(2) Abstra ct: Woodlands have been wid ely cleared r esulting in modify ing ecosystems with single trees or small patches of trees. The effects that scattered trees have on their immediate area co mp ared to that of surroundin g p asture land h as been look ed extensively . However, the degree to which differ ent sized scattered trees contribute to the conservation of terrestrial invertebrates and microbial pop ulations remains unknown. In this study the following hy pothesis was tested: The mean invertebrate abundance and microbial p op ulations under different sized tree crowns differs from that in the nearest p oint in the grassland (3m* crown radius). In addition, the sp atial variation of microorganisms and inv ertebrates in terms of distance at breast height (DBH), asp ect and position from the stem was evalu ated. So il was sampled under the crowns and in the grassland adjacent to five Eucalliptus melliodora of different sizes. A total of 80 samples for microorganisms and 80 samp les for invertebrates were collected, at distances of 0.5 m, R/2, R, and 3*R (R = Crown radius) from the tree trunk. There were no differences in the abundance of invertebrates and microor gan isms under trees comp ared with surrounding grazed pasture. There was a signif icant (P = 0.0024) differen ce between the m ean m icrobial p opulations and asp ect. A borderline significant value (P = 0.056) was found between mean microbial p op ulations and DBH. A generalized linear regression model p roduced a highly signif icant (P = 0.0001) trend p redicting variation in microb ial p op ulations with DBH and asp ect. The probability of invertebrate p resence increased within larger trees and there was a strong effect between total litter and total nitrogen with invertebrate p resence. Results demonstrated that tree microclim ate alone do es not p redictably influence biota abundances and highlight some of the difficulties in interpreting microbial and inv ertebrate measurements in these landscap es. Moreover, is fundamental to have more rep lication and data to get a better understanding of how scattered tree environments define patterns in biota abundance. Key words: Differ ent sized trees, invertebrates, soil respiration, scattered trees, Eucalliptus melliodora, sp atial variation. INTRO DUCTION Woodlands throughout the world have suffered clearin g and fragmentation that are mainly due to agriculture activities. As a result scattered landscapes with single trees or small patches of trees are a common feature of the ecosy stems (Manning et al. 2006). With the currently rising of land-use p ractices, p addock trees are actually declinin g worldwide (Ozolins et al., 2001 ; Gibbons et a l., 2008 ; Fischer et al., 2010). Understanding that they are key stones structures is clearly an imp ortant and urgent task. The effects that scattered trees have on their immediate area co mp ared to that of surrounding pasture has been looked at extensively in many p arts of the world. Isolated trees contribute to local increase of nutrients as exp lored by Joffre and Rambal (1993), Wilson (2002) and Tiessen (2003). Scattered trees form associations with my corrhizal fungi, reduce erosion and contribute to the conservation of native p lants (Vetaas, 1992; Zhang et a l., 1999). In addition, they provide stepp ing-stones, which facilitate bird, bats and arboreal mam mals mov ement across the fragmented landscap e (Oliver et al., 2006; Fischer et al., 2010). However, the degree to which different sized p addock trees p rovide habitat for terrestrial invertebrate and microbial p op ulations is largely unknown.. 2.
