods that are most likely to be negatively affected by increasing agricultural intensity (Lokemoen and Beiser 1997; Podruzny and others 2002). While it is possible that agriculture may attract some waterfowl species through nutrient enrichment (Longcore and others 2006), wetlands surrounded primarily by agriculture may function as an ecological trap due to negative effects on overall fitness and success. Future research that directly examines nesting female survival, nest success, and brood survival in the BTZ will be required to better assess relationships between waterfowl, macroinvertebrate communities, and overall impacts of agricultural expansion on waterfowl populations in this rapidly changing region of the Boreal Plains.
APPENDIX 1. Aquatic macroinvertebrates collected from Boreal
Transition Zone wetlands (n = 14) in central Alberta during May
and August, 2006. NMDS key to aquatic macroinvertebrate taxonomic
codes used in Figures 2 and 4.

Family            Genus                            NMDS Code

Aeshnidae         Anax                             Anax
Aeshnidae         Aeshna *
Baetidae          Baetis *
Baetidae          Centroptilum *
Baetidae          Clown                            Cloeon
Brachycentridae   Amiocentrus *
Caenidae          Caenis                           Caenis
Ceratopogonidae   Ceratopogoninae (+)              Cerato
Chaoboridae       Chaoborus-Sigara                 Chaobo
Chironomidae      Chironomidae ([double dagger])   Chiron
Chironomidae      Tanypodinae ([double dagger])    Tanypo
Chrysomelidae     Pyrrhalta *
Coenagrionidae    Enallagma                        Enalla
Coenagrionidae    Coenagrion (+)                   Coenag
Corduliidae       Somatochlora                     Somato
Corixidae         Sigara                           Sigara
Corixidae         Cymatia *                        Cymati
Culicidae         Cnlex *
Culicidae         Mansonia *
Curculionidae     ID not possible *
Dixidae           Dixella                          Dixell
Dytiscidae        Ilybius                          Ilybiu
Dytiscidae        Dytiscus                         Dytisc
Dytiscidae        Graphoderus                      Grapho
Dytiscidae        Acilius                          Aciliu
Dytiscidae        Agabus                           Agabus
Dytiscidae        Colymbetes *
Dytiscidae        Hydaticus *
Dytiscidae        Rhantus *
Empididae         ID not possible *
Erpobdellidae     Erpobdella                       Erpobd
Erpobdellidae     Nephelopsis                      Nephel
Erpobdellidae     Dina *
Erpobdellidae     Mooreobdella *                   Mooreo
Gammaridae        Gammarus                         Gammar
Glossiphoniidae   Glossiphonia                     Glossi
Glossiphoniidae   Placobdella                      Placob
Glossiphoniidae   Helobdella                       Helobd
Glossiphoniidae   Alboglossiphonia (+)
Glossiphoniidae   Theromyzon (+)
Haliplidae        Haliplus                         Halipl
Haliplidae        Brychius                         Brychi
Hyalellidae       Hyalella                         Hyalel
Hydrophilidae     Laccobius *
Leptoceridae      Triaenodes                       Triaen
Leptoceridae      Mystacides *
Lestidae          Lestes *
Limnephilidae     Limnephilus (+)                  Limnep
Limnephilidae     Arctopora *
Limnephilidae     Pedomoecus (+)
Limnephilidae     Nemotaulius                      Nemota
Lymnaeidae        Bakerilymnaea                    Bakeri
Lymnaeidae        Stagnicola (+)                   Stagni
Lymnaeidae        Lymnaea * (+)
Notonectidae      Notonecta                        Notone
Phryganeidae      Banksiola *
Phryganeidae      Ptilostomis
Physidae          Physa                            Physa
Planorbidae       Gyraulus                         Gyraul
Planorbidae       Promenetus                       Promen
Planorbidae       Armiger                          Armige
Planorbidae       Helisoma                         Heliso
Planorbidae       Menetus *
Psychodidae       Pericoma *
Sphaeriidae       Pisidium (+)                     Pisidi
Stratiomyidae     ID not possible *
Tipulidae         Prionocera                       Priono
Tipulidae         Limoniinae *
Valvatidae        Valvat                           Valvat

* Indicates taxa present in May, but found in only 1 wetland and
was not included in the analyses.

(+) Indicates taxa present in August, but found in only 1 wetland
and was not included in the analyses.

([double dagger]) Indicates classification at the subfamily

APPENDIX 2. Duck (Anatinae) species present on Boreal Transition
Zone wetlands (n = 14) in central Alberta during the breeding
(May) and molting (August) periods in 2006. NMDS key to waterfowl
taxonomic codes used in Figures 2 and 4.

