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Integrating burrowing crayfish and waterfowl conservation management on moist-soil wetlands

Published online by Cambridge University Press:  04 March 2022

Caitlin C Bloomer*
Affiliation:
Illinois Natural History Survey, Prairie Research Institute, 1816 S. Oak Street, Champaign, IL61820, USA University of Illinois Urbana-Champaign, W-503 Turner Hall, 1102 South Goodwin Ave, Urbana, IL61801, USA
Christopher A Taylor
Affiliation:
Illinois Natural History Survey, Prairie Research Institute, 1816 S. Oak Street, Champaign, IL61820, USA
Robert J Distefano
Affiliation:
Missouri Department of Conservation, 3500 E Gans Road, Columbia, MO65201, USA
*
Author for Correspondence: Caitlin C Bloomer, Email: bloomer3@illinois.edu
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Summary

The North American Waterfowl Management Plan highlights the importance of enhancing waterfowl habitat for productivity and resilience. Many forms of land management are conducted in wetlands to support the diverse communities of waterfowl and other species. Primary burrowing crayfish are also abundant and important in these environments, but little research is available assessing the effects of waterfowl land management on primary burrowers. We examined the response of the digger crayfish, Creaserinus fodiens, to the common vegetation management practices of mowing and disking at waterfowl conservation areas in south-eastern Missouri. Our results demonstrated that at a fine scale, crayfish density was affected by only canopy cover. We also highlighted distributional effects of landscape-level environmental variables and suggested that habitat generalists were tolerant of vegetation management, responding more to vegetation composition and broader landscape effects. We discuss wetlands conservation practices and suggest that burrowing crayfish management would integrate well with some current management strategies for waterfowl.

Type
Report
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation

Introduction

Burrowing crayfish populate most aquatic and semi-aquatic habitats in North America, including swamps, floodplain forests and prairies (Abell et al. Reference Abell, Olson, Dinerstein, Eichbaum, Hurley and Diggs2000). They provide important ecosystem functions including soil mixing and aeration (Richardson Reference Richardson1983, Stone Reference Stone1993), habitat provision (Williams et al. Reference Williams, Williams and Hynes1974, Pintor & Soluk Reference Pintor and Soluk2006) and serving key trophic roles (Hobbs Reference Hobbs1993). However, the paucity of data on these organisms is well established (Moore et al. Reference Moore, DiStefano and Larson2013, Bloomer et al. Reference Bloomer, DiStefano and Taylor2021). There are often not enough distribution or natural history data on burrowing crayfish to inform spatial patterns or direct surveys (Welch & Eversole Reference Welch and Eversole2006). Habitat loss through land-use change has been highlighted as a specific conservation concern (Taylor et al. Reference Taylor, DiStefano, Larson and Stoeckel2019). To improve the success of conservation measures for burrowing species it is important to understand habitat associations and responses to land management activities (Moore et al. Reference Moore, DiStefano and Larson2013).

Many land management practices are employed across private agricultural land, publicly owned properties and private easements (Oudenhoven et al. Reference Van Oudenhoven, Petz, Alkemade, Hein and de Groot2012), including prescribed burns, mechanical vegetation disturbance, hydrologic manipulation and chemical treatment. On moist-soil wetlands in the USA, management efforts focus on vegetation and hydrologic regimes (Fredrickson Reference Fredrickson1991, de Szalay Reference de Szalay and Resh1997). Negative impacts of land management practices are documented for aquatic invertebrates and fish (e.g., Berkman et al. Reference Berkman, Rabeni and Boyle1986, Wrubleski & Ross Reference Wrubleski and Ross2011) but little focus has been placed on burrowing crayfish.

Mowing is perhaps the most common land management practice employed on the terrestrial landscape. Plant diversity and nutrient cycling in agricultural grasslands benefit from semi-frequent cutting (Antonsen & Olsson Reference Antonsen and Olsson2005). Mowing has mixed effects on macroinvertebrates (Szalay & Resh Reference de Szalay and Resh1997, Humbert et al. Reference Humbert, Ghazoul, Sauter and Walter2010). The direct effects on burrowing crayfish have not been investigated; however, mowed roadside ditches are frequently inhabited (Tack Reference Tack1941, Rhoden et al. Reference Rhoden, Taylor and Peterman2016).

