DESCRIPTION OF MICROHABITAT BASED ON PLANT COVER

795

A DEVICE AND STANDARD VARIABLES TO DESCRIBE MICROHABITAT STRUCTURE OF SMALL MAMMALS BASED ON PLANT COVER FREITAS, S. R., CERQUEIRA, R. & VIEIRA, M. V. Laboratório de Vertebrados, Departamento de Ecologia, Universidade Federal do Rio de Janeiro, C. P. 68020, CEP 21941-590, Rio de Janeiro, RJ, Brazil Correspondence to: Simone R. Freitas, Laboratório de Vertebrados, Departamento de Ecologia, Universidade Federal do Rio de Janeiro, C. P. 68020, CEP 21941-590, Rio de Janeiro, RJ, Brazil, e-mail: [email protected] Received December 12, 2000 – Accepted May 21, 2001 – Distributed November 30, 2002

(With 3 figures) ABSTRACT Studies quantifying habitat structure generally use several instruments. This paper aims to propose a new and efficient device to characterize microhabitat structure of small mammals. Seven measurements were taken: plant cover, litter cover, rock cover, canopy cover, and vegetative obstruction at three heights. The device is a 0.25 m2 square wooden frame (0.50 m x 0.50 m) divided in to 100 open squares by wire mesh. Average time spent to measure each trapping station was six minutes. This new device is efficient, i.e., quick, practical, simple, and reliable. It can be used in any kind of forest. We propose this method as a standard method to describe habitat structure. Key words: habitat, methods, neotropics, small mammals, techniques. RESUMO Um instrumento e variáveis-padrão para descrever a estrutura do microhabitat de pequenos mamíferos baseada na cobertura vegetal Os estudos que quantificam a estrutura do habitat geralmente usam vários instrumentos. Este artigo objetiva propor um novo e eficiente instrumento para caracterizar a estrutura do microhabitat de pequenos mamíferos. Sete medidas foram tomadas: cobertura vegetal (herbáceos e lenhosos), cobertura de folhiço, cobertura de pedras, cobertura de dossel e obstrução foliar vertical em três alturas. O instrumento é uma tela quadrada de 0,25 m2 (0,50 m x 0,50 m) de madeira, dividida por arame em 100 quadrados abertos. O tempo médio para medir cada estação de captura foi de 6 minutos. Este novo instrumento é eficiente, isto é, rápido, prático, simples e confiável. Ele pode ser usado em qualquer tipo de floresta. Propomos este método como padrão para descrever a estrutura do habitat. Palavras-chave: habitat, métodos, neotrópicos, pequenos mamíferos, técnicas. INTRODUCTION A variety of qualitative and quantitative methods are available to characterize habitat structure (Barnett & Dutton, 1995). Qualitative studies define vegetational types using plant or floristic physiognomy. Quantitative studies measure a set of habitat variables considered important to determine local distribution of the animals studied

(Morrison et al., 1992). Habitat structure has been quantified by several instruments (Morrison et al., 1992), and by a different set of variables in each study. For most studies only a few habitat variables are standard, such as canopy height and number of trees with DBH range defined (James, 1971; Dueser & Shugart, 1978; August, 1983; Thomas & Verner, 1986). Therefore, measures of habitat structure of different studies are seldom comparable.

Braz. J. Biol., 62(4B): 795-800, 2002

796

FREITAS, S. R., CERQUEIRA, R. & VIEIRA, M. V.