                                                   Seasonal presence
                                                    (% of wetlands)

                      NMDS                        Breeding   Molting
    Common name       code    Scientific name      (May)     (August)

Dabbling ducks:
  Mallard             MALL   Anas platyrhynchos      100.0      92.9
  Gadwall             GADW   Anas strepera            62.5      64.3
  American Wigeon     AMWI   Anas americana           81.3      50.0
  American Green-     AGWT   Anas crecca              56.3      14.3
    winged Teal
  Blue-winged Teal    BWTE   Anas discors             87.5      78.6
  Northern Shoveler   NOSH   Anas clypeata            43.8      71.4
  Northern Pintail    NOPI   Anas acuta                6.3       7.1
Diving ducks:
  Redhead             REDH   Aythya americana         50.0       7.1
  Canvasback          CANV   Aythya valisineria       43.8       7.1
  Scaup               SCAU   Aythya affinis &         87.5      42.9
                               marila *
  Ring-necked Duck    RNDU   Aythya collaris          75.0      50.0
  Common Goldeneye    COGO   Bucephala clangula       25.0      35.7
  Bufflehead          BUFF   Bucephala albeola        87.5      35.7
  Ruddy Duck          RUDU   Oxyura jamaicensis       62.5      42.9

* Primarily Lesser Scaup based on
typical breeding and molting distribution.


We would like to thank the Alberta North American Waterfowl Management Plan Partnership and Ducks Unlimited Canada for funding this project. A NSERC Discovery Grant provided additional funding to Suzanne Bayley. This project was supported by the dedicated efforts of Mike Ranger, Traci Morgan, Jalon Leendertse, Madison Kobyrn, and Arielle Kobym in the field, and Nicole Hopkins in the Ducks Unlimited GIS lab.


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* Unpublished

Submitted 10 February 2011, accepted 15 November 2011. Corresponding Editor: Joan Hagar.


Department of Biological Sciences, University of Calgary, Calgary, AB T2N 1N4;


Ducks Unlimited Canada, 17915-118 Avenue, Edmonton, AB T5S 1L6


Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9
TABLE 1. Means of environmental variables, macroinvertebrate
density and diversity, and waterfowl abundance for Boreal
Transition Zone wetlands in central Alberta, 2006. The mean for
each month is presented in the respective overall column. Clusters
are represented by MCI, MC2, MC3, AC1, AC2, and AC3. The NMDS code
corresponds to the codes used in Figures 2 and 4.

                               NMDS code   Units of measure

Number of wetlands                         n
Open water area                Area        ha
pH                             pH          pH units
Maximum depth                  Maxdep      cm
Visibility (Secchi:maximum     Vis         Percent
Total nitrogen                 TN          [micro]g/L
Total phosphorus               TP          [micro]g/L
Ratio of TN:TP                 TN:TP       NA
Soluble reactive phosphorus    SRP         [micro]g/L
Total inorganic nitrogen       TIN         [micro]g/L
Ratio of TIN:SRP               TIN:SRP     NA
Salinity                       Sal         mg/L
Total Dissolved Solids         IDS         mg/L
Chlorophyll [alpha]            Chl         [micro]g/L
Agriculture                    Agri        Percent
Submersed aquatic vegetation   Veg         Ordinal rank
Macroinvertebrate density                  n/[m.sup.3]
Macroinvertebrate diversity                Taxa/wetland
Total waterfowl abundance                  May: IBP/wetland
                                           August: n/wetland
Dabbling duck abundance                    As above
Diving duck abundance                      As above


                                   MC1           MC2          MC3

Number of wetlands                5             5             4
Open water area                  15.3          15.1          17.2
pH                                9.0           8.7           9.4
Maximum depth                   238.8 (a)     125.0 (ab)     83.5 (b)
Visibility (Secchi:maximum       50.1          73.6          80.0
Total nitrogen                 3406.0        2273.0        3115.0
Total phosphorus                240.8         158.4         993.7
Ratio of TN:TP                   22.8          37.2          29.3
Soluble reactive phosphorus     131.7          96.2         780.8
Total inorganic nitrogen        335.2 (ab)     30.0 (a)     401.0 (b)
Ratio of TIN:SRP                  8.1           7.1           4.3
Salinity                        481.3 (ab)    368.9 (a)     581.9 (b)
Total Dissolved Solids          276.8 (ab)    269.0 (a)     382.8 (b)
Chlorophyll [alpha]              17.7           6.4           2.0
Agriculture                      46.4          28.5          67.8
Submersed aquatic vegetation      2.8           3.2           3.2
Macroinvertebrate density      2851.4 (a)    1357.1 (ab)    441.1 (b)
Macroinvertebrate diversity      12.8          18.2          11.0
Total waterfowl abundance        41.0          29.9          53.2
Dabbling duck abundance           7.9          14.7          20.2
Diving duck abundance            33.0          15.2          33.0