Disking is another commonly employed activity for managed landscapes and is used to break up soil, chop stover from previous agricultural crops and mix topsoil layers, often enhancing soil organic material (Komatsuzaki & Ohta Reference Komatsuzaki and Ohta2007). Spring or early summer disking is the most common mechanical manipulation practice used in wetlands (Gray et al. Reference Gray, Hagy, Nyman, Stafford, Anderson and Davis2013). This practice hinders succession, impeding the emergence of woody vegetation and promoting a higher diversity of seed-producing plants for wetland birds during autumn migration periods (Missouri Department of Conservation 2009). The effects of disking have only been examined in Procambarus clarkii, usually classed as a secondary or tertiary burrower. The results were conflicting, with both negative and positive responses to disking (Chien & Avault Reference Chien and Avault1983, Gray et al. Reference Gray, Kaminski, Weerakkody, Leopold and Jensen1999). However, it was noted that disking increases aeration and loosens soil (Gray et al. Reference Gray, Kaminski, Weerakkody, Leopold and Jensen1999), potentially reducing the energetic costs of excavating soil.

We examined how vegetation management might affect burrowing crayfish at two Missouri Department of Conservation (MDC)-owned conservation areas that are managed for waterfowl. Our study objectives were to: (1) identify the fine-scale and landscape-level characteristics of primary burrowing crayfish habitat; and (2) determine the response of burrowing crayfish to mowing and disking on these public properties.

Methods

Study areas

The Mississippi Alluvial Valley contains rich, moist soils suitable for burrowing crayfish. We identified two publicly owned properties in south-eastern Missouri – Duck Creek and Otter Slough Conservation Areas – with similar management practices and known crayfish presence. Both properties lie in the Pleistocene Valley Trains ecoregion. They are moist-soil wetlands managed by MDC for resident and migratory waterfowl and other wildlife. Ephemeral wetlands on site are disked annually during the dry season to promote native plant growth. Roadside ditches, levees and trails are mowed biannually for access. Unmanaged land on the properties often presents as units of native, bottomland forest that are maintained for wildlife habitat and food supplies of acorns and invertebrates.

Environmental data and sampling

Sampling was conducted in spring 2021. At each property, 11 40m transects were established in each of the three management types: disked, mowed and unmanaged. Transects were placed randomly with a minimum of 100 m spacing to ensure independence. Each transect had five 1m2 polyvinyl chloride (PVC) quadrats placed at 10 m intervals.

Within each quadrat we measured percentage of tree canopy cover, percentage of herbaceous ground cover, presence/absence of hydrophilic sedges, presence/absence of surface water, stem density and number of active burrows (see below). Canopy cover was estimated using a concave spherical densiometer (model C; Robert E. Lemmon, Forest Densiometers, Bartlesville, OK, USA) and inverted for herbaceous ground cover (Rhoden et al. Reference Rhoden, Taylor and Peterman2016). Stem density was measured using a 10cm2 quadrat placed in the upper left-hand corner of each 1m2 quadrat. A soil sample was collected at the third quadrat of each transect using a soil probe (AMS ⅞ in. open-end probe; AMS, American Falls, ID, USA) to an approximate depth of 50 cm. Soil samples were analysed for percentage composition (sand, silt and clay) by laser diffraction using a Malvern Mastersizer 3000 (Malvern Instruments, Malvern, UK). Selected habitat variables have previously been associated with other burrowing crayfish species in the south-eastern USA (Welch & Eversole Reference Welch and Eversole2006, Rhoden et al. Reference Rhoden, Taylor and Peterman2016). As only one soil sample was analysed, habitat variables across the quadrats were averaged to provide one measurement per transect. All active burrows within the quadrats were counted and burrow counts were averaged over transects to provide density as burrows/m2.

Active burrows were defined as burrows with freshly excavated mud at the entrances, substantial chimneys or smooth-walled entrances with no vegetation growth or debris in the opening (Helms et al. Reference Helms, Budnick, Pecora, Skipper, Kosnicki, Feminella and Stoeckel2013). All active burrows that fell within quadrats were excavated by hand. Crayfish captured were taxonomically identified and sexed, with representative specimens vouchered in the Illinois Natural History Survey Crustacean Collection.

