Apple Snail Dynamics Model

1 1Modeling apple snail population dynamics on the Everglades Landscape23Philip C. Darby, Donald L. DeAngelis, Stephanie Romañach, Kevin Suir, and Joshua 4Bridevaux5 Supplementary Material6Appendix 1. Detailed description of EverSnail model parameterization, submodels, and7description of their derivation89The estimation of parameters for the EverSnail model is described below, following a 10description of pertinent apple snail life history and ecology details. Additional details and 11references on apple snail life history and ecology are available in a literature review by the 12Pomacea Project (2013). 1314Summary of Apple Snail Life History and Ecology15Estimates for apple snail life span were reported from several lab and field studies, and based 16on different types of observations. Hanning (1979) concluded that Florida apple snails had a 171-1.5 year life span based on a shift in the size-frequency distribution (with a disappearance 18of larger size classes) as well as finding an increase in the number of dead adult-sized snails 19in a concentrated time period in June. Ferrer et al. (1990) reported a significant increase in 20mortality in 15-20 month old P. paludosa directly observed in situ in wetlands in Cuba. 21Darby et al. (2003) observed a steep decline in survival in May-June for both snails in the 22field (bearing transmitters) and in the lab, regardless of water level. Additional study showed23the steep decline in survival immediately followed peak egg cluster production (i.e., a post-24reproductive die-off) (Darby et al. 2008). The concentration of egg production in spring the 25previous year (see details below), and the increased mortality observed in summer the 2 1 3 26following year (~12-15 months later), are consistent with a 1-1.5 year life span for P. 27paludosa. 28 As with all Pomacea snails studied to date, the Florida apple snail can survive 29periodic dry downs typical of the tropical and subtropical wetlands they inhabit (Cowie 2002,30Darby et al. 2008). Water depths recede, with possible temporary reversals, during the dry 31season, which generally occurs from January-June. Dry marsh conditions, in years they 32occur at all, are most often found in April-June (Kushlan 1990, Darby et al. 2008). Dry down33survival rates depend on reproductive status of adults-sized snails, and snail size in general. 34Reproductive and post-reproductive adults die regardless of water depths (including dry 35downs) as a result of a life cycle that culminates in a post-reproductive die-off (Darby et al 362003). Adult-sized snails that had not reproduced (average shell width 31 ± 4.2 mm) survive 374 weeks in dry conditions with survival at 98%; this declines to 71% at 12 weeks and 27% at 3818 weeks (Darby et al. 2008). Juvenile-sized snails exhibited significantly lower survival 39rates, where 10-15 mm and 6-9 mm size class survival was ~80% after four weeks in dry 40conditions. After 8 weeks 10-15 mm snail survival was 43% and 6-9 mm snail survival was 4113%. Newly hatched snail survival (<6 mm) was more variable, but still significantly lower 42than the larger juvenile size classes (50% or fewer of the newly hatched snails survived after 434 weeks and all were dead at 8 weeks) (Darby et al. 2008).44 All Pomacea species are dioecious (Cowie 2002), and Hanning (1979) estimated a 1:145sex ratio for the majority of samples he collected on Lake Okeechobee, which we apply to 46our population model. Hanning (1979) found that snails were sexually mature when shells 47reached approximately 35 mm in size. Darby et al. (2008) reported egg-laying females and 48mating males of somewhat smaller size (~25-30 mm) in the Upper St. Johns basin. Females 49deposit clusters of cleidoic eggs above the water line on emergent vegetation; each cluster 50typically consists of 20-40 eggs (Hanning 1979, Turner 1996). Hanning (1979) reported an 4 2 51average of one cluster produced per female per week, and Hurdle (1974) recorded 21 and 25 52total clusters produced by two Florida apple snails (total fecundity, and what influences it, 53requires further study). Egg clusters can be found year round; however, from November 54through January or early February few or no eggs are found (Hanning 1979, Darby et al. 552008). Darby et al. (2008) reported ~80% of annual egg cluster production in April-June 56(greatest annual egg counts also occurred in April, May, or June); in the seven transects 57reported, none experienced a drying event. This peak period corresponds to the late dry 58season and typically receding water levels (see Darby et al. 2008). In a drying event, snails 59do not move, mate or lay eggs (Darby et al. 2008). Spring dry downs can skew peak egg 60production toward the summer (i.e., wet) season (O’Hare 2010, Darby 2012 unpublished 61data). Hanning (1979) reported the incubation period for egg clusters as approximately 16-2262days.63 Although P. paludosa typically deposit their eggs 10-20 cm above the water line 64(Turner 1996, Hanning 1979, O’Hare 2010), they can be vulnerable to rising water that 65results in egg submersion. [Oviposition height can be higher, depending on the vegetation 66type available (Hanning 1979, Darby unpublished data).] Turner (1998) found that 1- to 8-67day old eggs failed to hatch when submerged. Sixty-five percent of 12-day-old (fully 68hardened and calcified eggs) hatched despite being submerged. Based on egg height data 69from the Everglades (Darby unpublished data), a water level rise of more than 18 cm would 70be required to submerge most unhatched egg clusters.71 Although a water level rise may not be problematic for snail eggs already deposited, 72there appears to be a negative effect of relatively deep water on egg cluster production. 