(3) Scattered trees have b een shown to create a m icroclim ate below their canop y that differs to that of their surrounding grassland (Oliver et al., 2006; Carnovale, 2009; McElhinny et al., 2009). The breakdown of litter below the tree crown and the tree root activity maintain soil nutrient cy cling processes (McElhinny et al., 2009). In fact, dep ending of the diam eter at breast height DBH and the accumulated litter load throughout the time, nutrients availability may be higher below the trunk and decrease gradu ally with distance from the tree (C arnovale, 2009; McElhinny et al., 2009). In addition, the shading crown effect aids to buffer extremes conditions such as high temp erature, prevailing winds and low mo isture (Raich & Tufekcio glu, 2000). The combined eff ect of various biotic and abiotic conditions beneath the scatter tree crown may create ‘Islands of high fertility’ that provide a more comp lex habitat and food resources for microorganisms, and invertebrates comp ared to the gr assland (Pearce, 1999; Tang & Baldocchi, 2005; McElhinny et al., 2009). Addressing differences in soil biota abundances between soil above tree crowns and the gr assland would suggest that scattered trees are an imp ortant component of the ecosystem and that they p lay a critical role in maintainin g biolo gical activities thus, soil quality and fertility . Microbial activity has an important role in nutrient cy clin g. Microbial biomass affects rates of decomp osition and fertility. One parameter for evaluating microb ial activity or soil microbial p opulations is by measuring CO 2 fluxes as aerob ic respiration. Soil resp iration exhibits high sp atial and temp oral variab ility do to litter p roduction rates, soil temperature and moisture conditions (Keith et al., 1997; Raich & Tufekcioglu, 2000; Stoy an et al., 2000; Hadley & Sched lbauer, 2002; Eprona et al., 1999; Fernandez et a l., 2006). Sp atial h eterogeneity of soil respiration has b een related to litter accumulation. Litter production and soil respiration are p ositively correlated as found by Raich & Nadelhoffer (1989), Bowden (1993), Raich & Tufekcio glu (2000) and Chang (2008). Accord ing to Lohila (2003) and Han (2006) litter allocated into the soil might enhance the soil r espiration by stimulating m icrobial growth and activity . Temporal variations have been associated with chan ges in both soil temp erature and soil humidity. Evidence ind icates that the evolved CO 2 flu xes are positively correlated with these two abiotic factors (Howard & Howard, 1993; Stoyan et al., 2002; Smith & Johnson, 2004; Yuste et al., 2005; Lihua et al., 2007). Soil-dwellin g invertebrates are key sp ecies as they supp ort and regulate pop ulations of other organisms through p redation and p arasitism (San gha et al., 2006). The feed ing activities of collembo la and mite p opulations can determine the distribution and comp osition of fungal and bacterial co mmunities (Anderson & Domsch, 1998; Pearce, 1999; Oliver et al., 2006). Additionally, they p lay imp ortant roles on soil processes through their feeding and burrowing activities. Soil invertebrates promote nutrient cycling (Carnovale, 2009), water retention and soil structure (Pearce, 1999). As mentioned above scattered trees may p rovide better habitat for invertebrates. For example Oliver (2006) found that scattered trees make an imp ortant contribution to the conservation of terrestrial invertebrates in landscap es dominated by grazing systems. Pearce (1998) showed that isolated trees are capable of supp orting a diverse invertebrate community of native species that are less well represented in the grassland commun ity . Majer (1999) indicated that the invertebrate conservation p otential of scattered trees was enhanced if the trees were lar ge, were n ative to the area and sup ported a high epip hyte load.. 3.
(4) The overall aim of this study was to investigate whether soil below different sized p addock trees offer more fertile substrate and less stressed conditions for soil microor gan isms and invertebrates co mp ared with the surroundin g p asture. Specifically , the objectives of this study were: (1) to find out weather the mean invertebrate abundance and soil resp iration under d ifferent sized tree crowns differs from that in the grassland; (2) to ch aracterize the sp atial var iation of invertebrate abundance and soil respiration in a scattered tree env ironment in terms of asp ect, distance from the trunk and (DBH) and to relate this spatial variation to environmental conditions; (3) to p redict a signif icant soil respiration and invertebrate mod el in terms of DBH, distance from the tree stem and asp ect and the interaction of these variables. MET HODS S tudy area The study was conducted at Goorooy arroo Nature Reserve located in the Australian Cap ital Territory, during early sp ring. This reserve is part of the Mulligans FlatGoorooy arroo Woodland Exp erim ent, a joint venture between the Australian Cap ital Territory Government and The Australian National University (Manning, 2008). The nature reserve comp rises one of the lar gest areas of Eucalyptus m elliodora in the ACT region, which is a critically endangered ecolo gical community in Australia (ACT Dep artment of Territory and Municip al services 2009). The reserve covers an area of app roximately 700 ha. This site was declared a nature reserv e in 2004. Sin ce then grazing and collection of firewood has ceased. Subsequently, the site offered a scattered tree environment with a relatively intact litter layer (McElhinny et al., 2009). Field Data: Soil Collection (tree vs. grassland) A samp le of five sp ecies of Eucalyptus m elliodo ra was chosen. Each sample was of different size across a DBH from 15 cm to 140 cm. All trees were located on flat terrain accordin g to a p revious study conducted by Carnovale (2009). For each tree, four transects were established fro m the tree stem to the grassland in the northerly , southerly, easterly , and westerly directions. On each transect, 8 samples were taken at a stem distance of 0.5 m, R /2, R, and 3*R (R = Crown radius). At each sample point, litter was removed and the ground lay er vegetation was clipp ed to reduce root interference (Fig. 1). A total of 160 samp les were collected, 80 for invertebrates and other 80 for soil respiration. App roximately 100g of soil p er samp le was collected in p oly ethy lene bags and then dried for 24 hours to standardize moisture. Field Data: analysis of the methods (Tree vs. Grassland) The high heterogeneity among sites in terms of terrain slop e, soil fertility , water content, temperature etc. may have biased the an alysis. To eliminate this variation and just quantify the effects of the tree relative to the nearest point in the grassland a p aired design was used to collect samp les for soil resp iration and invertebrates.. 4.