The landscape-level environmental variables selected were elevation, available soil water storage up to 1.5 m depth, Euclidean distance to the nearest stream and average annual precipitation. Elevation was measured from the United States Geological Survey digital elevation map. Available soil water storage was measured from the United States Department of Agriculture gridded soil survey geographic database. Euclidean distance was calculated in ArcGIS using the National Hydrography Dataset. Average annual precipitation was measured from the PRISM Climate Group data from Oregon State University (http://prism.oregonstate.edu).

Statistical analysis

We used generalized linear mixed models (GLMMs) to examine relationships between burrow density and fine-scale habitat variables. Statistical analyses were conducted using R version 3.3.2 (R Core Development Team 2017). The predictor habitat variables were centred and scaled prior to analysis. Spearman’s correlation coefficient (ρs) was used to test for multicollinearity in predictor variables. Stem density, herbaceous ground cover and canopy cover were significantly correlated (ρs ≥ 0.60); therefore, only canopy cover was included in the fine-scale models. Models were zero-inflated to account for low detection. Candidate models were fitted using the R package glmmADMB (Fournier et al. Reference Fournier, Skaug, Ancheta, Ianelli, Magnusson and Maunder2012). Burrow density was modelled with a zero-inflated Poisson distribution with a log-link. Conservation area was included as a random effect in models to account for potential effects from using two separate properties. A global model containing selected predictor variables and conservation area as a random effect was fitted. The marginal r2 and overdispersion parameter c-hat were used to assess the fit of the models. Candidate models were evaluated using Akaike’s information criterion (AIC) with a small sample size correction (AICc; Akaike Reference Akaike1974). The top model(s) were defined as having ΔAICc values < 2.0 and containing majority weight (Burnham & Anderson Reference Burnham and Anderson2002). Model selection was conducted through the R package MuMIn (Barton Reference Barton2014). Variables in the top model were assessed for significance at α = 0.05.

We used a second set of GLMMs to examine the relationships between burrow presence and landscape-level environmental variables. The response variable was active burrow presence or absence within a transect. Using GLMMs, the response variable was modelled with a binomial distribution with a log-link. As above, conservation area was included as a random effect and model fit was assessed with marginal r2 and c-hat. The top models (AICc < 2.5; Table 1) were averaged using the R package MuMIn (Barton Reference Barton2014) to contain a majority weight. Variables were assessed for significance at α = 0.05.

Table 1. Generalized linear mixed model results for Creaserinus fodiens density (active burrows/m2) and fine-scale habitat data and C. fodiens burrow presence and landscape-level environmental data. The top five models, global model and null model for each are included. Models are ranked by Akaike’s information criterion (AIC) with small sample size correction (AICc). Difference in AICc (ΔAICc), Akaike weight (W i ), and log likelihood (LL) are presented. For fine-scale variables: canopy = canopy cover (%); sand = soil composition classed as sand (%); sedge = presence/absence of sedges; water = presence/absence of surface water; treatment = land management treatment (disked, mowed or unmanaged). For landscape-level variables: AWS = available water storage in the first 150 cm of soil; Precip = average annual precipitation (cm); EucStr = Euclidean distance to nearest stream (m); Elev = elevation (m). Data were collected from two conservation areas in south-western Missouri

Results

A total of 110 active burrows were recorded, with 30 individual crayfish captured in transects across the two properties. Twenty-six of the individuals collected were primary burrowing crayfish, Creaserinus fodiens. One individual each of Procambarus viaeviridis and Lacunicambarus ludovicianus was captured in mowed transects. As only one of each of these species was recovered and no other nearby burrows were recorded, they were excluded from statistical modelling. Two Procambarus acutus were collected from very shallow (<15cm), single-chamber burrows in transects. As this is a tertiary burrowing species, these individuals were also excluded. The remaining 106 active burrows were assumed to be C. fodiens. Additional excavated burrows and moulted exuviae outside the transects were also used to confirm the population species.