73Gleason et al. (1975) described an inverse relationship between a hydrologic index (average 74depth*hydroperiod) and snail eggs counted, although snail density estimates, which might 75have explained at least part of the variation in egg production, were not available. Darby 5 3 76(unpublished) calculated a per capita egg cluster count (PCE) (number of egg clusters divided77by snail densities) and found higher PCE associated with lower depths (as long as depths 78were greater than approximately 10 cm). Egg cluster production dropped by an order of 79magnitude, despite relatively abundant snails, in a relatively wet year in WCA3A (2003, 80where water depths for the year never fell below 40 cm) compared to the previous year 81(2002) in which the study sites had depths of 10-40 cm during the spring reproductive season 82(Darby et al. 2005). In addition, the PCE dropped by an order of magnitude from 2002 to 832003 (Darby, unpublished calculations). The following year (2004) the snail population in 84this part of WCA3A dropped by over 80% (Darby et al. 2005). Although the depth range 85best suited for apple snail recruitment requires further study, especially for the upper depth 86limits (see Pomacea Project 2013), there is sufficient evidence to suggest that a negative 87influence of some upper depth limit on reproduction should be incorporated into the apple 88snail population model.89 Apple snails hatch out at three to six millimeters in diameter (Hanning 1979, Darby et90al. 2008). They grow approximately 10-13 mm per month during the first two months 91(Hanning 1979, Glass and Darby 2009); therefore, snails that hatch in spring can reach adult 92size (and sizes consumed by kites) by early to mid-summer. Growth rates slow down 93considerably once the snails reach ~25 mm (Hanning 1979). Although numerous 94environmental factors likely influence growth rates, they have not been sufficiently quantified95to be parameterized in our model.96 The sub-tropical climate of southern Florida results in sufficient temperature 97fluctuations to significantly influence apple snail activity in general. Stevens et al. (2002) 98found no activity in apple snails exposed to water temperatures <13°C, and below 10°C 92% 99of snails burrowed into the sediments. These observations of snails were consistent with 100Cary (1985), having found no snail captures by kites attempting to forage when air 6 4 101temperatures fell below 10°C. From 11°C up to 30°C, prey capture rates by kites increased 102linearly, most likely a function of increased rates of general activity and surfacing by snails 103(Cary 1985). McClary (1964) reported a 2.7-fold increase in the number of surface 104inspirations by Pomacea snails as temperatures increased from 12°C to 26°C. Stevens et al. 105(2002) observed that the greatest increase (nearly exponential) in general activity occurred 106between 20°C and 22°C degrees. Given the over-riding effect of low temperatures on 107activity, relatively low dry-season temperatures would be expected to reduce rates of egg 108cluster production (see Hanning 1979), and this effect may be amplified by a depth-109temperature interaction (Pomacea Project 2013).110 Several studies have made associations between snail density or relative abundance 111and attributes of plant community structure (Bryan 1990, Turner 1996, Darby et al. 2004, 112Karunarante et al. 2006); however, the current version of our apple snail model does not 113parameterize the complex influence of habitat components (other than water depth) on snail 114demographic metrics. In laboratory studies, diet (Sharfstein and Steinman 2001, Shuford et 115al. 2005), and calcium and pH (Glass and Darby 2009) have also been shown to influence P. 116paludosa growth and survival; however, these parameters have not yet been incorporated into117the model.118119EverSnail Model Description Following Grimm et al. (2006, 2010) ODD protocol120Purpose and Parameterization 121The purpose of EverSnail is to describe the dynamics of the apple snail population on the 122Everglades landscape over a period of years, in order to interpret effects of year-to-year 123variability in landscape hydrology on apple snail abundance. In particular, the numbers and 124size distributions of the snails are simulated by following cohorts of snails through their life 125cycles, which allows total numbers within any given size range to be calculated for any day 7 5 126within a year. The effects of scenarios based on historical environmental data, as well as 127scenarios based on artificially varied sequences of environmental conditions, can be 128employed in the model to study the effects on apple snail population distributions across the 129landscape.130131State variables and scales132The age- and size-structured apple snail population is represented as a vector consisting of 133500 daily