(5) Fig. 1. Sample design used in this study at each of the five trees to investigat e microbial and invertebrate abundances (n = 160). Arrows indi cate the prevailing wind di rection; R is the crow radi us; each pair of small circl es show sample point locati ons, one for invert ebrat es and the other for soil respiration; the small cloud indi cat es low humidity while the large one indicates high humidity. Note that the coolest and more humid aspect is the south followed by the east, then the west and finally the north (Adapted from Carnoval e, 2009).. Laboratory analysis for soil respiration: Alkali adsorption method For estimating soil resp iration, an adap tation of the alkali- absorp tion method was used in this study to measure CO2 flux. Details of the method are provided in Wollum and Gomez (1969). The authors used sodium hy droxide as the absorbing alkali. In the p resent study, p otassium hy droxide ( alkali) was used according to Drake (2009). This electrical conductivity (EC) p rocedure was selected because of its simp licity, low cost, replicability , and its capacity to measure CO 2 effluxes in the laboratory, and hence suitability for measuring large amount of samp les in differ ent day s under controlled conditions. The alkali absorption method has been used in a wide ran ge of ecosystems includin g temp erate, trop ical, subtrop ical and agricultural ecosystems (Hulm et al., 1991; Jensen et al., 1996; Yim et al., 2002; Bijay alaxmi & Yadava, 2009). This p rocedure depends particularly up on soil temperature, water content, surface ar ea and time. It is imp ortant to standardise these factors to avoid bias and increase p recision (Fig. 2). Reaction 1 shows the change with CO 2. Reaction 1: KOH + CO 2 ⇒ K 2CO 3+ H2O. 5.
(6) Fig. 2. Alkali absorption method (Drake, 2009). Respiration Steps: a) Weight out 100g of soil into small containers and place into airtight contai ners b) Make up fresh 0.5M KOH adding 1 amphoule of 1M KOH to a 1L volumetric flask c) Add 8.8mL of 0.5M KOH to the vi als and place in containers. d) Put lid on contai ners and record number and time. e) After ~24 hours, remove vials from containers and record number and time. Expired KOH Analysis: f) Calibrat e the EC meter using the 1M KCl solution. g) Measure and record the EC and temperature for each vial.. Laboratory analysis: CO 2efflux measurements Soil CO 2 eff lux was measured over 24 hour p eriods during the 6 day s, from the 28th of Sep tember until 3rd of October of 2009. The first day, a fresh 0.5M KOH was made addin g 1 Amp houle of 1M KOH to a 1L volumetric flask. The flask was filled with distilled water until the mark and shak en well by inverting 20 times. Subsequently , 16 from the 80 samp les were selected randomly. For each samp le, 100 g of soil were weighted into a 69.3 cm2 round numbered container without lid (fine roots were removed so that the resp iration of soil microbiota was assessed). Following the app lication of 20 mL of deionized water the sample was p laced into an airtight container. In addition to the soil, the airtight chamber also had a vial, previously numbered to correspond with containers, with 8.8 mL of 0.5M KOH to trap the CO2 evolved. Im mediately after the chamber was sealed, number, time and date was recorded. A blank was also p rep ared accord ing to the method described above with out the soil to account for the amount of CO2 absorbed by the p otassium hy droxide in the headspace of the airtight container. After 24 hours of incubation, the chamb er was opened and the vials were removed from the chambers. To estimate the amount of CO2 evolved, the electric conductivity of the now p otassium carbonate was measured by a previous calibrated EC m eter using 1M KCL solution. Time, date off, EC and temp erature were recorded (Fig. 2). Laboratory analysis: Temperature calibration for the correction of EC Finally, as EC of aqueous solutions and soils is strongly dep endent on temperature, it was necessary to correct values by calibr ating temperature and the corresp onding EC. For this, the fresh 0.5M KOH was taken out from the frid ge and placed in a warm water bath. The EC of the solution was recorded at each degree from 18.5 – 24.5 ºC. 6.