Only canopy cover was included in the top model for fine-scale environmental variables (Table 1). Canopy cover was a significant predictor (p = 0.017) of C. fodiens density, with lower canopy cover percentage being preferred (Fig. 1). Vegetation treatment was not present in the top model, nor was it significant in the global model (p = 0.3) of all fine-scale variables. The top model held a modest weight and several models ranked below the null model (Table 1). There was a non-significant decline in burrow density between the managed sites and the unmanaged sites (Fig. 1). Herbaceous ground cover and stem density were both excluded from modelling due to correlation with canopy cover. However, when canopy cover was removed and models run with herbaceous ground cover or stem density, neither was included in top models, nor was herbaceous ground cover or stem density significant in the global models (herbaceous ground cover p = 0.061, stem density p = 0.244). Similarly, soil texture did not represent as a significant contributor to the top model, regardless of which of the three soil texture percentages were included. Soil texture did not vary much across the sampled areas, with all samples being categorized as silt or silty loam (Fig. 2).

Fig. 1. Estimated number of Creaserinus fodiens burrows/m2 (95% confidence intervals) in relation to percentage of canopy cover (significant) and vegetation management (not significant).

Fig. 2. Soil texture plot for soil samples collected at Duck Creek and Otter Slough Conservation Areas, Missouri, in spring 2021. Each symbol represents a transect and its shade denotes the vegetation treatment. Texture classes follow the United States Department of Agriculture classification system (Soil Survey Division Staff 1993). All soil samples collected were classified as silt (SI) or silty loam (SIL).

Four top models were averaged to form the final model for landscape-level variables (Table 1). All four variables were present in the final model, with available soil water storage and average annual precipitation being significant (p < 0.05; Table 2). Available soil water storage was positively correlated with C. fodiens presence, whereas average annual precipitation was negatively correlated with C. fodiens presence (Table 2). Models with landscape-level variables consistently ranked above the null model.

Table 2. Model averaged parameter estimates of the top models for Creaserinus fodiens presence in two conservation areas in Missouri. Bold values indicate significant results at α = 0.05

Discussion

Crayfish response to management

We developed both fine-scale and landscape-level models to assess the habitat preferences of burrowing crayfish. It was not expected that our sampling would yield only one species, C. fodiens, but this result allowed us to examine the habitat preferences of this species more closely. Across the sampled landscape, open-canopy habitat was the only significant fine-scale characteristic for burrow density. Open-canopy environments have been recorded as important habitats for several species (Welch Reference Welch2006, Rhoden et al. Reference Rhoden, Taylor and Peterman2016, Adams et al. Reference Adams, Hereford and Hyseni2021). C. fodiens did not exhibit a significant response to vegetation management; however, our data do show it had lower burrow densities in unmanaged areas. This is likely attributable to higher levels of canopy cover in unmanaged areas, often being the result of no vegetation management to impede succession. In unmanaged areas where canopy cover was lower, both active burrows and captured specimens were recorded. Adams et al. (Reference Adams, Hereford and Hyseni2021) demonstrated a significant effect of vegetation but not vegetation management (mowing, mulching and prescribed burning) on Creaserinus oryktes in Mississippi. We split mechanical vegetation management into individual management practices to examine any fine-scale differences. It seems possible that primary burrowing crayfish are tolerant of the disturbance resulting from vegetation management and are responding largely to the resulting vegetation composition alone or in conjunction with other faunal responses to vegetation composition.

There was a significant effect of available soil water storage and precipitation on the presence or absence of C. fodiens burrows. Available water storage was positively correlated with burrow presence. Open canopy and high available water storage both indicate areas of wet seepage and higher soil moisture (Anderson et al. Reference Anderson, Loucks and Swain1969, Gray et al. Reference Gray, Spies and Easter2002). Precipitation was negatively correlated with burrow presence, although the average annual precipitation fluctuated by only 5 cm across the sampled areas. This may be an indicator that some primary burrowing crayfish prefer moist-soil areas but respond negatively to heavily saturated or flooded conditions.