age-classes, with 500 d representing the approximate life span of Florida apple 134snails;135 N = [N1(t), N2(t), …, Ni(t), … , N500(t)] (A.1)136where Ni(t) is the number of apple snails in age class i in a given spatial cell at time t. The 137snails in each age class have an attribute of size (linear dimension in mm), which increases 138deterministically. Space is represented by 253125 spatial cells, each 400 x 400 m, which are 139contiguous and represent the Water Conservation Areas and ENP (see Figure 1, main text) 140and some surrounding wetlands. The temporal scale of resolution is one day, and simulations141can be run for any period beginning January 1st, 1991 (details on water depth input, 142Appendix 3). The individual spatial cells are assumed independent (no movement of snails 143between cells is assumed), so simulations can be performed either on the whole spatial extent,144or on individual cells or subsets of cells, such as those for which empirical data on snail 145densities are available. The analyses presented here emphasized WCA3A (see Figure 1), 146where the majority of Everglades snail density data has been collected (Pomacea Project 1472013). 148149Process overview and scheduling8 6 150As there is no immigration to or emigration from a spatial cell, the dynamics of the age-151structured subpopulation in each spatial cell is entirely governed by a Markov chain matrix 152model, A, shown below. 0 0 0 . fi f i1 f i2 . f 499 f500 a12 0 0 . 0 0 0 . 0 00 a23 0 . 0 0 0 . 0 0 ...... 0 0 0 . 0 0 0 . 0 0 153 A  (A.2) 0 0 0 . ai,i1 0 0 . 0 00 0 0 . 0 ai1,i2 0 . 0 0 ...... 0 0 0 . 0 0 0 . 0 00 0 0 . 0 0 0 . a499,500 0154155where ai,i+1 represents the fractional survival of a given one-day age class cohort from age 156class i to age class i+1, and fi is fecundity (per capita offspring) of age class i. The number of157new 1-day old snails on each day is given by158 N1 (t+20) = f iN i (t) + f i+1N i+1(t) … + … f 500 N500(t), (A.3)159starting from the first age class capable of reproduction, where the ‘20’ represents a 20-day 160delay for eggs to hatch. Survival from one age class to the next is given by161 Ni+1(t+1) = ai,i+1Ni(t) (i = 1, 2….., 500) (A.4)162163Initialization 164At the start of each simulation, an equal number of snails is assumed present in each age class165and in all spatial cells. Simulations are run over preliminary periods of several years to allow166transient effects of the initialization to disappear, which occurs after about three years.167168Environmental conditions 9 7 169We assume a grid of 400 x 400 meter cells covering the area of the simulation. For each cell,170we assume that we can assign:171  daily values of water depth from Everglades Depth Estimator Network (EDEN)172  daily values of ambient air temperature.173174Daily water depth values for each spatial cell are input each day using data from the 175Everglades Depth Estimation Network (see Appendix 3 for details). Regional temperature 176values were linearly interpolated from existing data points across the whole set of spatial cells177(Appendix 3). The specific spatial area to be simulated (the whole area or a subset of cells 178examined for sensitivity analyses) and the number of years simulated are prescribed as input. 179180Submodels181There are three basic submodels that determine the simulated snail population; growth, 182survival, and reproduction, each of which is based on empirical information. The matrix A 183(equation A.2) contains the elements ai,i+1(t) and fi(t), for age class survival and reproduction, 184respectively. Both of these elements are functions of sizes of the snails, so the relationship 185between age and size, or ‘growth’ is first described. Parameter values are given in Table A1-1861.187188Growth. A logistic function is used to describe the mean individual size with age for every 189snail cohort; kgrowth Age Sizemine 190 Sizei  , (A.5) kgrowth Age 1 ( Sizemin / Sizemax )( e 1)191where Sizemin = linear size of newly hatched snail, Sizemax = maximum size of snail, and 192kgrowth = daily growth rate (see Figure A1-1). Growth is assumed to follow the pattern of 10 8 193Equation (A.5) regardless of changing environmental conditions, and thus every cohort 194follows the same growth pattern. The influence of environmental conditions such as 195temperature requires additional empirical data on P. paludosa to support further 196parameterization of the growth component of EverSnail. 197198199Survival. The values of day-to-day survival, ai,i+1, depend on snail size. Four survival 200categories were selected based on empirical data that show distinct survival rates between 201three small juvenile categories as well as a fourth category that includes juveniles >16 mm 202and reproductively mature adults. Survival can be divided into two conditions, wet (water 203depth > 0 cm) and dry (see Table A1-1 and Figure A1-2).204205 Size Wet conditions Dry conditions206 size ≤ 6 mm Survwet1 Survdry1207 6 mm ≤ size < 10 mm Survwet2 Survdry2208 10 mm ≤ size < 16 mm Survwet3 Survdry3209 16 mm ≤ size Survwet4 Survdry4210211The maximum lifespan of adults does not extend much beyond 500 days. In order to achieve 212rapid die-off around this age, we substitute the following expressions for mortality of snails 213of size > 16 mm under wet and dry conditions, respectively.kage ( Agemortage) 214 Survadult,wet  Survwet 4 /1 e  (A.6)kage ( Agemortage) 215 Survadult,dry  Survdry4 /1 e  (A.7)21611 9 217Reproduction. The values of fi(t), or the numbers of offspring produced per female snail per 218day, depend on a number of factors specific to the snails and the environmental conditions. 