(7) (Fig. 3). Subsequently , the values obtained were entered in a sp readsheet accordin g to Drake (2009), where the followin g sin gle linear regr ession model was obtained : 2 [Equation 1] Æ y = -0.7301x + 139.27 R = 0.9816 Finally this equation was used to correct the EC of the fresh KOH.. Fig. 3. Procedure for temperat ure Calibration according to Drake 2009: a) Take cold 0.5M KOH out of the fridge and place in a warm water bath b) R ecord the EC of the KOH at each degree from 16 - 25ºC c) This will be entered into the spreadsheet in excel and used as a correction.. Invertebrate extraction: Tullgren funnels Invertebrates were extracted using tullgren funnels d esigned by Dumaresq and Carruthers (1994). Stainless steel cor e tubes (5x5 cm) (samp les) were p laced in a tray with 2 rows of 10 holes. Glass funnels were inserted into each hole. The tray was p laced in the extraction unit that consisted of 20 light globes, susp ended from above, that heated up each sample. The heat p rovided from above drove the fauna downwards into the glass funnels and finally in collectin g jars filled with ethanol (Fig. 4). The contents of each p lastic jar were p laced in sep arated petri dishes, and with the aid of microscop es, were sorted into order level.. 7.
(8) Fig. 4. Diagram of the tullgren funnel used in this study. Each unit is suitable to extract 20 sampl es at the same time. a) electric bulb to heat t he samples b) soil cores c) glass funnels d) collecting jars with ethanol.. S tatistical analysis A p aired difference analysis was used for all the stages of data an aly sis via subtracting above crown resp iration from grassland resp iration (R T – R G) and biota p resence in the grassland from biota p resence above the crown (BG – B T). To investigate if soil below different sized p addock trees offers more f ertile substrate for soil microor gan isms and invertebrates compared with the surrounding p asture the followin g question was addressed: Is there a difference in mean soil resp ira tion and m ean invertebrate abundance belo w scattered trees and th e nea rest g rassland? To investigate the spatial variation of soil respiration and invertebrates in a scattered tree environment and to relate this sp atial variation to environ mental conditions the followin g questions were addressed: 1) Can aspect, DBH and d istance from the tree explain sp ecia l patrons in soil respiration and invertebra te abundance? One-way analy sis of variance was used to compare the mean for resp iration (Diff) and mean for biota total in terms of asp ect, DBH, and position. A comp arison for each p air of means was p erformed using student’s t analysis. 2) It is possible to p redict a significan t respiration (Diff) and biota total ( Diff) model in terms of DBH, distan ce from the tree stem and aspect and the interaction of th ese variables? A generalized linear regression was used. Only sign ificant (P < 0.05) or borderline signif icant var iables were r etained in the f inal model. All the data was analysed using JMP 7 statistical software.. 8.