Cross-taxa management on wetlands

The United States Fish and Wildlife Service National Wetlands Inventory estimates that there are c. 44.5 million ha of wetlands across the conterminous USA, with 94.7% of these being freshwater wetlands (Dahl Reference Dahl2011). Managing the 9.7 million ha of wetlands in the Mississippi Alluvial Valley requires regular mowing and/or disking to support perennial plant seed production (Covington et al. Reference Covington, Gray, Hoag, Mattinson, Tidwell, Rodrigue and Whited2003). This practice promotes food and habitat for several seed-eating ducks and foraging birds such as herons, egrets and bitterns in moist-soil wetlands. Similarly, emergent marshes require mowing and/or disking to impede succession and to support emergent cover for wading birds such as rails, grebes and coots (Covington et al. Reference Covington, Gray, Hoag, Mattinson, Tidwell, Rodrigue and Whited2003). Our results demonstrate that these open-canopy, moist-soil areas are key habitats for maintaining C. fodiens populations. Whereas macroinvertebrates are not actively managed on wetlands properties, aligning their management with waterfowl management could benefit both faunal groups.

The formation of subsurface burrows by crayfish leads to mixing of soil layers, leached nutrients being returned to the surface soil, increased aeration and improved subsurface water flow promoting plant growth (Bloomer et al. Reference Bloomer, DiStefano and Taylor2021). Moist-soil wetland managers typically do not plant seeds because seeds are already present in frequently flooded soils (Covington et al. Reference Covington, Gray, Hoag, Mattinson, Tidwell, Rodrigue and Whited2003), so improved plant growth would help to maintain this resource. Similarly, native grass stand culm density is reduced when plant litter builds up. Burrowing crayfish are detritivores (Thoma & Armitage Reference Thoma and Armitage2008, Grey & Jackson Reference Grey and Jackson2012) and can reduce autochthonous plant matter. Managed vegetation stands support a wide diversity of invertebrates that serve as a critical food source for migrating birds (Covington et al. Reference Covington, Gray, Hoag, Mattinson, Tidwell, Rodrigue and Whited2003). Crayfish burrows support many invertebrate species including arthropods, nematodes, annelids and insects (Bloomer et al. Reference Bloomer, DiStefano and Taylor2021), providing habitats for these key food sources. The North American Waterfowl Management Plan highlights the importance of enhancing waterfowl habitats for productivity and resilience (North American Waterfowl Management Plan Committee 2012). Burrowing crayfish provide many benefits and should be considered to be a valuable resource on wetland properties.

The wide geographical range of C. fodiens combined with its open-canopy association and ability to inhabit disturbed soils classify it as a habitat generalist (Loughman et al. Reference Loughman, Welsh and Simon2012). Other generalist burrowing species have been found in open and forested habitats across their ranges (Hobbs & Rewolinski Reference Hobbs and Rewolinski1985, Hobbs & Whiteman Reference Hobbs and Whiteman1991, McGrath Reference McGrath1994). These species seem to present fewer fine-scale habitat associations, which likely facilitates their ability to occupy a large geographical range. Habitat specialists are suggested to be less tolerant of human disturbance (Loughman et al. Reference Loughman, Welsh and Simon2012). However, habitat specialists have also been demonstrated to thrive in mechanically managed areas (Adams et al. Reference Adams, Hereford and Hyseni2021) and mowed roadside ditches (Rhoden et al. Reference Rhoden, Taylor and Peterman2016). From this literature, we expect that the management practices that reduced canopy cover and benefitted C. fodiens here would also benefit other burrowing species, both generalist and specialist.

However, there are other wetlands management practices that have not been evaluated. Hydrologic manipulation is a major wetlands management practice using structures such as dikes, diversions and sloughs to control flooding depth, duration and timing (Covington et al. Reference Covington, Gray, Hoag, Mattinson, Tidwell, Rodrigue and Whited2003). Water-level manipulations attract foraging birds through guaranteed water supply, increased moist-soil vegetation, the reducing of predation and the trapping of edible invertebrates (Fredrickson Reference Fredrickson1991). During our study, 4 workers searched for 45 min in an area of managed waterfowl habitat that is manually flooded for c. 7 months of the year. We observed no sign of crayfish burrows, despite such burrows being present in nearby non-flooded areas. The impact of the timing and duration of hydrologic manipulation must be evaluated before we can assert that all waterfowl management is beneficial to burrowing crayfish.