At the same time most habitat quantification techniques take a great deal of time and effort, especially in tropical rainforests (Barnett & Dutton, 1995). We have been studying small mammal microhabitats. To lessen the problems referred to, we developed a device to measure all variables in a standard set. The device gives fast and easy readings of the variables which were chosen to minimize the well-known effect of temporal variation in habitat structure (Dueser & Shugart, 1978; Freitas, 1998). The set of variables corresponds to factors we regard as relevant to a variety of small mammal species investigated in previous studies (Birney et al., 1976; Dueser & Shugart, 1978; Barnum et al., 1992; Cassini & Galante, 1992; Morrison et al., 1992; Freitas, 1998). Plant cover is considered a major determinant of local distribution and abundance of small mammals (Birney et al., 1976; Barnum et al., 1992; Cassini & Galante, 1992). Hence, the device shown in this paper chiefly measures factors related to plant cover. Herein, we describe the new device and the set of standard variables to describe habitat structure relevant to small mammals. Habitat measurements must be repeatable and, therefore, we tested the repeatability of the proposed device which is applied to studies in forests. MATERIAL AND METHODS The method using the device was tested in a mountainside locality of the Atlantic Forest in the Serra dos Órgãos (22 o28’28”S and 42o59’86”W), Guapimirim Municipality, Rio de Janeiro State, Brazil. Serra dos Órgãos is a mountain range running through several municipalities in Rio de Janeiro State. The general type of vegetation has been classified as Montane Pluvial Atlantic Forest (Rizzini, 1979). Three grids of 0.64 ha were established in the area at different altitudes (748 m, 652 m, and 522 m) as part of an ongoing mark-recapture study of small mammal populations. Each grid had 25 trapping stations, 20 m apart, and a stake marking the center of each trapping station. Four lateral stakes were established 3 m away from the central stake, forming a cross aligned with the cardinal points (north, south, east, and west). Hence, each trapping station had five stakes (Fig. 1A). Microhabitat variables

Braz. J. Biol., 62(4B): 795-800, 2002

were measured simultaneously with trapping sessions of small mammals as suggested by Murúa et al. (1996) and Cerqueira & Freitas (1999). In each trapping station, traps of small mammals were always placed at or near the central stake, inside the 36 m2 square formed by the stakes. The device is a 0.25 m2 square wooden frame (0.50 x 0.50 m) divided in to 100 open squares by wire mesh (Fig. 1B). It measures seven microhabitat variables (Table 1). Each measurement consists in a count of the number of squares visually obstructed, defined as any square with more than 50% visual obstruction. Squares less than 50% obstructed are considered empty. PLANT, LITTER, ROCK, and CANOPY are measured at the five stakes of each trapping station. PLANT, LITTER, and ROCK are measured, by the observer holding the frame parallel to the ground near his knees (Fig. 2A). Portions of bare ground are also measured and added to the total area measured. PLANT, LITTER, and ROCK are measured, recalling that these microhabitat variables are complementary, their sum being equal to 100% after portions of bare ground are included. CANOPY is measured by the observer holding the frame at a horizontal position above his head, with arms extended (Fig. 2B). The observer has to measure the percentage of closed areas in the canopy. OBSTR1, OBSTR2, and OBSTR3 are measured with the frame held vertically at three heights (0.50 m, 1.00 m, and 1.50 m), as the observer stands at the central stake pointing the frame to each of the other four stakes (Figs. 2C, 2D, and 2E). The observer has to estimate the percentage of obstruction between the frame and the pointed stake by imagining a wall right behind this stake. Hence, the observer must focus only in the 3 m range between the frame and the stake. The number of logs (trunks fallen on the ground) with perimeters at breast height greater than 0.20 m) is counted inside the 36 m2 square limited by the stakes (Fig. 1A). Estimates of plant, litter, rock, and canopy cover are made for the 36 m2 area around the central stake limited by four lateral stakes. The relative precision of the method was tested through a repeatability experiment. This method, a total of 25 observers using measured five trapping stations three times. A coefficient of variation (CV) was calculated based on his three repeated measures of each observer at each trapping station.

DESCRIPTION OF MICROHABITAT BASED ON PLANT COVER

797

N

A)

E

3m W S

0.50 m B)

0.50 m

Fig. 1 — A) Square of 36 m2 where habitat measurements were taken. The square was delimited by four stakes aligned with cardinal points (north, south, east, and west) placed 3 m away from a central staked. B) Instrument used to describe habitat structure.

TABLE 1 Description of microhabitat variables.

Variables

Description

PLANT

Plant cover on the ground

LITTER

Litter cover on the ground

ROCK

Rock cover on the ground

CANOPY

Canopy cover

OBSTR1

Obstruction from 0.00 to 0.50 m high

OBSTR2

Obstruction from 0.50 to 1.00 m high

OBSTR3

Obstruction from 1.00 to 1.50 m high

Braz. J. Biol., 62(4B): 795-800, 2002

798

FREITAS, S. R., CERQUEIRA, R. & VIEIRA, M. V.