219We can write fi(t) as a product of factors:220 fi(t) = (fraction of snails of age i that are female) 221 x (fraction of females of age i that are sexually mature) x (clutch size) 222 x (effects of time of year) x (effects of temperature) x (effects of water depth)223 x (effects of egg submersion) (A.8)224where ‘egg submersion’ means that the snail eggs are under water for some time, whereas 225‘effects of water depth’ refer to the effects of water depth independent of submersion of the 226eggs.227We consider each of these reproduction factors in turn.228 1. Fraction of snails of age i that are female; we assume Female fraction = 0.5 229230 2. Fraction of females of age i that are sexually mature. Sexual maturity depends on snail231 size, which is calculated as a function of age in equation (A.5). We assume there is a 232 mean size of arrival at maturity (MaturityThreshold), 27.5 mm, but that there is also 233 variation about this value, described by the equation e krepr (Sizei MaturityThreshold ) 234 Fraction of mature females at agei  ’ (A.9) 1 ekrepr (Sizei MaturityThreshold )235 where Sizei is the size of females in age class i (see Figure A1-3). A value of krepr = 236 1.0 will result in virtually all females being sexually mature by Size = 30 mm.237238 3. Clutch size, Clutch. A clutch size of Clutch = 30 eggs is assumed.23912 10 240 4. Effects of time of year, f(time of year). There is some seasonality in reproduction for 241 which we do not yet have a mechanistic explanation. To account for this seasonal 242 variation, we assume (see Figure A1-4)243 f(time of year) = 1.0 Day 15 ≤ time of year < Day 189244 f(time of year) = 0.3 Day 190 ≤ time of year < Day 328245 f(time of year) = 0.0 otherwise246247 5. Effects of water depth, f(water depth). Apple snails do not reproduce when water 248 depth is too low, because of difficulty in moving. High water depths also inhibit 249 reproduction. We represent the effects of water depth by a parabolic function between250 upper and lower bounds, Depthmin and Depthmax, respectively, with a midpoint 251 Depthmid (see Figure A1-5),252 f(water depth) = 0.0 water depth < Depthmin2 2 253 f(water depth) = 1.0 - (water depth –Depthmid ) /Wh Depthmin ≤ water depth<Depthmax254 f(water depth) = 0.0 Depthmax ≤ water depth 255256 6. Effects of temperature on reproduction. The probability of reproduction decreases 257 rapidly as temperature decreases below 17° C and reaches a maximum (plateau) at 258 21° C and above. We can represent this as, f(temperature) (see Figure A1-6)1 259 f(temperature) = (A.10) 1 e ktemp ( TemperatureTempraturethreshold )260261 7. Effects of egg submersion, f(egg submersion). Note that this is different from #5 262 ‘Effects of water depth’, which does not take into account egg submersion. Eggs may 263 die if submersed for some period following oviposition during the time of 20 days that264 they take to hatch. The egg clusters are oviposited about 18 cm above the water level.13 11 265 Rule 1. If they are not submersed, they will hatch within 20 days, with the assumption266 that 5% of the original number of eggs hatch each day, such that 100% hatch after 20 267 days. Rule 2. If the eggs are submersed for longer than 14 days, then only 5% of the 268 remaining unhatched eggs survive to hatching. It is assumed in the model that all 269 surviving eggs hatch in the model 20 days after the egg cluster is oviposited.270271Carrying capacity. A carrying capacity is imposed on the population of cells in any given 272cell by assuming there is an upper limit on the number of eggs that can exist on a given day, 273as reproductive sites are limited to emergent vegetation. This acts as the ‘density-dependent’ 274regulation in the model. The upper limit on total eggs at a given time is assumed to be-1 275 Egglimit = 35,000 ha 276If this limit is reached, no more eggs are assumed to be oviposited. It is possible that this 277limit will not be reached under realistic conditions.278279References280Bryan DC (1990) Apple snail densities at Alexander Springs, Lake County, and observations 281 on snail ecology. Fla Sci 53:13 282Cary DM (1985) Climatological factors affecting the foraging behavior and ecology of snail 283 kites (Rostrhamus sociabilis plumbeus Ridgway) in Florida. Thesis. University of Miami, 284 Florida285Cowie RH (2002) Apple snail (Ampullariidae) as agricultural pests: their biology, impacts, 286 and management In Barker GM (ed) Molluscs as Crop Pests. CABI Publishing, 287 Wallingford, UK, pp 145-192 288Darby PC, Valentine-Darby PL, Percival HF (2003) Dry season survival in a Florida apple 289 snail (Pomacea paludosa Say) population. Malacologia 45:179-184 14 12 290Darby PC, Valentine-Darby PL, Percival HF, Kitchens WM (2004) Florida apple snail 291 (Pomacea paludosa Say) responses to lake habitat restoration activity. Arch Hydrobiol 292 161:561-575 293Darby PC, Karunaratne LB, Bennetts RE (2005) The influence of hydrology and associated 294 habitat structure on spatial and temporal