Taylor et al. (Reference Taylor, DiStefano, Larson and Stoeckel2019) emphasized that incorporating crayfish into conservation planning and habitat management in protected areas is a key strategy to improve US conservation efforts for crayfish. Maintaining open-canopy, moist-soil areas in wetlands is key to conserving primary burrowing crayfish and to halting population declines. Integrating crayfish management with some aspects of waterfowl management may facilitate this. C. fodiens is the most widespread primary burrowing species in the USA, so the conservation efforts proposed here apply beyond the locality of this study. Our data demonstrate that some wetland management practices directed towards unrelated taxonomic groups may be beneficial to non-target organisms. Future efforts must examine other burrowing crayfish species and land management practices in wetlands in order to evaluate whether management integration can be a widespread conservation solution.

Acknowledgements

We thank Colton Hampton, Ashley Hrdina, Jim Baker, Kevin Brunke, Liz Yohe, Jacob Westhoff and Josh Hartwig for field assistance. We thank Nicky Walker, Pam Ward, Mike Reed and Luke Wehmoff for their local knowledge and guidance at the conservation areas. We are grateful to Auriel Fournier and the two anonymous reviewers for their valuable comments on the manuscript.

Financial support

This study was funded by the Missouri Department of Conservation.

Conflict of interest

The authors declare none.

Ethical standards

None.