(9) 3) Does the va riations in surface soil properties such a s bulk den sity, percentage of organic ca rbon, to tal litter and total nitrogen produce patterns in soil biota presence/ab sence? Nominal lo gistic fit was used to asses the probability of biota being present or absent in relation to soil p rop erties such as bulk density , p ercentage of organ ic carbon, total litter in tonnes p er hectare and total nitrogen in p art p er million. RES ULTS Is there a difference in the mean soil respiration and the mean invertebrate abundance below scattered trees and the nearest grassland? The distribution across respiration and biota total d ifferen ce h ad a mean of 4.1 and 0.05 respectively. With 95% of confidence the upp er mean for respiration was 19.3 and the lower mean was -11.1, for biota total the upp er mean was 0.85 and the lower mean was -0.75. Accordin g to these values, and particularly as the means were close to 0, there were not a resp iration and biota total difference between the grassland and the soil above the crown of p addock trees. Figur e 5a also shows there was a lot of variation in the respiration (diff) with a Standard Deviation of 59. This variation makes it difficu lt to test whether the tree environment is havin g an eff ect. Figur e 5b did not show large amount of variation, with a Standard Deviation of 3.08.. Fig. 5. Graphs of the distribution of the di fference between soil respi ration and biot a total di fference under the t ree and not under the tree. The Y-axis is the frequency or the number o f times a parti cular value occurred. 5a) Mean distribution for respiration difference (n = 60). The mean 4.1, was not signifi cant different to cero. W ith a 95% of confidence, the upper mean was 19.3 and a lower mean was -11.1. 5b) Mean distribution for bi ota total difference (n = 60). The mean (0.05) was not signi ficant di fferent to cero. W ith a 95% of confidence, the upper mean was 0.85 and a lower mean was -0.75.. 1) Can aspect, DBH and distance from the tree explain special patrons in soil respiration and invertebrate abundance? One-way ANOVA was used to find p atrons among mean respiration (Diff) and mean biota total (Diff) in terms of aspect, DBH and position. For resp iration (Diff), p osition did not show a significant effect with all the means close to 0, so was removed from the resp iration (Diff) analy sis (Fig. 6a). The relationship between respiration (Diff) and DBH was borderline signif icant (P = 0.056) (Fig. 6b). Comparison for each p air of means did not show a defined p attern. Mean resp iration (Diff) was notably low in 9.
(10) the bigger tree (DBH = 139; µ = -35.44) and particularly high in the medium-big tree (DBH = 87; µ = 34.92). There was a significant effect between asp ect and r esp iration (Diff) (P = 0.0024). The comparison amon g p air of means showed that southerly asp ect was significantly different to easterly (P = 0.0022) and northerly (P = 0.0007) asp ects and west direction was signif icantly different to north direction (P = 0.049). 2 The mean resp iration (Diff) in southerly (45 mgCO2/m /hr) and westerly (15 2 mgCO2/m /hr) directions was higher than the means resp iration (Diff) in easterly 2 2 (17.4 mgCO 2/m /hr) and northerly (-25 m gCO 2/m /hr) aspects (Fig. 6c).. Fig. 6. Comparison of mean respi ration and biot a tot al di fference (n=120) i n terms of position from the tree: trunk (T), middl e (M), edge (E); di ameter at breast height and aspect: north (N), south (S), east (E), west (W ). The diamond represent 95% of confi dence and the line correspond to the mean. Means with the same letter are not significantly di fferent.. For biota total (Diff), the relations between p osition (P = 0.2459), DBH (P = 0.1487) and asp ect (P = 0.92) were not signif icant with all the means close to 0 (Fig. 6 d, e, f). For this reason, it was necessary to build up contingen cy tables to analy ze the p robability of biota p resence/absence with asp ect, DBH and position. In terms of asp ect, for east and south, the coolest and humid places, the p robability of biota p resence was high (73% and 80% resp ectively ). The probability of obtaining the outcome in biota p resence/absence by chance was 44% (P = 0.44) (Table 1a). For. 10.