                                AC1      AC2      AC3

Number of wetlands                5        2        7
Open water area                  22.6     15.3     11.1
pH                                9.5      8.5      8.5
Maximum depth                   104.0    389.5     86.7
Visibility (Secchi:maximum       57.8     25.6     73.5
Total nitrogen                 4074.0   4500.0   3818.6
Total phosphorus                140.7    112.9    819.0
Ratio of TN:TP                   45.4     39.9     18.6
Soluble reactive phosphorus      41.0     10.2    637.8
Total inorganic nitrogen         50.8    178.4    301.3
Ratio of TIN:SRP                  7.7     13.4      1.4
Salinity                        466.8    459.4    518.2
Total Dissolved Solids          377.6    335.5    345.7
Chlorophyll [alpha]              33.0     57.5     42.2
Agriculture                      32.4     40.2     57.6
Submersed aquatic vegetation      2.5      1.2      3.1
Macroinvertebrate density      3741.8   1029.8   2442.7
Macroinvertebrate diversity       9.6      5.0     11.9
Total waterfowl abundance        88.6     39.0     88.7
Dabbling duck abundance          69.4     22.5     68.3
Diving duck abundance            14.6     14.5     16.3

                                  May         August
                                Overall      Overall

Number of wetlands               14           14
Open water area                  15.8         15.8
pH                                9.0          8.9
Maximum depth                   153.8        136.1
Visibility (Secchi:maximum       67.0         61.1
Total nitrogen                 2918.2 (a)   4007.1 (b)
Total phosphorus                426.5        475.9
Ratio of TN:TP                   27.8         31.2
Soluble reactive phosphorus     304.5        335.0
Total inorganic nitrogen        245.5        194.3
Ratio of TIN:SRP                  6.6          5.4
Salinity                        469.9        491.4
Total Dissolved Solids          304.3        355.6
Chlorophyll [alpha]               9.2 (a)     41.1 (b)
Agriculture                      46.1         46.1
Submersed aquatic vegetation      3.0 (a)      2.6 (b)
Macroinvertebrate density      1629.1       2704.8
Macroinvertebrate diversity      14.2 (a)     10.1 (b)
Total waterfowl abundance        40.3         81.6
Dabbling duck abundance          17.2 (a)     62.1 (b)
Diving duck abundance            23.1         15.4

Superscripts indicate significant Kruskal-Wallis analyses with
post-hoc pairwise Wilcoxon rank sum test and bonferonni P-
correction (P < 0.10) to determine monthly variation among
macroinvertebrate clusters, and to compare between May and August
to determine seasonal variation of overall environmental
conditions, abundance and diversity of macroinvertebrates, and
waterfowl abundance.

TABLE 2. Multi-response permutation procedure (MRPP) summary of
macroinvertebrate community types in Boreal Transition Zone
wetlands (n = 14) in central Alberta based on macroinvertebrate
and waterfowl abundance.

                            Cluster 1 (May   Cluster 2 (May:
                             and August:     Diptera, August:
                              Amphipoda)        Notonecta)

Number of lakes in May      5                5
May macroinvertebrate       0.6111           0.5483
  abundance, [delta]
May waterfowl               0.3743           0.6158
  abundance, [delta]
Number of lakes in August   5                2
August macroinvertebrate    0.6213           0.4407
  abundance, [delta]
August waterfowl            0.4488           1.0000
  abundance, [delta]

                            Cluster 3 (May:               Chance-
                            Sigara, August:              corrected
                              Chaoborus-                within group
                                Sigara)          P      agreement, A

Number of lakes in May      4
May macroinvertebrate       0.6215            <0.0000    0.1335
  abundance, [delta]
May waterfowl               0.2926             0.0600    0.0672
  abundance, [delta]
Number of lakes in August   7
August macroinvertebrate    0.5148            <0.0000    0.1678
  abundance, [delta]
August waterfowl            0.5877             0.5100   -0.0020
  abundance, [delta]

TABLE 3. Summary of waterfowl species in each macroinvertebrate
cluster. Values indicate the average number of indicated
breeding pairs-wetland in May and average number of molting
individuals-wetland in August and standard errors ([+ or -]).
Waterfowl species codes are in Appendix 2; UNDA = unidentified
dabbling duck; UNDI = unidentified diving duck; UNDU =
unidentified duck.