References

Abell, RA, Olson, DM, Dinerstein, E, Eichbaum, W, Hurley, P, Diggs, JT et al. (2000) Freshwater Ecoregions of North America: A Conservation Assessment, Vol. 2. Washington, DC, USA: Island Press.Google Scholar
Adams, SB, Hereford, SG, Hyseni, C (2021) Burrow densities of primary burrowing crayfishes in relation to prescribed fire and mechanical vegetation treatments. Water 13: 1854.CrossRefGoogle Scholar
Akaike, H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19: 716723.CrossRefGoogle Scholar
Anderson, RC, Loucks, OL, Swain, AM (1969) Herbaceous response to canopy cover, light intensity, and throughfall precipitation in coniferous forests. Ecology 50: 255263.CrossRefGoogle Scholar
Antonsen, H, Olsson, PA (2005) Relative importance of burning, mowing and species translocation in the restoration of a former boreal hayfield: responses of plant diversity and the microbial community. Journal of Applied Ecology 42: 337347.CrossRefGoogle Scholar
Barton, K (2014) MuMIn Package: Multi-model Inference. CRAN Project, USA [www document]. URL https://cran.r-project.org/web/packages/MuMIn/index.html Google Scholar
Berkman, HE, Rabeni, CF, Boyle, TP (1986) Biomonitors of stream quality in agricultural areas: fish versus invertebrates. Environmental Management 10: 413419.CrossRefGoogle Scholar
Bloomer, CC, Taylor, CA (2020). American Crayfish Atlas [www document]. URL https://americancrayfishatlas.web.illinois.edu/ Google Scholar
Bloomer, CC, DiStefano, RJ, Taylor, CA (2021) A global review of life history studies on burrowing crayfish. Crustaceana 94: 357379.CrossRefGoogle Scholar
Burnham, KP, Anderson, DR (2002) Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. New York, NY, USA: Springer.Google Scholar
Chien, YH, Avault, JW Jr (1983) Effects of flooding dates and disposals of rice straw on crayfish, Procambarus clarkii (Girard), culture in rice fields. Aquaculture 31: 339359.CrossRefGoogle Scholar
Covington, P, Gray, R, Hoag, C, Mattinson, M, Tidwell, M, Rodrigue, P, Whited, M (2003) Wetland Restoration, Enhancement, and Management. Washington, DC, USA: United States Department of Agriculture.Google Scholar
Dahl, TE (2011) Status and Trends of Wetlands in the Conterminous United States 2004 to 2009. Washington, DC, USA: US Department of the Interior, US Fish and Wildlife Service, Fisheries and Habitat Conservation.Google Scholar
de Szalay, FA, Resh, VH (1997) Responses of wetland invertebrates and plants important in waterfowl diets to burning and mowing of emergent vegetation. Wetlands 17: 149156.CrossRefGoogle Scholar
Fournier, DA, Skaug, HJ, Ancheta, J, Ianelli, J, Magnusson, A, Maunder, MN et al. (2012) AD model builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization Methods and Software 27: 233249.CrossRefGoogle Scholar
Fredrickson, LH (1991) Waterfowl Management Handbook: Strategies for Water Level Manipulations in Moist-Soil Systems, 13.4.6 (Vol. 13). Washington, DC, USA: US Department of the Interior, Fish and Wildlife Service.Google Scholar
Gray, AN, Spies, TA, Easter, MJ (2002) Microclimatic and soil moisture responses to gap formation in coastal Douglas-fir forests. Canadian Journal of Forest Research 32: 332343.CrossRefGoogle Scholar
Gray, MJ, Hagy, HM, Nyman, JA, Stafford, JD (2013) Management of wetlands for wildlife. In: Anderson, JT, Davis, CA (eds.), Wetland Techniques (pp. 121180). Dordrecht, The Netherlands: Springer.CrossRefGoogle Scholar
Gray, MJ, Kaminski, RM, Weerakkody, G, Leopold, BD, Jensen, KC (1999) Aquatic invertebrate and plant responses following mechanical manipulations of moist-soil habitat. Wildlife Society Bulletin 27: 770779.Google Scholar
Grey, J, Jackson, MC (2012) ‘Leaves and eats shoots’: direct terrestrial feeding can supplement invasive red swamp crayfish in times of need. PLoS ONE 7: e42575.CrossRefGoogle Scholar
Helms, B, Budnick, W, Pecora, P, Skipper, J, Kosnicki, E, Feminella, J, Stoeckel, J (2013) The influence of soil type, congeneric cues, and floodplain connectivity on the local distribution of the devil crayfish (Cambarus diogenes Girard). Freshwater Science 32: 13331344.CrossRefGoogle Scholar
Hobbs, HH III (1993) Trophic relationships of North American freshwater crayfishes and shrimps. Contributions in Biology and Geology 85: 1110.Google Scholar
Hobbs, HH III, Rewolinski, SA (1985) Notes on the burrowing crayfish Procambarus (Girardiella) gracilis (Bundy) (Decapoda, Cambaridae) from southeastern Wisconsin, USA. Crustaceana 48: 26–33.CrossRefGoogle Scholar
Hobbs, HH III, Whiteman, M (1991) Notes on the burrows, behavior, and color of the crayfish Fallicambarus (F.) devastator (Decapoda: Cambaridae). Southwestern Naturalist 36: 127135.CrossRefGoogle Scholar
Humbert, JY, Ghazoul, J, Sauter, GJ, Walter, T (2010) Impact of different meadow mowing techniques on field invertebrates. Journal of Applied Entomology 134: 592599.Google Scholar
Komatsuzaki, M, Ohta, H (2007) Soil management practices for sustainable agro-ecosystems. Sustainability Science 2: 103120.CrossRefGoogle Scholar
Loughman, ZJ, Welsh, SA, Simon, TP (2012) Occupancy rates of primary burrowing crayfish in natural and disturbed large river bottomlands. Journal of Crustacean Biology 32: 557564.CrossRefGoogle Scholar