Hence, there were five CVs per observer. A mean CV was calculated for each observer, based on his five CVs. Habitat variables were measured at every trapping station in the grids during a oneyear period, from February 1997 to February 1998. The performance of each habitat variable was analyzed both separately and together. Our hypothesis was that measurements of the observers varied less than habitat measurements between trapping stations and seasons. The mean CV of observers was compared to the mean CV of habitat variables between trapping stations and seasons. The percentage of observers with mean CV lower than the mean CV of the habitat was the measure of relative precision. To determine if observers measured similarly to each other, we compared the CV of habitat variables measured by two observers in the same day at the same trapping stations to the CV of habitat variables between trapping points and seasons. If the mean CV between measures of two observers was lower than the mean CV of habitat variables, then the measures taken by observers were considered comparable.

RESULTS Measuring each trapping station averaged 6 minutes (SD = 2 min, N = 61). Comparing the frequency distributions of CVs of all habitat variables to CVs of all 25 observers, 17 observers were below the lower CV of habitat variables in one year. In other words, 68% of the observers varied in their replications less than the habitat variation found in each grid in each trapping session during one year of study. The relative precision of some variables was even higher individually: OBSTR3 obtained 100% of CV of replications smaller than the CV of habitat, 96% of PLANT and ROCK, 92% of OBSTR1 and CANOPY, 88% of OBSTR2, and 80% of LITTER (Fig. 3). Six out of 17 pairs of observers had mean CVs between observers lower than the mean CVs of habitat variables. Some variables were less affected than others by the readings of different observers. Hence, ROCK had 94% of the CVs between observers lower than the CV of habitat in one year, PLANT and OBSTR3 had 88%; OBSTR1, 82%; CANOPY, 77%; OBSTR2, 71%; and LITTER, 59%.

Fig. 2 — Postures of the observers measuring habitat variables, (1) PLANT, LITTER and ROCK, (2) CANOPY, (3) OBSTR1, (4) OBSTR2, and (5) OBSTR3.

Braz. J. Biol., 62(4B): 795-800, 2002

DESCRIPTION OF MICROHABITAT BASED ON PLANT COVER

CV Observers

Habitat

D)

Habitat

Observers

F)

OBSTR1 mean=32% sd=5%

mean=14% sd=7%

CV

Observers

Habitat

G)

Observers

OBSTR3

37 %

mean=34% sd=5%

3 0 %

23 %

16 %

mean=14% sd=5%

44 %

8 7 6 5 4 3 2 1 0

9 %

Frequency

%

mean=33% sd=6%

CV Habitat

24

OBSTR2

10 8 6 4 2 0

Frequency

mean=14% sd=9%

Observers

13 % 17 % 21 % 24 % 28 % 32 % 36 % 39 % 43 % 47 % 51 % M or e

12 10 8 6 4 2 0

5% 8% 12 % 15 % 19 % 22 % 25 % 29 % 32 % 36 % 39 % 42 % 46 % M or e

Frequency

E)

36 %

CV

CV Habitat

%

mean=17% sd=6%

31 %

5%

mean=5% sd=3%

26 %

mean=162% sd=67%

21 %

mean=28% sd=27%

Observers

CANOPY

10 8 6 4 2 0

Frequency

12 10 8 6 4 2 0

16 %

ROCK

49 % 73 % 98 % 12 2% 14 7% 17 1% 19 6% 22 0% 24 5% 26 9% 29 4% M or e

Frequency

C)

CV

10 %

Habitat

20

2%

50 % 54 % M or e

38 % 42 % 46 %

30 % 34 %

17 % 21 % 26 %

0

%

2

mean=16% sd=4%

16

4

mean=7% sd=4%

%

mean=38% sd=6%

13

mean=16% sd=7%

9%

6

LITTER

6 5 4 3 2 1 0

Frequency

Frequency

B)

PLANT 8

6%

A)

799

CV Habitat

Observers

Fig. 3 — Frequency distribution of mean coefficient of variation representing observers and habitat for each variable. A) PLANT, B) LITTER, C) ROCK, D) CANOPY, E) OBSTR1, F) OBSTR2, G) OBSTR3.