(11) p osition, there was no marked trend of biota presence, what means that p osition did not disp lay any variation in the probability of invertebrate abundance. The p robability of obtaining the results by chance was 92% (P = 0.92) (Table 1b). In terms of DBH there was such a m arked effect of size of tree amon g biota p resence with a chance p robability of 0.023% (P= 0.0024*) (Table 1 c). The results showed the probability of biota presence incr eased within lar ge trees. The likelihood of b iota p resence was h igh for the large trees (139 cm) and declined as trees became sm aller.. Table 1. Contingency t abl es to find the likelihood of biot a presence (n=60) in terms of: a) Aspect, where the probability of getting the results by chance was 44% (P=0.44). b) Position, where the probability of getting the results by chance was 92% (P= 0.92). c) DBH where the likelihood o f getting the results by chance was 0.023% (P= 0.0024*). For DBH the chance probability was suffi ciently small, thus big trees have an effect on biota P/A.. 2) It is possible to predict a significant respiration (Diff) and biota total (Diff) model in terms of DBH, distance from the tree stem and aspect and the interaction of these variables? Linear r egression analy sis was used to model the spatial variation in r esp iration (Diff). The model had aspect and DBH as exp lanatory variables. For DBH and the interaction between asp ect and DBH the models that were fitted were sign ificant ( P < 0.05). For aspect the fitted model was highly significant (P = 0.0001), therefor e to see the effect of asp ect four regression equations were p lotted (one for each aspect) that p redicted the variation in respiration (Diff) with size of the tree (Table 2). The multiple regression equ ations indicated a negative relationship between resp iration (Diff) and DBH in the north, west and east asp ects (Fig. 7). The whole model exp lain ed 48% of the v ariation. Scattered p lots of the residuals versus the p redicted variables were used to check if the models fitted the data well. The residuals p lots for these models were app roximately normally distributed, with little heteroscedasticity thus, the quality of the fitted model was adequate. Due to asp ect, p osition and DBH did not have a significant effect in biota total (Diff) it was not p ossible to predict a significant model that p redicted invertebrate abundance. Thus, the p robability of biota presence in terms of asp ect, distance from the trunk and DBH was assessed.. 11.
(12) Table 2. Plotted regression equations to predict the effect of aspect in t erms o f respiration (Diff) and DBH (cm). The general equation was: Respiration (Di ff) = a + b*(DBH) + aspect + asp ect *(D BH).. Fig. 7. Predicted change in respiration (Di ff) with DBH (cm) and for north, south, east, and west directions, using the equations in Table 2. (r2 = 0.48) (P =0.0001 ).. 3) Does the variations in surface soil properties such as bulk density, percentage of organic carbon, total litter and total nitrogen produce patterns in soil biota presence/absence? A nominal logistic plot was used to p redict the probability of biota being present in terms of soil properties. Bulk density and organic carbon were not sign ificant (P>0.05) (Fig. 8 a, b). There was a strong effect b etween total litter and biota P/A, and total nitrogen and biota P/A. Both mod els were h ighly significant indicating that the p robability of biota absence decline as total litter t/ha and total nitrogen pp m increased (Fig. 8 c, d).. 12.
(13) Fig. 8. Nominal logistic fit to find out i f bi ota P/A is affect ed by soil properti es (n=60). The trend curve represents the probability of not presence.. DIS CUSSION Is there a difference in the mean soil respiration and the mean invertebrate abundance below scattered trees and the nearest grassland? Results did not show any app reciable difference between the resp ired flu xes and the mean inv ertebrate abundance above trees and the nearest p oint in the grassland. The environment under tree crowns accumulated more litter mass and or ganic matter than grasslands environments (Gomoryova, 2004; Cornovale, 2009 ; McElhinny et al., 2009). This increased mass under tree crowns correlates p ositively with invertebrate and microbial p op ulations (Uetz, 1979; Martin & M ajor, 2001; Oliver et al., 2006). Given this, soil respiration and invertebrate abundance should be higher below the tree crown than in the p asture. However, other soil characteristics such as temp erature, p H, soil typ e and moisture are related with the sp atial variation of soil biological activity (Gomoryova, 2004). The fine scale var iation of these factors makes it difficult to test whether the tree environment is havin g an effect. Several studies have investigated the sp atial variation of these factors at various scales, and have found that microbial and invertebrate communities can vary at any number of scales: fro m the “micro” scale ( millimetres) (Morris, 1999; Stoy an et al., 2000), over sev eral metres (Bruckner et al., 1999). Thus, the knowledge of sm all-scale v ariation of these soil characteristics is crucial for determining the necessary distance of indep endent soil samp ling. Oliver (2006) found that the distance of indep endent samples for microbes and invertebrates were around 10 m. In this study there were no differences between the surface soil below the tree canopy and the grassland probably due to the distance. 13.