McGrath, C (1994) Status of the Greensboro Burrowing Crayfish Cambarus (Depressicambarus) catagius (Hobbs and Perkins, 1967). Nongame Project Report for the US Fish and Wildlife Service. Nongame and Endangered Wildlife Program. Raleigh, NC, USA: North Carolina Wildlife Resource Commission.Google Scholar
Missouri Department of Conservation (2009) Spring Strip Disking for Quail [www document]. URL https://mdc.mo.gov/blogs/more-quail/spring-strip-disking-quail Google Scholar
Moore, MJ, DiStefano, RJ, Larson, ER (2013) An assessment of life-history studies for USA and Canadian crayfishes: identifying biases and knowledge gaps to improve conservation and management. Freshwater Science 32: 12761287.CrossRefGoogle Scholar
North American Waterfowl Management Plan Committee (2012) North American Waterfowl Management Plan 2012: People Conserving Waterfowl and Wetlands. Washington, DC, USA: US Department of the Interior, US Fish and Wildlife Service; Ottawa, Ontario, Canada: Environment Canada, Canadian Wildlife Service.Google Scholar
Pintor, LM, Soluk, DA (2006) Evaluating the non-consumptive, positive effects of a predator in the persistence of an endangered species. Biological Conservation 130: 584591.CrossRefGoogle Scholar
R Core Development Team (2017) R: A language and environment for statistical computing [www document]. URL https://www.R-project.org/ Google Scholar
Rhoden, CM, Taylor, CA, Peterman, WE (2016) Highway to heaven? Roadsides as preferred habitat for two narrowly endemic crayfish. Freshwater Science 35: 974983.CrossRefGoogle Scholar
Richardson, AMM (1983) The effect of the burrows of a crayfish on the respiration of the surrounding soil. Soil Biology and Biochemistry 15: 239242.CrossRefGoogle Scholar
Soil Survey Division Staff (1993) Soil Survey Manual (No. 18). Washington, DC, USA: US Department of Agriculture.Google Scholar
Stone, EL (1993) Soil burrowing and mixing by a crayfish. Soil Science Society of America Journal 57: 10961099.CrossRefGoogle Scholar
Tack, PI (1941) The life history and ecology of the crayfish Cambarus immunis Hagen. American Midland Naturalist 25: 420446.CrossRefGoogle Scholar
Taylor, CA, DiStefano, RJ, Larson, ER, Stoeckel, J (2019) Towards a cohesive strategy for the conservation of the United States’ diverse and highly endemic crayfish fauna. Hydrobiologia 846: 3958.CrossRefGoogle Scholar
Thoma, RF, Armitage, BJ (2008) Burrowing Crayfish of Indiana. Indianapolis, IN, USA: Indiana Department of Natural Resources.Google Scholar
Van Oudenhoven, AP, Petz, K, Alkemade, R, Hein, L, de Groot, RS (2012) Framework for systematic indicator selection to assess effects of land management on ecosystem services. Ecological Indicators 21: 110122.CrossRefGoogle Scholar
Welch, S (2006) Multiscale Habitat Associations of Three Primary Burrowing Crayfish. PhD dissertation. Clemson, SC, USA: Clemson University.Google Scholar
Welch, SM, Eversole, AG (2006) The occurrence of primary burrowing crayfish in terrestrial habitat. Biological Conservation 130: 458464.CrossRefGoogle Scholar
Williams, DD, Williams, NE, Hynes, HBN (1974) Observations on the life history and burrow construction of the crayfish Cambarus fodiens (Cottle) in a temporary stream in southern Ontario. Canadian Journal of Zoology 52: 365370.CrossRefGoogle Scholar
Wrubleski, DA, Ross, LC (2011) Aquatic invertebrates of prairie wetlands: community composition, ecological roles, and impacts of agriculture. Arthropods of Canadian Grasslands 2: 91116.Google Scholar
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Table 1. Generalized linear mixed model results for Creaserinus fodiens density (active burrows/m2) and fine-scale habitat data and C. fodiens burrow presence and landscape-level environmental data. The top five models, global model and null model for each are included. Models are ranked by Akaike’s information criterion (AIC) with small sample size correction (AICc). Difference in AICc (ΔAICc), Akaike weight (Wi), and log likelihood (LL) are presented. For fine-scale variables: canopy = canopy cover (%); sand = soil composition classed as sand (%); sedge = presence/absence of sedges; water = presence/absence of surface water; treatment = land management treatment (disked, mowed or unmanaged). For landscape-level variables: AWS = available water storage in the first 150 cm of soil; Precip = average annual precipitation (cm); EucStr = Euclidean distance to nearest stream (m); Elev = elevation (m). Data were collected from two conservation areas in south-western Missouri

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Fig. 1. Estimated number of Creaserinus fodiens burrows/m2 (95% confidence intervals) in relation to percentage of canopy cover (significant) and vegetation management (not significant).

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Fig. 2. Soil texture plot for soil samples collected at Duck Creek and Otter Slough Conservation Areas, Missouri, in spring 2021. Each symbol represents a transect and its shade denotes the vegetation treatment. Texture classes follow the United States Department of Agriculture classification system (Soil Survey Division Staff 1993). All soil samples collected were classified as silt (SI) or silty loam (SIL).

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Table 2. Model averaged parameter estimates of the top models for Creaserinus fodiens presence in two conservation areas in Missouri. Bold values indicate significant results at α = 0.05