patterns of apple snail abundance and 295 recruitment. Final Report to U.S. Geological Survey. University of West Florida, 296 Pensacola 297Darby PC, Bennetts RE, Percival HF (2008) Dry down impacts on apple snail (Pomacea 298 paludosa) demography: Implications for wetland water management. Wetlands 28:204-299 214 300Ferrer JR, Perera G, Yong M (1990) Life tables of Pomacea paludosa (say) in natural 301 conditions. Fla Sci 53 (supplement):15 302Glass NH, Darby PC (2009) The effect of calcium and pH on Florida apple snail Pomacea 303 paludosa (Gastropoda: Ampullariidae) shell growth and crush weight. Aquat Ecol 304 43:1085-1093 305Gleason PJ, Stone PA, Rhoads P, Davis SM, Zaffke M, Harris L (1975) The impact of 306 agricultural runoff on the everglades marsh located in the conservation areas of the 307 central and southern Florida flood control district. South Florida Water Management 308 District, West Palm Beach309Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, 310 Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe΄er G, Piou311 C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi 312 S, Stillman RA, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for 313 describing individual-based and agent-based models. Ecol Model 198:115-12615 13 314Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD 315 protocol: A review and first update. Ecol Model 221:2760-2768316Hanning GW (1979) Aspects of reproduction in Pomacea paludosa (Mesogastropods: 317 Pillidae). Thesis, University of Florida, Gainesville318Hurdle MT (1974) Life history studies and habitat requirements of the apple snail at Lake 319 Woodruff National Wildlife Refuge. Proc Ann Conf Southeastern Assoc Game Fish 320 Commissioners 27:215-224 321Karunaratne LB, Darby PC, Bennetts RE (2006) The effects of wetland habitat structure on 322 Florida apple snail density. Wetlands 26:1143-1150 323Kushlan JA (1990) Freshwater marshes. In: Myers RL, Ewel JJ (eds) Ecosystems of Florida. 324 University of Central Florida Press, Orlando, pp 324-363325McClary A (1964) Surface inspiration and ciliary feeding in Pomacea paludosa 326 (Prosobrachia: Mesogastropoda: Ampullariidae). Malacologia 2:87-104327O’Hare NK (2010) Pomacea paludosa (Florida apple snail) reproduction in restored and 328 natural seasonal wetlands in the Everglades. Wetlands 30:1045-1052 329Pomacea Project, Inc. (2013) Literature review of Florida apple snails and snail kites, and 330 recommendations for their adaptive management. Final Report. Submitted to the 331 National Park Service, Everglades National Park. Available from 332 http://www.nps.gov/ever/naturescience/upload/ASS10-3FinalReportSecure.pdf. Accessed333 22 June 2014.334Sharfstein B, Steinman AD (2001) Growth and survival of the Florida apple snail (Pomacea 335 paludosa) fed 3 naturally occurring macrophyte assemblages. J North Am Benthol Soc 336 20:84-95337Shuford III RBE, McCormick PV, Magson J (2005) Habitat related growth of juvenile 338 Florida applesnails (Pomacea Paludosa). Fla Sci 68:11-19 16 14 339Stevens AJ, Welch ZC, Darby PC, Percival HF (2002) Temperature effects on Florida 340 applesnail activity: Implications for snail kite foraging success and distribution. Wildl Soc341 Bull 30:75-81 342Turner RL (1996) Use of stems of emergent plants for oviposition by the Florida applesnail, 343 Pomacea paludosa, and implications for marsh management. Fla Sci 59:34-49344Turner RL (1998) Effects of submergence on embryonic survival and development rate of the345 Florida applesnail, Pomacea paludosa: Implications for egg predation and marsh 346 management. Fla Sci 61:118-12934717 15 348Table A1-1. Life history parameters and their baseline values 349______350Sizemin = 3 mm351Sizemax = 50 mm352kgrowth = 0.05-1 353Survwet1 = 0.987 day-1 354Survwet2 = 0.987 day-1 355Survwet3 = 0.987 day356Survwet4 = 0.99 -1 357Survdry1 = 0.976 day-1 358Survdry2 = 0.984 day-1 359Survdry3 = 0.989 day-1 360Survdry4 = 0.99 day 361Agemort = 500. day-1 362kage = 0.1 day363MaturityThreshold = 27.5 mm364krepr = 1.0365Clutch = 30366Depthmid = 50 cm367Wh = 40 cm368Depthmin = 10 cm369Depthmax = 90. cm.370ktemp = 1.0 per º C371Temperaturethreshold = 17°C-1 372Egglimit = 35,000 ha 18 16 373Appendix 1 Figure Captions 374375Figure A1-1. Snail size versus age in days (Equation A1).376Figure A1-2. Daily survival rate as a function of snail size for both wet and dry conditions.377Figure A1-3. Cumulative fraction of sexually mature snails, which is used to determine the 378fraction of snails of a given age class that are mature.379Figure A1-4. Maximum possible rate of reproduction as a function of time of year.380Figure A1-5. Effect of water depth on reproduction.381Figure A1-6. Affect of temperature on snail reproduction (Equation A6).19 17 382383384 385Figure A1-1. Snail size versus age in days (Equation A1)38638738838939039139239339439520 18 396397398 399400Figure A1-2. Daily survival rate as a function of snail size for both wet and dry conditions.40140240340440540640740840941041121 19 412413Figure A1-3. Cumulative fraction of sexually mature snails, which is used to determine the 414fraction of snails of a given age class that are mature.41541641741841942042142242342442522 20 426427 428Figure A1-4. Maximum possible rate of reproduction as a function of time of year.42943043143243343443543643743843944023 