Braz. J. Biol., 62(4B): 795-800, 2002

800

FREITAS, S. R., CERQUEIRA, R. & VIEIRA, M. V.

DISCUSSION The device, which allows measurements to be taken in a fast, practical, simple, reliable, and comparable fashion, is practical since its use requires only one easily transportable measurement instrument and two observers, one to take measurements and the other to write on the field form. With only seven variables to learn and measure, its methodology is simple. In addition reliability and comparability of the results were demonstrated by the repeatability experiment. This method seems faster than most of those previously described, although such information is rarely reported (e.g., James & Shugart, 1970; Dueser & Shugart, 1978; Cooperrider, 1986; Ernest & Mares, 1986; Morrison et al., 1992). It can be used in any kind of forest, and is now being utilized as a standard method to describe habitat structure of the Atlantic Rainforest. This method standardization makes our habitat studies comparable, consequently strengthening results and conclusions. It is also a first step to wards creating models of habitat use, similar to those developed in other regions for a variety of terrestrial vertebrates in the neotropics (Van Horne & Wiens, 1991; Fielding & Haworth, 1995; Reading et al., 1996). Acknowledgments — We would like to thank Ricardo F. Leite, Paula Aprigliano, Natalie Olifiers, Cristiane Sousa, Marcia S. Mello, Karen Dinucci, Luciana M. Corado, Alice C. Caparelli, Davi Rojtenberg, André T. Garcia, Ronaldo S. da Silva, and Ernesto M. Alvarez for their help in testing the efficiency of this device in the field. We are very grateful to the staff of the Laboratório de Vertebrados for help in fieldwork, especially Rosana Gentile and Vitor Rademaker. Paula and Filipe Aprigliano did the drawings. Carlos E. V. Grelle, Diego Astúa de Moraes, Fernando Fernandez, Helena Bergallo, Luciana Araripe, Marina Anciães, Marcelo Passamani, Rosana Gentile, and Ricardo Santori reviewed the manuscript. Nélio P. Barros and Angela M. Marcondes gave technical and administrative support. The work was supported by grants from CAPES, CEPG/UFRJ, CNPq, FAPERJ, FAPESP, FINEP, FUJB/UFRJ, and PROBIO/PRONABIO/MMA.

REFERENCES

BIRNEY, E. C., GRANT, W. E. & BAIRD, D. D., 1976, Importance of vegetative cover to cycles of Microtus populations. Ecology, 57: 1043-1051. CASSINI, M. H. & GALANTE, M. L., 1992, Foraging under predation risk in the wild guinea pig: the effect of vegetation height on habitat utilization. Ann. Zool. Fennici, 29: 285-290. CERQUEIRA, R. & FREITAS, S. R., 1999, A new study method of microhabitat structure of small mammals. Rev. Bras. Biol., 59: 219-223. COOPERRIDER, A. Y., 1986, Habitat evaluation systems, pp. 757-776. In: A. Y. Cooperrider, R. J. Boyd & H. R. Stuart (eds.), Inventory and monitoring of wildlife habitat. Bur. Land Manage, Service Center, U.S. Department of the Interior, Denver. DUESER, R. D. & SHUGART Jr., H. H., 1978, Microhabitat in a forest floor small mammal fauna. Ecology, 59: 89-98. ERNEST, K. A. & MARES, M. A., 1986, Ecology of Nectomys squamipes the neotropical Water rat in central Brazil: home range habitat selection reproduction and behaviour. J. Zool., 210: 599-612. FIELDING, A. H. & HAWORTH, P. F., 1995, Testing the generality of bird-habitat models. Conserv. Biol., 9: 1466-1481. FREITAS, S. R., 1998, Variação espacial e temporal na estrutura do habitat e preferência de microhabitat por pequenos mamíferos na Mata Atlântica. M.S. Thesis, Museu Nacional, Universidade Federal do Rio de Janeiro, Rio de Janeiro, 168p. JAMES, F. C. & SHUGART Jr., H. H., 1970, A quantitative method of habitat description. Audubon Field Notes, 24: 727-736. JAMES, F. C., 1971, Ordinations of habitat relationships among breeding birds. Wilson Bull., 83: 216-236. MORRISON, M. L., MARCOT, B. G. & MANNAN, R. W., 1992, Wildlife-habitat relationships: concepts and applications. The University of Wisconsin Press, Madison, 364p. MURÚA, R., GONZÁLEZ, L. A. & JOFRÉ, Y. C., 1996, Latitidinal variation of habitat components in two species of Abrothrix (Rodentia: Cricetidae) in Chile. Medio Ambiente, 13: 3-10. READING, R. P., CLARK, T. W., SEEBECK, J. H. & PEARCE, J., 1996, Habitat suitability index model for the eastern barred bandicoot. Perameles gunnii. Wildl. Res., 23: 221-235.