(14) of soil samp ling. Additionally , in this study the sample p oint for the grassland was located 3 m mu ltip lying crown radius away from the tree trunk. This was the distance thought necessary to avoid any effect from the tree environment. Jacobs (1955) found that most of the Eucaly ptus sp ecies growing in scattered woodlands in Australia have shallow roots that spread out possibly 30 m from the trunk. Dye (1996) studied the root system of Eucalyptus species in South Africa and found liv e roots at 28 m below the surface. According to this, the distance used to samp le the nearest p oint in the grassland (3 m* crown radius) was not enough to avoid the tree environment effects. 1) Can aspect, DBH and distance from the tree explain special patrons in soil respiration and invertebrate abundance? In this study soil resp iration was only significantly different in terms of asp ect and borderline sign ificant in terms of DBH. South direction, the humid asp ect, showed a substantial incr ease in respiration (Diff) meanin g that humidity is p ulling up CO2 fluxes during this time of the year. In the dry soil of the north asp ect soil resp iration was dep ressed. This suggests that it is possible to relate the sp atial variation of microbial soil activity directly to p lant-mediated effects on soil microclimate as found by Gomory ova (2004), Gengche (2004), Tang & Baldo cchi (2005), and Papa (2008). Furthermore, the biggest tree (DBH 139 cm) showed a decrease in resp iration difference. This is surp rising because the positive relationship of litter p roduction and soil resp iration, and the p ositive correlation of litter load under crowns and stem size had bein g confir med by many other studies (Raich & Nadelhoffer, 1989; Adu-Bredu et al., 1997; Bowden et al., 1992; Grigg & Mulligan, 1999; Raich & Tufekcio glu, 2000; M cElhinny et al., 2009). However, due to soil respiration is a net flux deriv ed from several different processes (temperature, moisture availability and nutrients), chan ges occurring in any single process can be masked by op p osite changes in another (Raich & Nadelhoff er, 1989). Var iation between these variables and soil resp iration has been commonly observed in temp erate regions (Ch ander & Brookes, 1991; Ep rona et al., 2004; Tang & Baldocchi, 2005; Had ley & Schedlbauer, 2002). In this study it was not p ossible to sep arate the effects of temp erature, moisture availability and nutrients on soil resp iration, consequently a conclusive spatiotemp oral p attern of soil respiration was very difficult to distinguish p robably because the surrogate m easurem ents DBH, distance from the tree and asp ect are not app rop riate for this typ e of analysis. 2) It is possible to predict a significant respiration (Diff) model in terms of DBH, distance from the tree stem and aspect and the interaction of these variables? The model obtained suggested a correlation of soil respiration (Diff) and DBH in terms of aspect (P=0.0001). Therefore, aspect and DBH explained 48% of the variation in soil r espiration in scattered ecosystems. The model (Fig. 7) p redicted resp iration (Diff) would decrease as the stem size become b igger in north, west and east directions with dry soil. This can be attributed to low soil moisture and in addition, the shadin g of the crown reduces soil surface temp erature and thus, soil resp iration (Hoch et al., 2002; Stoy an et al., 2002; Smith & Johnson, 2004; Lihua, 2007; Carnovale, 2009). Nonetheless southerly asp ect, with high water content, did not follow this p attern. The regression equation p redicted an increase in soil resp iration with stem size. Thus, higher soil moisture contents are p ulling up CO2 fluxes, and possibly masked the shading crown effect (Raich & Tufekcio glu, 2000).. 14.