21 44124 22 443Figure A1-5. Effect of water depth on reproduction.44444544644744844945045145245345445545625 23 457Figure A1-6. Affect of temperature on snail reproduction (Equation A6).45845946026 24 461Appendix 2. EverSnail programming and file formats462463In order to facilitate parameterization and execution of simulations, a software program 464encapsulating the apple snail population model logic was developed in the Java™ 465programming language. The software operates against water depth and temperature inputs 466that are stored in the Network Common Data Form (NetCDF) file format and conform to the 467Comprehensive Everglades Restoration Plan (CERP) NetCDF Metadata Conventions (JEM 4682011). Each input must be organized as a regular grid of cells in three dimensions: 2D 469coordinate space plus time. A graphical user interface allows users to supply the location of 470the inputs on the file system and the simulation time period, as well as adjust any of 25 model471parameters to support model validation and sensitivity analysis. All selections made by the 472user are stored in an internal data structure which is accessed by the model logic during 473runtime. Output is a CERP conventions-compliant NetCDF file containing daily simulated 474population values per spatial cell for total snails (adults plus juveniles), adults only, juveniles 475only, and eggs. These data were then analyzed both graphically, by using the EverVIEW 476Data Viewer (Romañach et al. 2014), and in tabular format with Microsoft Excel.477478References479Romañach SS, McKelvy M, Conzelmann C, Suir K (2014) EverVIEW Data Viewer: A 480 visualization framework and exploration tool for decision support of large-scale 481 biological planning. Environ Model Software 62:221-229 482 doi:10.1016/j.envsoft.2014.09.008483JEM (Joint Ecosystem Modeling) (2011) CERP NetCDF standard. Available from 484 http://www.jem.gov/Standards/NetCDF. Accessed 30 June 201448527 25 486Appendix 3. Detailed description of the air temperature and EDEN water depth inputs 487to EverSnail 488489The two input variables to EverSnail are daily average air temperature (°C) and estimated 490daily water depths from the Everglades Depth Estimation Network (EDEN). The spatial 491extent of the EverSnail model is dictated by the EDEN coverage. The Everglades Depth 492Estimation Network (EDEN) is a system more than 250 real-time water level monitoring 493stations throughout the Greater Everglades landscape. Water level data are combined with a 494ground surface elevation model to create a water surface simulation model. Water surface 495data are available from 1991 to present for the entire freshwater Everglades region. Data can 496be downloaded from http://sofia.usgs.gov/eden/models/watersurfacemod_download.php. 497EDEN daily water depth estimates can be manipulated to create artificial sequences of 498hydrologic conditions using the Slice and Dice tool available at 499http://jem.gov/Modeling/SliceAndDice. The South Florida Water Management District, 500south Florida’s water governing authority, has been collecting surface water, ground water, 501and meteorological data for many decades. For this model, we used daily air temperature 502values from 16 stations located throughout the model domain (applicable temperature data 503are presented in the main manuscript) dating back to 1991. Data can be downloaded from 504http://www.sfwmd.gov/dbhydroplsql/show_dbkey_info.main_menu. 505 Intra- and inter-annual fluctuations in water depths drive the observed changes in the 506EverSnail population output. Temperature influences were also evident, in EverSnail they 507impact reproduction (especially at lower temperatures), with applicable details presented in 508the main manuscript. The primary areas of interest for examining hydrologic influences on 509apple snail populations, as presented in the manuscript, are Water Conservation Area 3A 510(WCA3A), WCA3B, and northern portions of Everglades National Park (ENP) (see Figure 1,28 26 511main manuscript, and Figure A3-1, below). In order to characterize hydrologic impacts 512described in the manuscript, we obtained EDEN data for representative sites. WCA3A has a 513hydrologic gradient represented by Sites 13 (lower ground elevation, southern WCA3A) and 51418 (higher elevations further north), and one site each was selected for comparison in 515WCA3B and ENP (Figure A3-1). 516 For the Everglades region, the driest year for the period of interest (2000-2004 517hydrology, which influenced 2001-2005 snail abundance, see main manuscript) occurred in 5182001. In order to represent low water and high water extremes for the period of interest, we 519focused on WCA3A, but considered conditions for adjoining wetlands, WCA3B and ENP, as 520well (Figure A3-1). In 2001, portions of WCA3A, WCA3B and ENP experienced dry 521conditions (Figures A3-2, A3-3 and A3-4). For DrySim we copied the 2001 hydrologic data 522into simulation years 2002 and 2003 to artificially create 3 consecutive low water years. For 523WetSim we copied the 2003 hydrologic data into simulation years 2001 and 2002 to 524artificially create 3 consecutive high water years. Note that 2003 exhibited the highest dry 525season (winter-spring) water depths for the period of interest (Figures A3-2, A3-3, A3-4). 