           Amphipoda            Diptera             Sigara
Code      (MCl, n = 5)        (MC2, n = 5)       (MC3, n = 4)

MALL    2.0 [+ or -] 0.6    2.8 [+ or -] 1.2   3.7 [+ or -] 2.1
GADW    0.5 [+ or -] 0.4    0.9 [+ or -] 0.6   2.0 [+ or -] 0.7
AMWI    2.2 [+ or -] 0.7    1.7 [+ or -] 0.9   1.2 [+ or -] 0.5
AGWT    0.4 [+ or -] 0.3    1.2 [+ or -] 0.6   0.8 [+ or -] 0.3
BWTE    2.9 [+ or -] 0.6    4.0 [+ or -] 1.9   6.8 [+ or -] 2.0
NOSH    0.0 [+ or -] 0.0    3.3 [+ or -] 2.1   5.8 [+ or -] 1.2
NOPI    0.0 [+ or -] 0.0    0.8 [+ or -] 0.8   0.0 [+ or -] 0.0
REDH    0.8 [+ or -] 0.8    1.6 [+ or -] 1.1   3.6 [+ or -] 0.8
CANV    0.4 [+ or -] 0.3    0.3 [+ or -] 0.2   0.8 [+ or -] 0.5
SCAU   19.1 [+ or -] 5.5    4.1 [+ or -] 1.8   9.2 [+ or -] 1.6
RNDU    2.9 [+ or -] 1.0    0.8 [+ or -] 0.2   3.5 [+ or -] 1.5
COGO    1.2 [+ or -] 1.2    3.7 [+ or -] 3.7   4.6 [+ or -] 4.6
BUFF    3.9 [+ or -] 1.4    3.4 [+ or -] 1.3   4.2 [+ or -] 1.7
RUDU    4.8 [+ or -] 3.5    1.5 [+ or -] 0.9   7.0 [+ or -] 1.9
UNDA    0.0 [+ or -] 0.0    0.0 [+ or -] 0.0   0.0 [+ or -] 0.0
UNDI    0.0 [+ or -] 0.0    0.0 [+ or -] 0.0   0.0 [+ or -] 0.0
UNDU    0.0 [+ or -] 0.0    0.0 [+ or -] 0.0   0.0 [+ or -] 0.0


           Amphipoda            Notonecta         Chaoborus-Sigara
Code      (AC1, n = 5)         (AC2, n = 2)         (AC3, n = 7)

MALL   10.2 [+ or -] 5.2     7.0 [+ or -] 7.0    19.1 [+ or -] 11.4
GADW    8.0 [+ or -] 4.1     1.5 [+ or -] 1.5     6.9 [+ or -] 4.5
AMWI   12.6 [+ or -] 12.6    0.0 [+ or -] 0.0    18.6 [+ or -] 10.1
AGWT    0.0 [+ or -] 0.0     0.0 [+ or -] 0.0     1.3 [+ or -] 1.1
BWTE   18.4 [+ or -] 8.5     1.0 [+ or -] 1.0    12.9 [+ or -] 5.9
NOSH    8.8 [+ or -] 2.9     3.0 [+ or -] 3.0     5.6 [+ or -] 2.5
NOPI    1.2 [+ or -] 1.2     0.0 [+ or -] 0.0     0.0 [+ or -] 0.0
REDH    0.0 [+ or -] 0.0     0.0 [+ or -] 0.0     2.1 [+ or -] 2.1
CANV    0.0 [+ or -] 0.0     2.0 [+ or -] 2.0     0.0 [+ or -] 0.0
SCAU    6.2 [+ or -] 4.2     7.5 [+ or -] 7.5     1.7 [+ or -] 1.1
RNDU    0.4 [+ or -] 0.4     2.5 [+ or -] 2.5     3.7 [+ or -] 1.5
COGO    2.8 [+ or -] 2.6     0.5 [+ or -] 0.5     1.7 [+ or -] 1.4
BUFF    3.8 [+ or -] 1.8     0.5 [+ or -] 0.5     0.7 [+ or -] 0.4
RUDU    0.8 [+ or -] 0.6     0.0 [+ or -] 0.0     5.1 [+ or -] 4.2
UNDA   10.2 [+ or -] 7.5    10.0 [+ or -] 10.0    4.0 [+ or -] 2.3
UNDI    0.6 [+ or -] 0.6     1.5 [+ or -] 0.5     1.1 [+ or -] 0.8
UNDU    4.6 [+ or -] 0.9     2.0 [+ or -] 0.0     4. [+ or -] 1.8
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Author:Silver, Carly A.; Thompson, Jonathan E.; Wong, Agnes S.; Bayley, Suzanne E.
Publication:Northwestern Naturalist: A Journal of Vertebrate Biology
Article Type:Report
Geographic Code:1USA
Date:Mar 22, 2012
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