(15) These results indicate that tree microclimate alon e does not predictably influence soil resp iration rates. Thus, to capture patterns of soil resp iration it may be important to analy se temperature, humidity and nutrients separately. - The p robability of biota presence differs with aspect, distan ce from the trunk and DBH. Possibly due to the lack of data it was necessary to model the p robability of biota p resence in terms of aspect, distance from the trunk and DBH. Aspect and p osition were not significant. However, the cooler and humid aspects (west and south) were more likely to increase the p robability of biota p resence than the warm and dry asp ects (north and west). This was similar to the pattern observed by Coulson (1996), although they did not investigate scattered ecosy stems, they found that during warm dry conditions invertebrate abundance, specifically Collembola numbers, declin ed. Distance from the trunk showed no trend in the p robability of biota p resence. Previous studies have shown that gradients in litter or distances from the tree bases exp lain ed signif icant amounts of variation in invertebrate communities (Oliver et al., 2000; Mcelhinny et al., 2009). Size of tree was correlated with the p robability of biota p resence. The large litter mass under trees with large crowns is likely to increase the p robability of biota presence as they offer a more comp lex habitat (Mcelhinny et al., 2009). There was no lin ear increase observed in the p robability of biota presence with DBH as the small to medium-small sized trees showed anomalous p robabilities (Table 1c). For examp le, accordin g to the results, small trees (15.5 cm DBH) are more likely to increase the p robability of biota presence (58%) than medium-sm all sized trees (35 cm DBH) (25%). This may be due to p articular conditions within each tree, as fertility , soil p orosity , terrain slope etc. had gr eater effects on biota than the accumu lated litter load. Those sp ecific conditions of each tree may bias the results, thus it is important to have rep licates of each tree size class. 3) Does the variations in surface soil properties such as bulk density, percentage of organic carbon, total litter and total nitrogen produce patterns in soil biota presence/absence? Gradients in litter and total nitro gen exp lained the p robability of biota p resence. As observed by Oliver (2006) there is a p ositive relationship between these two variables and invertebrates abundan ce. This study has shown that the p robability of biota p resence is particularly sensitive to total nitrogen. Soil invertebrates release nitrogen through consumption of microbial bio mass. In fact they mediate about 30% on the nitrogen turnover (Aber, 1989; Anderson & Domsch, 1998). Total litter resulted in the same p ositive relationships found by Oliver (2006) and Carnovale (2009). Accumulated litter load provides food and shelter for invertebrates and also may have a p ositive feedback effect on soil nutrients and thus, the p robability of finding invertebrates. Although bulk density and percentage of or gan ic carbon had no signif icant eff ects, the trends were consistent with Oliver (2006) and Carnovale (2009). Invertebrate burrowin g activities create tunnels that may decrease soil density and incr ease soil dwellin g-invertebrates (Anderson & Domsch, 1998). In addition, organ ic carbon is a food source for invertebrates (Wolters, 2000), thus as percentage of organ ic carbon incr eases the probability of not finding biota in creases as well.. 15.
(16) Management im plications Although there were no ap preciable differences between surface soil in different sized scattered trees and the nearest point in the grassland it is clear that at some p oint is p ossible to relate the sp atial variation of soil activity to p lant-mediated effects on soil microclimate. The general consensus is that scattered trees are p ivotal in terrestrial ecosystems being focal p oints for p rocesses such as nutrient cycling (Majer, 1999; Oliver et al., 2006; McElhinny et a l., 2009; C arnovale, 2009). For the m anagement of these woodlands, the Precautionary Principle that states that where there are threats of serious or irrev ersible environmental damage, lack of fu ll scientific certainty should not be used as a reason for postponing measures to p revent environmental degr adation is imperative. Thus conservation-eff ective efforts have to con centrate on scattered trees of all sizes. Future Implication s This study has shown that DBH, asp ect and p osition as surrogates for temp erature humidity and nutrients may cancel the effect over invertebrates and microbial p op ulations. Future work should consider measuring temperature, hum idity and nutrients directly to avoid overlapping interactions. Knowledge about the necessary distance of independent soil sampling is vital. For invertebrate extraction, further work should consider samp ling invertebrates with p itfall traps instead of soil cores as used by Oliver (2006). Is fundamental to have more rep lication and measurements of different tree species and if that is the case, just big trees should be samp led to understand how scattered tree environments define p atterns in the abundance of soildwellin g or ganisms. This may help to determine the variability and the resp onse of soil biota commun ities to disturbance such the clearin g of woodlands ecosy stem.. 16.
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