29 27 527Appendix 3 Figure Headings528529Figure A3-1. Everglades sites (*) for which daily water depths for 2000-2004 are presented 530in Figures A3-2, A3-3 and A3-4. Wetland units (as labeled in main text Figure 1) are 531L=WCA3A (showing sites 13 and 18), M=WCA3B (one site) and N=ENP (one site). 532533Figure A3-2. WCA3A sites 13 (black diamonds) and 18 (white circles, higher ground 534elevation) water depths from 2000-2004. 2001 conditions are noted as being used to create 3 535consecutive low water years for DrySim and 2003 conditions are noted as being used to 536create 3 consecutive high water years for WetSim. For site locations see Figure A3-1. 537Dashed horizontal line represents the depth (10 cm) below which Florida apple snails stop 538moving, mating or laying eggs (see Appendix 1).539540Figure A3-3. WCA3B site water depths from 2000-2004. 2001 conditions are noted as being541used to create 3 consecutive low water years for DrySim and 2003 conditions are noted as 542being used to create 3 consecutive high water years for WetSim. For site locations see Figure543A3-1. Dashed horizontal line represents the depth (10 cm) below which Florida apple snails 544stop moving, mating or laying eggs (see Appendix 1).545546Figure A3-4. ENP site water depths from 2000-2004. 2001 conditions are noted as being 547used to create 3 consecutive low water years for DrySim and 2003 conditions are noted as 548being used to create 3 consecutive high water years for WetSim. For site locations see Figure549A3-1. Dashed horizontal line represents the depth (10 cm) below which Florida apple snails 550stop moving, mating or laying eggs (see Appendix 1).30 28 551Figure A3-1. 552* *55331 29 554Fig A3-2. 555120 2000 2001 2002 2003 2004 (used in DrySim) (used in WetSim) 100 ) 80 m c ( h t 60 p e D40 r e t a 20 W0 Site 13 WCA3A Site 18 -20 55632 30 557Fig A3-3.5581002000 2001 2002 2003 2004 (used in DrySim) (used in WetSim) 806040200-20-40 WCA3B559 -6033 31 560Fig A3-4.56180 2000 2001 2002 2003 2004 (used in DrySim) (used in WetSim)60 ) m 40 c ( h t p 20 e D r e t 0 a W-20ENP562 -4034 32 563Appendix 4. Detailed results of EverSnail sensitivity analyses564-1 -1 565The model was very sensitive to changing Survwet4 from 0.99 d down to 0.988 d ; this 566resulted in the snail population quickly falling to zero (Table A4-1). Increasing Survwet4 to 5670.992 d-1 had no effect on the snail population. Sensitivity for all the remaining parameter 568changes ranged from −62.0% to +5.5%, and in some cases there were marked differences in 569sensitivity between sites (13 and 18) for the same parameter (Table A4-1). Sensitivity was 570less than ±10% of baseline snail abundance for kgrowth, ktemp, Survwet1, Survwet2, Survwet3. A 20% 571decrease in Tempthreshold (down to 13.6 °C) resulted in <6% increase in the population (Table 572A4-1).573 A +20% increase in Tempthreshold (up to 20.4 °C) resulted in ~≈20-22% decrease, based 574on quarterly averages, in the snail population. This population decline resulted from the input575temperatures having to rise to a higher level to stimulate reproduction. Very small declines in576air temperature below a threshold set at 20.4 °C (+20% of baseline) resulted in substantial 577changes in sensitivity (Figure A4-1). Changing Depthmax for reproduction from 90 cm 578(baseline) down to 72 cm (−20% of baseline) resulted in significant changes to snail 579abundance, but varied with topography. Parameterizing the model to prevent snails from 580reproducing at depths >72 cm greatly constrained egg production in the breeding season. The 581relative impact of setting Depthmax to 72 cm across a depth gradient was quantified by 582comparing output from WCA3A Site 13 vs 18; for site 13 (lower ground elevation) the 583EDEN depth data more frequently exceeded 72 cm and resulted in a population decline of 584−62%, compared to Site 18 at −12% (Figure A4-2). Due to overall lower depths in Site 18, 585the negative influence of lowering Depthmax was much less, compared to Site 13, for the site-586specific snail population. At only one point in time did mean quarterly depth in Site 18 587exceed 72 cm (in 2005), and this resulted in a significant negative effect on the snail 35 33 588population (−51% relative to the baseline) (Figure A4-2). The fact that raising Depthmax to 589108 cm resulted in no change in the population relative to baseline (Table A4-1) reflects the 590fact that quarterly mean depths in Sites 13 and 18 never exceeded 108 cm, and at this setting 591the simulated snail population continued to produce eggs. When EDEN depth inputs stayed 592between 10 and 90 cm under baseline conditions the population remained relatively stable 593and the annual cycle was driven by seasonal variation in egg cluster production (see main 594text).595 Since a change in Depthmax for reproduction resulted in a significant impact in the 596sensitivity analyses, and since Everglades restoration and management focuses primarily on 597restoring certain hydrologic conditions, we will elaborate on the response of the population to598changes in seasonal depths. The overall lowest water depths (falling below 10 cm in Site 18) 599were observed in 2001 during the dry season (Figure A4-2, also see Appendix 3). The 600highest dry-season water depths were observed in 2003; during that year depths stayed above 60125 cm in site 18 and in site 13 depths never fell below 59 cm. For any given year, the 602greatest depths occurred in the fall, and 2005 fall depths were the greatest overall (Figure A4-6032). Generally lower Site 18 water depths reflect a higher ground elevation than Site 13 (for 60475% of the simulation days, depths were ~20-40 cm lower than site 13, see Appendix 3). 