AUGUST, P. V., 1983, The role of habitat complexity and heterogeneity in structuring tropical mammal communities. Ecology, 64: 1495-1507.

RIZZINI, C., 1979, Tratado de fitogeografia do Brasil: aspectos sociológicos e florísticos. 2o vol., Hucitec/ EdUSP, 375p.

BARNETT, A. & DUTTON, J., 1995, Describing the habitat, pp. 64-65. In: A. Barnett & J. Dutton (eds.), Expedition field techniques: small mammals (excluding bats). Expedition Advisory Centre, London.

THOMAS, J. W. & VERNER, J., 1986, Habitat evaluation systems, pp. 757-776. In: A. Y. Cooperrider, R. J. Boyd & H. R. Stuart (eds.), Inventory and monitoring of wildlife habitat. Bur. Land Manage, Service Center, U.S. Department of the Interior, Denver.

BARNUM, S. A., MANVILLE, C. J., TESTER, J. R. & CARMEN, W. J., 1992, Path selection by Peromyscus leucopus in the presence and absence of vegetative cover. J. Mamm., 73: 797-801.

Braz. J. Biol., 62(4B): 795-800, 2002

VAN HORNE, B. & WIENS, J. A., 1991, Forest bird habitat suitability models and the development of general habitat models. Fish and Wildl. Res., 8: 1-30.

Simone RF.p65 - Semantic Scholar

... Departamento de Ecologia, Universidade. Federal do Rio de Janeiro, C. P. 68020, CEP 21941-590, Rio de Janeiro, RJ, Brazil, e-mail: [email protected].br.

480KB Sizes 0 Downloads 289 Views

Recommend Documents

Physics - Semantic Scholar
... Z. El Achheb, H. Bakrim, A. Hourmatallah, N. Benzakour, and A. Jorio, Phys. Stat. Sol. 236, 661 (2003). [27] A. Stachow-Wojcik, W. Mac, A. Twardowski, G. Karczzzewski, E. Janik, T. Wojtowicz, J. Kossut and E. Dynowska, Phys. Stat. Sol (a) 177, 55

Physics - Semantic Scholar
The automation of measuring the IV characteristics of a diode is achieved by ... simultaneously making the programming simpler as compared to the serial or ...

Physics - Semantic Scholar
Cu Ga CrSe was the first gallium- doped chalcogen spinel which has been ... /licenses/by-nc-nd/3.0/>. J o u r n a l o f. Physics. Students http://www.jphysstu.org ...

Physics - Semantic Scholar
semiconductors and magnetic since they show typical semiconductor behaviour and they also reveal pronounced magnetic properties. Te. Mn. Cd x x. −1. , Zinc-blende structure DMS alloys are the most typical. This article is released under the Creativ

vehicle safety - Semantic Scholar
primarily because the manufacturers have not believed such changes to be profitable .... people would prefer the safety of an armored car and be willing to pay.

Reality Checks - Semantic Scholar
recently hired workers eligible for participation in these type of 401(k) plans has been increasing ...... Rather than simply computing an overall percentage of the.