605These differences in water depth differentially impacted the sensitivity to lowering the 606Depthmax for reproduction down to 72 cm. From 2001-2005, Site 18 depths exceeded 72 cm 607only once in 20 quarters, so sensitivity was <20% the majority of this period. In contrast, 608Site 13 depths exceeded 72 cm one to two quarters each year, and sensitivity ranged from 609-29% to -86%. The relationship between egg cluster production and seasonal water depth, 610represented here as Depthmax, needs to be addressed with more empirical data (see Discussion,611main text), since the value of this parameter in EverSnail has a substantial impact on 612predicted snail abundance over the Everglades landscape (Figure A4-3).36 34 613Table A4-1. EverSnail sensitivity expressed as percent change in total snail density when 614comparing simulations set at baseline parameter values to those with -20% and +20% 615changes for four model parameters shown, and a change of ±0.002 for daily survival rate (for 616four size categories) in flooded conditions (equivalent to ±20% of the mortality rate). Sites 61713 and 18 are shown to illustrate differences as a function of location within WCA3A (i.e., 618site 13 has a lower ground elevation). The mean snail density was calculated for each quarter619of the simulation period (2001-2005), with the standard deviation (SD) (n= 20 total quarterly 620calculations). 621 622 Quarterly QuarterlyBaseline % change % changeParameter Snail density Snail densityParameter* Value Site w/-20% BPV w/+20% BPV(submodel) (BPV) Mean ± SD (n=20) Mean ± SD (n=20) kgrowth (size) 0.05 13 -4.2 ± 2.7 1.6 ± 1.518 -3.1 ± 2.1 0.6 ± 1.6 ktemp (reproduction) -1.0 / °C 13 1.1 ± 1.0 -0.2 ± 0.8018 0.2 ± 1.0 -1.3 ± 1.0Tempthreshold 17 °C 13 5.5 ± 7.6 -21.7 ± 15.7(reproduction) 18 2.5 ± 3.4 -19.9 ± 12.1Depthmax 90 cm 13 -62.0 ± 17.1 0.0 ± 0.0(reproduction) 18 -12.1 ± 12.0 0.0 ± 0.0 w/-0.002 w/+0.002 (survival) (survival)Survwet1 0.987 / d 13 -1.4 ± 1.0 1.8 ± 0.9(survival) 18 -2.1 ± 1.3 1.3 ± 1.6Survwet2 0.987 / d 13 -1.1 ± 0.6 1.7 ± 1.0(survival) 18 -1.9 ± 1.4 0.9 ± 1.0Survwet3 0.987 / d 13 -1.0 ± 0.6 1.6 ± 1.0(survival) 18 -1.9 ± 1.4 0.9 ± 1.0Survwet4 0.990 / d 13 -100 ± 0.0 0.0 ± 0.0(survival) 18 -100 ± 0.1 0.0 ± 0.0 37 35 623*See Appendix 1 for description of parameters62462562662762862963063163263363463563638 36 637Appendix 4 Figure Headings638639Figure A4-1. Variation in model sensitivity through the simulation period when the 640Tempthreshold (for reproduction) was set at +20% of baseline, expressed on a quarterly basis for 641simulation years 2001-2005. Solid black line represents the average quarterly deviation in 642snail abundance from the baseline abundance after Tempthreshold was set at +20%. Dashed-gray643horizontal line represents 20.4 °C (+20% of the baseline 17 °C) in order to reference when 644input data fall below this temperature threshold, which yielded the greatest percent deviation 645in snail abundance. Temperature data used as input for the model (solid gray line) are shown 646for Site 18 (sensitivity results were very similar for Site 13, not shown).647648Figure A4-2. Variation in model sensitivity to Depthmax (for reproduction) expressed on a 649quarterly basis for simulation years 2001-2005. Solid black lines represent the average 650quarterly deviation in snail abundance from the baseline abundance after Depthmax was set at 651minus 20%. Dashed-gray horizontal lines represent 72 cm (-20% of the baseline 90 cm) in 652order to reference when input data fall below this depth threshold. EDEN-estimated depths 653(solid gray line) shown for Site 18 and Site 13 (the latter having a lower ground elevation).654655Figure A4-3. Landscape level output of the simulated Everglades total snail population 656associated with sensitivity analyses that lowered Depth Max for reproduction from the 657baseline setting of 90 cm (panel a) down to 72 cm (-20% of baseline) (panel b). The output is658for February 1st of 2004, which reflects a snail population exposed to relatively high water 659levels (Appendix 3) in the 2003 breeding season.66039 37 661Fig A4-1. -60.0 30.0-50.0 25.0 e c n -40.0 a d 20.0 ) n u C ( b e A -30.0 r l i u t a a n 15.0 r S e p n i -20.0 m e e g T n 10.0 a h -10.0 C% 5.0 0.0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 2001 2002 2003 2004 2005 10.0 0.0 66266366466540 38 666 fig A4-2.-100.0 100Site 18 90 -80.0 e 80 c n a d 70 n -60.0 u b A60 ) l i m a c n (S-40.0 50 h t n i p e e g D n 40 a h -20.0 C 30 %20 0.0 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 10 2001 2002 2003 2004 2005 20.0 0 667668 -100.0 100Site 13 90 -80.0 80 e c n 70 a d -60.0 n u ) b 60 A m l c i ( a-40.0 50 h n t S p e n i40 D e g n -20.0 a h 30 c% Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 20 0.0 2001 2002 2003 2004 2005 1020.0 0 66941 39 670FigA4-3671 Panel a. (depthmax=90) Panel b. (depthmax=72)67242 40

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