Top Articles - Semantic Scholar
Home | Login | Logout | Access Information | Alerts | Sitemap | Help. Top 100 Documents. BROWSE ... Image Analysis and Interpretation, 1994., Proceedings of the IEEE Southwest Symposium on. Volume , Issue , Date: 21-24 .... Circuits and Systems for V

TURING GAMES - Semantic Scholar
DEPARTMENT OF COMPUTER SCIENCE, COLUMBIA UNIVERSITY, NEW ... Game Theory [9] and Computer Science are both rich fields of mathematics which.

A Appendix - Semantic Scholar
buyer during the learning and exploit phase of the LEAP algorithm, respectively. We have. S2. T. X t=T↵+1 γt1 = γT↵. T T↵. 1. X t=0 γt = γT↵. 1 γ. (1. γT T↵ ) . (7). Indeed, this an upper bound on the total surplus any buyer can hope

i* 1 - Semantic Scholar
labeling for web domains, using label slicing and BiCGStab. Keywords-graph .... the computational costs by the same percentage as the percentage of dropped ...

fibromyalgia - Semantic Scholar
analytical techniques a defect in T-cell activation was found in fibromyalgia patients. ..... studies pregnenolone significantly reduced exploratory anxiety. A very ...

hoff.chp:Corel VENTURA - Semantic Scholar
To address the flicker problem, some methods repeat images multiple times ... Program, Rm. 360 Minor, Berkeley, CA 94720 USA; telephone 510/205-. 3709 ... The green lines are the additional spectra from the stroboscopic stimulus; they are.

Dot Plots - Semantic Scholar
Dot plots represent individual observations in a batch of data with symbols, usually circular dots. They have been used for more than .... for displaying data values directly; they were not intended as density estimators and would be ill- suited for

Master's Thesis - Semantic Scholar
want to thank Adobe Inc. for also providing funding for my work and for their summer ...... formant discrimination,” Acoustics Research Letters Online, vol. 5, Apr.

talking point - Semantic Scholar
oxford, uK: oxford university press. Singer p (1979) Practical Ethics. cambridge, uK: cambridge university press. Solter D, Beyleveld D, Friele MB, Holwka J, lilie H, lovellBadge r, Mandla c, Martin u, pardo avellaneda r, Wütscher F (2004) Embryo. R

Physics - Semantic Scholar
length of electrons decreased with Si concentration up to 0.2. Four absorption bands were observed in infrared spectra in the range between 1000 and 200 cm-1 ...

aphonopelma hentzi - Semantic Scholar
allowing the animals to interact. Within a pe- riod of time ranging from 0.5–8.5 min over all trials, the contestants made contact with one another (usually with a front leg). In a few trials, one of the spiders would immediately attempt to flee af

minireviews - Semantic Scholar
Several marker genes used in yeast genetics confer resis- tance against antibiotics or other toxic compounds (42). Selec- tion for strains that carry such marker ...

PESSOA - Semantic Scholar
ported in [ZPJT09, JT10] do not require the use of a grid of constant resolution. We are currently working on extending Pessoa to multi-resolution grids with the.

PESSOA - Semantic Scholar
http://trac.parades.rm.cnr.it/ariadne/. [AVW03] A. Arnold, A. Vincent, and I. Walukiewicz. Games for synthesis of controllers with partial observation. Theoretical Computer Science,. 28(1):7–34, 2003. [Che]. Checkmate: Hybrid system verification to

SIGNOR.CHP:Corel VENTURA - Semantic Scholar
following year, the Brussels Treaty would pave the way for the NATO alliance. To the casual observer, unaware of the pattern of formal alliance commitments, France and Britain surely would have appeared closer to the U.S. than to the USSR in 1947. Ta

r12inv.qxp - Semantic Scholar
Computer. INVISIBLE COMPUTING. Each 32-bit descriptor serves as an independent .... GIVE YOUR CAREER A BOOST □ UPGRADE YOUR MEMBERSHIP.

fibromyalgia - Semantic Scholar
William J. Hennen holds a Ph.D in Bio-organic chemistry. An accomplished ..... What is clear is that sleep is essential to health and wellness, while the ..... predicted that in the near future melatonin administration will become as useful as bright

Bioinformatics Technologies - Semantic Scholar
and PDB were overlapping to various degrees (Table 3.4). .... provides flexibility in customizing analysis and queries, and in data ma- ...... ABBREVIATION.